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A general multi-trait-based framework for studying the effects of biodiversity on ecosystem functioning
Abstract
Environmental change is as multifaceted as are the species and communities that respond to these changes. Current theoretical approaches to modeling ecosystem response to environmental change often deal only with single environmental drivers or single species traits, simple ecological interactions, and/or steady states, leading to concern about how accurately these approaches will capture future responses to environmental change in real biological systems. To begin addressing this issue, we generalize a previous trait-based framework to incorporate aspects of frequency dependence, functional complementarity, and the dynamics of systems composed of species that are defined by multiple traits that are tied to multiple environmental drivers. The framework is particularly well suited for analyzing the role of temporal environmental fluctuations in maintaining trait variability and the resultant effects on community response to environmental change. Using this framework, we construct simple models to investigate two ecological problems. First, we show how complementary resource use can significantly enhance the nutrient uptake of plant communities through two different mechanisms related to increased productivity (over-yielding) and larger trait variability. Over-yielding is a hallmark of complementarity and increases the total biomass of the community and, thus, the total rate at which nutrients are consumed. Trait variability also increases due to the lower levels of competition associated with complementarity, thus speeding up the rate at which more efficient species emerge as conditions change. Second, we study systems in which multiple environmental drivers act on species defined by multiple, correlated traits. We show that correlations in these systems can increase trait variability within the community and again lead to faster responses to environmental change. The methodological advances provided here will apply to almost any function that relates species traits and environmental drivers to growth, and should prove useful for studying the effects of climate change on the dynamics of biota.
... Recently, the overall shape of the community functional trait distributions including kurtosis and skewness has been recognized as useful information to understand the causes of community assemblages and the consequences on ecosystem functioning (Chacón-Labella et al., 2022;Enquist et al., 2015). Briefly, the trait driver theory (Enquist et al., 2015;Norberg et al., 2001;Savage et al., 2007) assumes that: ...
... Such directional shifts may be better reflected by respectively (Enquist et al., 2015). In contrast to the niche complementarity hypothesis, the trait driver theory assumes that functional trait variance in communities leads to decreases in productivity in the simple case where a single trait underlies individual growth under a given stable environment (but see Savage et al., 2007 for a trait-based framework incorporating multiple traits and environmental drivers). As long as mean trait values are close to the optimum, positive kurtosis may increase productivity. ...
... Whereas fertilization tended to increase the degree of community-level overyielding, responses to fertilizer application varied widely by species composition (Fig. 3.6 & 3.7). Here, we interpret this context-dependent responses, based on the trait driver theory (Enquist et al., 2015;Norberg et al., 2001;Savage et al., 2007), which provides predictions regarding community responses to environmental changes (e.g., fertilization) and the resultant effects on ecosystem functioning (e.g., productivity). ...
... The This could improve understanding on how the ecological strategies and internal nutrient history of a wider range of common bioindicators influence their responses to nutrient enrichment (Sangil & Guzman, 2016;Zubia et al., 2018). For instance, by using this traitsbased approach, monitoring programs could build a suite of bioindicators functionally-similar species to obtain more ecologically-relevant information about the impacts of nutrients on a larger spatial scale (Savage et al., 2007;Mouillot et al., 2011;Hevia et al., 2016;McWilliam et al., 2018), particularly as it is less likely to weakened by distributional gaps of one species (Chapter 1; Linton & Warner, 2003). ...
... However, as Chapter 2 & 3 suggest that fluctuating nutrient regimes can result in the coexistence of multiple species within diverse macroalgal communities, it could be equally interesting to investigate the diversity of responses of macroalgae with a range of nutrient uptake, assimilation and/ or storage mechanisms within the same communities (functional diversity) (Nyström, 2006;Petchey & Gaston, 2006;Christie et al., 2019). This could allow scientists to directly compare functional redundancy against functional diversity to determine which of the two is able to capture a more realistic estimate of the overall high variability of nutrient regimes in these diverse communities (Nyström, 2006;Petchey & Gaston, 2006;Savage et al., 2007;McWilliams et al., 2018). In addition, this could help to improve understanding of how macroalgal community structure may change during a time when multiple stressors increasing in severity impacting these ecosystems, such as increasing rainfall and storms that tend to favour opportunistic algae . ...
... Therefore, a more cost-effective and ecologically relevant approach, especially in coastal areas with limited funds and resources, could involve collected macroalgal samples from a wide geographical area, perhaps even across multiple regions and countries, to build up a nutrient gradient within the ecological model. But in order to generate threshold point(s) of nutrient concentrations that can be generalised across large geographical areas, using the traits-based approach for a suite of congruent bioindicators will be more important than ever, as it will likely be impossible to collect the same species at every single site being surveyed (Gartner et al., 2002;Linton & Warner, 2003;Savage et al., 2007;Violle et al., 2007;Fong & Fong, 2014;Darling et al., 2017;Hevia et al., 2017;Bellwood et al., 2018;Zubia et al., 2018;Hu et al., 2019;McQuatters-Gollop et al., 2019;Bedford et al., 2020). Thus, identifying key functional traits in macroalgae (i.e. ...
Anthropogenic nutrient runoff is a major local stressor on coral reefs but compared to research on global climate change and overfishing, progress has been slower at quantifying its effects, particularly at the ecosystem scale. This is due to the difficulties in cost-effectively capturing the high spatio-temporal variability of bioavailable nutrients in reef systems. In this thesis, I examine common bioindicators and associated methodologies for assessing nutrient regimes as well as the relationships between nutrient and biological responses of the bioindicators. I first compare the precision and cost-effectiveness of five nutrient signatures (δ15N, δ13C, %N, %C and C:N Ratio) in a suite of eight indicators across 21 reefs around the inner Seychelles islands. I show that the congruency between the three most precise types (brown macroalgae, green macroalgae and zoanthids) was low, which was likely due to differences in species-specific ecological strategies (e.g. nutrient uptake and/ or storage capacity). I then test the theory that species within the same functional groups should respond similarly to nutrient enrichment using a) passive biomonitoring (sampling along a nutrient gradient) b) active biomonitoring (in situ reciprocal transplant experiment), and c) manipulative laboratory experiments (nutrient supply rates). Overall, these studies suggest that even the responses of morphologically-similar macroalgae with different strategies for nutrient uptake can vary over fine spatio-temporal scales, particularly if they are not nutrient-limited. Finally, I use one of these methodologies in a real-world scenario to investigate the influence of mass coral mortality events on δ15N signatures of transplanted macroalgae 1) before and after the 2016 bleaching event in the Seychelles, and 2) during the 2019 bleaching event in Mo’orea. Both case studies strongly imply that macroalgae can potentially take up this mass release of dead coral tissue, and possibly locking them into local biogeochemical cycles for up to a year after a bleaching event. I conclude that a traits-based approach, using a suite of congruent bioindicators with the same functional traits (i.e. rapid nutrient uptake), would be most cost-effective for future research and monitoring programs.
... One weakness induced by the simplification of phytoplankton communities in both aggregate and discrete models, however, is that competitive exclusion (Hardin, 1960;Hutchinson, 1961) often leads to a collapse of the modelled diversity (Merico et al., 2009), making adaptation impossible unless trait variance is artificially imposed (Norberg et al., 2012;Wirtz, 2013) or a mechanism is explicitly added to sustain it. One way to sustain biodiversity is through immigration from a distant community (Norberg et al., 2001;Savage et al., 2007). Yet, immigration does not explain the diversity observed in closed laboratory experiments, including continuous cultures (Fussmann et al., 2007;Kinnison and Hairston, 2007;Beardmore et al., 2011). ...
... Upgrading the trait diffusion framework to several traits requires more complex equations and the introduction of a new class of state variables: the covariances between traits. However, multi-trait models are more realistic, and conceptual modelling studies have shown that the dynamics of correlated traits sometimes differ from those of single-trait models (Savage et al., 2007). ...
... If at the same time the half-saturation is negatively correlated with optimal temperature (i.e. if phenotypes with low half-saturation constants also tend to have high optimal temperatures), the competition for nutrients will also increase the concentrations of phenotypes with high optimal temperatures, in addition to the effect of environment temperature. In the conceptual model of Savage et al. (2007), the inter-trait correlation in a two-trait model led to higher variances and to a considerable improvement in the ability of the mean phytoplankton traits to track optimal values controlled by environmental conditions compared with one-trait models. In order to know whether these results also apply to our model, we compare the dynamics of traits x and y in SPEAD to the dynamics of simplified one-trait models wherein either x or y varies between phenotypes and the other trait is optimized instantaneously (i.e. ...
Diversity plays a key role in the adaptive capacity of marine ecosystems to environmental changes.
However, modelling the adaptive dynamics of phytoplankton traits remains challenging due to the competitive exclusion of sub-optimal phenotypes and the complexity of evolutionary processes leading to optimal phenotypes.
Trait diffusion (TD) is a recently developed approach to sustain diversity in plankton models by introducing mutations, therefore allowing the adaptive evolution of functional traits to occur at ecological timescales. In this study, we present a model called Simulating Plankton Evolution with Adaptive Dynamics (SPEAD) that resolves the eco-evolutionary processes of a multi-trait plankton community. The SPEAD model can be used to evaluate plankton adaptation to environmental changes at different timescales or address ecological issues affected by adaptive evolution. Phytoplankton phenotypes in SPEAD are characterized by two traits, the nitrogen half-saturation constant and optimal temperature, which can mutate at each generation using the TD mechanism.
SPEAD does not resolve the different phenotypes as discrete entities, instead computing six aggregate properties: total phytoplankton biomass, the mean value of each trait, trait variances, and the inter-trait covariance of a single population in a continuous trait space. Therefore, SPEAD resolves the dynamics of the population's continuous trait distribution by solving its statistical moments, wherein the variances of trait values represent the diversity of ecotypes. The ecological model is coupled to a vertically resolved (1D) physical environment, and therefore the adaptive dynamics of the simulated phytoplankton population are driven by seasonal variations in vertical mixing, nutrient concentration, water temperature, and solar irradiance. The simulated bulk properties are validated by observations from Bermuda Atlantic Time-series Studies (BATS) in the Sargasso Sea.
We find that moderate mutation rates sustain trait diversity at decadal timescales and soften the almost total inter-trait correlation induced by the environment alone, without reducing the annual primary production or promoting permanently maladapted phenotypes, as occur with high mutation rates. As a way to evaluate the performance of the continuous trait approximation, we also compare the solutions of SPEAD to the solutions of a classical discrete entities approach, with both approaches including TD as a mechanism to sustain trait variance. We only find minor discrepancies between the continuous model SPEAD and the discrete model, with the computational cost of SPEAD being lower by 2 orders of magnitude. Therefore, SPEAD should be an ideal eco-evolutionary plankton model to be coupled to a general circulation model (GCM) of the global ocean.
... One weakness induced by the simplification of phytoplankton communities in both the aggregate and discrete models, however, is that competitive exclusion (Hardin, 1960;Hutchinson, 1961) often leads to a collapse of the modeled diversity 15 (Merico et al., 2009) unless trait variance is imposed (Norberg et al., 2012;Wirtz, 2013) or a mechanism is added explicitly to sustain it. One way to sustain biodiversity is through immigration from a distant community (Norberg et al., 2001;Savage et al., 2007). Yet, immigration does not explain the diversity observed in closed laboratory experiments, including continuous cultures (Fussmann et al., 2007;Kinnison and Hairston, 2007;Beardmore et al., 2011). ...
... If at the same time the half-saturation is negatively correlated with optimal temperature (i.e. if phenotypes with low half-saturation constants tend to also have a high optimal temperatures), the competition for nutrients will also increase the amount of phenotypes with high optimal temperatures, in addition to the 10 effect of environment temperature. In the conceptual model of Savage et al. (2007), the inter-trait correlation in a 2-trait model led to higher variances and to a considerable improvement in the ability of the mean phytoplankton traits to track optimal values controlled by environmental conditions compared with 1-trait models. In order to know whether these results also apply to our model, we compare the dynamics of traits x and y in SPEAD to the dynamics of simplified 1-trait models where either ...
... The trait dynamics of models with 2 traits differ from those of simpler and less realistic single-trait models. Savage et al. (2007) obtain larger trait variances and much larger adaptive capacities when two traits are modeled together rather than in separate models. In our study, we also find a larger adaptive capacity, although it is conveyed by inter-trait correlation only. ...
Diversity plays a key role in the adaptive capacities of marine ecosystems to environmental changes. However, modeling phytoplankton trait diversity remains challenging due to the strength of the competitive exclusion of sub-optimal phenotypes. Trait diffusion (TD) is a recently developed approach to sustain diversity in plankton models by allowing the evolution of functional traits at ecological timescales. In this study, we present a model for Simulating Plankton Evolution with Adaptive Dynamics (SPEAD), where phytoplankton phenotypes characterized by two traits, nitrogen half-saturation constant and optimal temperature, can mutate at each generation using the TD mechanism. SPEAD does not resolve the different phenotypes as discrete entities, computing instead six aggregate properties: total phytoplankton biomass, mean value of each trait, trait variances, and inter-trait covariance of a single population in a continuous trait space. Therefore SPEAD resolves the dynamics of the population's continuous trait distribution by solving its statistical moments, where the variances of trait values represent the diversity of ecotypes. The ecological model is coupled to a vertically-resolved (1D) physical environment, and therefore the adaptive dynamics of the simulated phytoplankton population are driven by seasonal variations in vertical mixing, nutrient concentration, water temperature, and solar irradiance. The simulated bulk properties are validated by observations from BATS in the Sargasso Sea. We find that moderate mutation rates sustain trait diversity at decadal timescales and soften the almost total inter-trait correlation induced by the environment alone, without reducing the annual primary production or promoting permanently maladapted phenotypes, as occur with high mutation rates. As a way to evaluate the performance of the continuous-trait approximation, we also compare the solutions of SPEAD to the solutions of a classical discrete entities approach, both approaches including TD as a mechanism to sustain trait variance. We only find minor discrepancies between the continuous model SPEAD and the discrete model, the computational cost of SPEAD being lower by two orders of magnitude. Therefore SPEAD should be an ideal eco-evolutionary plankton model to be coupled to a general circulation model (GCM) at the global ocean.
... One weakness induced by the simplification of phytoplankton communities in both aggregate and discrete models, however, is that competitive exclusion (Hardin, 1960;Hutchinson, 1961) often leads to a collapse of the modelled diversity (Merico et al., 2009), making adaptation impossible unless trait variance is artificially imposed (Norberg et al., 2012;Wirtz, 2013) or a mechanism is explicitly added to sustain it. One way to sustain biodiversity is through immigration from a distant community (Norberg et al., 2001;Savage et al., 2007). Yet, immigration does not explain the diversity observed in closed laboratory experiments, including continuous cultures (Fussmann et al., 2007;Kinnison and Hairston, 2007;Beardmore et al., 2011). ...
... Upgrading the trait diffusion framework to several traits requires more complex equations and the introduction of a new class of state variables: the covariances between traits. However, multi-trait models are more realistic, and conceptual modelling studies have shown that the dynamics of correlated traits sometimes differ from those of single-trait models (Savage et al., 2007). ...
... If at the same time the half-saturation is negatively correlated with optimal temperature (i.e. if phenotypes with low half-saturation constants also tend to have high optimal temperatures), the competition for nutrients will also increase the concentrations of phenotypes with high optimal temperatures, in addition to the effect of environment temperature. In the conceptual model of Savage et al. (2007), the inter-trait correlation in a two-trait model led to higher variances and to a considerable improvement in the ability of the mean phytoplankton traits to track optimal values controlled by environmental conditions compared with one-trait models. In order to know whether these results also apply to our model, we compare the dynamics of traits x and y in SPEAD to the dynamics of simplified one-trait models wherein either x or y varies between phenotypes and the other trait is optimized instantaneously (i.e. ...
Diversity plays a key role in the adaptive capacities of marine ecosystems to environmental changes. However, modeling phytoplankton trait diversity remains challenging due to the strength of the competitive exclusion of sub-optimal phenotypes. Trait diffusion (TD) is a recently developed approach to sustain diversity in plankton models by allowing the evolution of functional traits at ecological timescales. In this study, we present a model for Simulating Plankton Evolution with Adaptive Dynamics (SPEAD), where phytoplankton phenotypes characterized by two traits, nitrogen half-saturation constant and optimal temperature, can mutate at each generation using the TD mechanism. SPEAD does not resolve the different phenotypes as discrete entities, computing instead six aggregate properties: total phytoplankton biomass, mean value of each trait, trait variances, and inter-trait covariance of a single population in a continuous trait space. Therefore SPEAD resolves the dynamics of the population’s continuous trait distribution by solving its statistical moments, where the variances of trait values represent the diversity of ecotypes. The ecological model is coupled to a vertically-resolved (1D) physical environment, and therefore the adaptive dynamics of the simulated phytoplankton population are driven by seasonal variations in vertical mixing, nutrient concentration, water temperature, and solar irradiance. The simulated bulk properties are validated by observations from BATS in the Sargasso Sea. We find that moderate mutation rates sustain trait diversity at decadal timescales and soften the almost total inter-trait correlation induced by the environment alone, without reducing the annual primary production or promoting permanently maladapted phenotypes, as occur with high mutation rates. As a way to evaluate the performance of the continuous-trait approximation, we also compare the solutions of SPEAD to the solutions of a classical discrete entities approach, both approaches including TD as a mechanism to sustain trait variance. We only find minor discrepancies between the continuous model SPEAD and the discrete model, the computational cost of SPEAD being lower by two orders of magnitude. Therefore SPEAD should be an ideal eco-evolutionary plankton model to be coupled to a general circulation model (GCM) at the global ocean.
... The intention is not to examine statistical significance but to indicate the relative effect sizes of factors, calculated as η 2 . Commonly used benchmarks for small, medium and large effect sizes are 0.02, 0. 13 131 Local and Regional Components The realised regional response that mediated TL MC could be 132 decomposed into local and regional response mechanisms or components, the relative importance 133 and timescale of which depended on manipulated factors (above all inter-patch distance, Fig 4). ...
... Recasting biodiversity theory in terms of traits integrates the mech-386 anisms that generate and maintain diversity and allows scaling from individual fitness through 387 community trait distributions to ecosystem properties 3 . We have applied theory that predicts a 388 trait-lag in response to directional environmental change 10,13 to the metacommunity level to pro-389 pose a simple metric of integrated regional response capacity, the inverse of the integrated lag. ...
Climate change is altering the structure and functioning of communities ¹ . Trait-based approaches are powerful predictive tools that allow consideration of changes in structure and functioning simultaneously 2, 3 . The realised biomass-weighted trait distribution of a community rests on the ecophysiology of individuals, but integrates local species interactions and spatial dynamics that feed back to ecosystem functioning. Consider a response trait that determines species performance (e.g. growth rate) as a function of an environmental variable (e.g. temperature). The change in this response trait’s distribution following directional environmental change integrates all factors contributing to the community’s response and directly reflects the community’s response capacity ³ .
Here we introduce the average regional community trait-lag (TL MC ) as a novel measure of whole-metacommunity response to warming. We show that functional compensation (shifts in resident species relative abundances) confers initial response capacity to communities by reducing and delaying the initial development of a trait-lag. Metacommunity adaptive capacity in the long-term, however, was dependent on dispersal and species tracking of their climate niche by incremental traversal of the landscape. With increasing inter-patch distances, network properties of the functional connectivity network became increasingly more important, and may guide prioritisation of habitat for conservation.
... Recent advances in trait-based models are uncovering direct links between trait variation, environmental gradients and organismal fitness, the key to understanding the influence of selection on assemblage dynamics (Cornwell et al. 2006, Shipley et al. 2006, Savage et al. 2007, Suding et al. 2008, Dray and Legendre 2008, Messier et al. 2010, Shipley 2010, Mason et al. 2013, Warton et al. 2015a, Loranger et al. 2016, Ovaskainen et al. 2017. Traitbased models may involve empirically relating intra-and/ or inter-specific trait values to environmental variation using correlative models and projecting how the spatiotemporal distribution of traits and their performance across environmental gradients give rise to assemblage-level properties (Laughlin et al. 2012, Lasky et al. 2014, Laughlin and Messier 2015. ...
... Traitbased models may involve empirically relating intra-and/ or inter-specific trait values to environmental variation using correlative models and projecting how the spatiotemporal distribution of traits and their performance across environmental gradients give rise to assemblage-level properties (Laughlin et al. 2012, Lasky et al. 2014, Laughlin and Messier 2015. Alternatively, trait-based models may involve describing trait-environment relationships mechanistically from first principles (Norberg et al. 2001, Shipley et al. 2006, Savage et al. 2007, Jabot 2010, Enquist et al. 2015, Holt and Chesson 2016, Scherer et al. 2016, Galic et al. 2018. Such mechanistic models are highly theoretical and translate common notions of trait-based mechanisms into dynamic differential equations. ...
The difficulty of integrating multiple theories, data, and methods has slowed progress towards making unified inferences of ecological change generalizable across large spatial, temporal and taxonomic scales. However, recent progress towards a theoretical synthesis now provides a guiding framework for organizing and integrating all primary data and methods for spatiotemporal assemblage‐level inference in ecology. In this paper, we describe how recent theoretical developments can provide an organizing paradigm for linking advances in data collection and methodological frameworks across disparate ecological sub‐disciplines and across large spatial and temporal scales. First, we summarize the set of fundamental processes that determine change in multispecies assemblages across spatial and temporal scales by reviewing recent theoretical syntheses of community ecology. Second, we review recent advances in data and methods across the main sub‐disciplines concerned with ecological inference across large spatial, temporal and taxonomic scales, and organize them based on the primary fundamental processes they include, rather than the spatiotemporal scale of their inferences. Finally, we highlight how iteratively focusing on only one fundamental process at a time, but combining all relevant spatiotemporal data and methods, may reduce the conceptual challenges to integration among ecological sub‐disciplines. Moreover, we discuss a number of avenues for decreasing the practical barriers to integration among data and methods. We aim to reconcile the recent convergence of decades of thinking in community ecology and macroecology theory with the rapid progress in spatiotemporal approaches for assemblage‐level inference, at a time where a robust understanding of spatiotemporal change in ecological assemblages is more crucial than ever to conserve biodiversity.
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... Therefore, eqn 1 provides an ideal theoretical framework for investigating BEF relationships for microbial organisms having nearly continuous trait distributions. Note that eqn 1 can be easily extended to two or more traits (Wirtz & Eckhardt 1996;Savage et al. 2007). For the sake of simplicity, we herein assume that size is the only master trait for phytoplankton, because many key traits that quantify aspects of phytoplankton physiology, such as nutrient uptake and photosynthesis, vary systematically with size (Litchman & Klausmeier 2008;Finkel et al. 2010;Edwards et al. 2012Edwards et al. , 2015Marañ on 2015). ...
... The environment can encompass several dimensions, such as light, temperature and different nutrients in the case of autotrophs and food concentrations and qualities in the case of heterotrophs. The effective trait space is therefore multi-dimensional, with each dimension relating to one or more environmental axes (Savage et al. 2007). The details of each function relating traits and the environment may have far-reaching implications for the intricate interactions among the environment, biodiversity and ecosystem functioning. ...
While most biodiversity and ecosystem functioning (BEF) studies have found positive effects of species richness on productivity, it remain unclear whether similar patterns hold for marine phyto-plankton with high local richness. We use the continuous trait-based modelling approach, which assumes infinite richness and represents diversity in terms of the variance of the size distribution, to investigate the effects of phytoplankton size diversity on productivity in a three-dimensional ocean circulation model driven by realistic physics forcing. We find a slightly negative effect of size diversity on primary production, which we attribute to several factors including functional trait-environment interactions, flexible stoichiometry and the saturation of productivity at low diversity levels. The benefits of trait optimisation, whereby narrow size distributions enhance productivity under relatively stable conditions, tend to dominate over those of adaptive capacity, whereby greater diversity enhances the ability of the community to respond to environmental variability .
... A recent approach to solve this problem is to move from a species-to a trait-based perspective. This is not just a change in terminology but in concept, providing a mechanistic basis for biodiversity-ecosystem function relationships and improving our potential to identify general rules in community ecology (McGill et al., 2006;Savage et al., 2007;Hillebrand and Matthiessen, 2009). Functional traits are used to link species to their function in the ecosystem. ...
... Alternatively, functionally different entities are represented by a continuous trait value distribution ( Figure 10.1b right), which reduces model complexity (Wirtz and Eckhardt, 1996;Norberg, 2004;Tirok et al., 2011). Some studies used this so-called dynamic trait or gradient-dynamics approach to describe evolution (Abrams and Matsuda, 1997) and co-evolution of predator and prey (Dieckmann and Law, 1996), adaptive behavioral dynamics, and community dynamics (Savage et al., 2007;Merico et al., 2014). Both approaches are based on ordinary differential equations describing biomass dynamics in time. ...
Introduction Although the ubiquitous biodiversity-related flexibility of ecological systems is qualitatively well established, most empirical and theoretical studies regard ecological systems so far as units with rigid, predefined properties. The reason for this static approach is that incorporating the tremendous diversity and flexibility of natural systems into empirical and theoretical studies has been extremely challenging in terms of developing consistent mathematical frameworks and designing appropriate experiments. This approach has also been necessary owing to the lack of empirical data on the ability of species to change properties over time. A recent approach to solve this problem is to move from a species- to a trait-based perspective. This is not just a change in terminology but in concept, providing a mechanistic basis for biodiversity–ecosystem function relationships and improving our potential to identify general rules in community ecology (McGill et al., 2006; Savage et al., 2007; Hillebrand and Matthiessen, 2009). Functional traits are used to link species to their function in the ecosystem. They are well defined, measurable properties of individuals (e.g., edibility or diet selectivity) affecting their performance and responses to environmental changes and hence population and community dynamics as well as trophic interactions. The frequency distribution of functional traits (Figure 10.1a) enables a quantification of functional diversity. Large variation in trait values (e.g., a full range from highly edible, fast growing to almost inedible, slow growing species) implies a high functional diversity and vice versa. This trait distribution may be described by its shape and central tendency (Figure 10.1b) and may change in response to altered abiotic (e.g., temperature) and biotic conditions (e.g., predator density) and thus characterize the milieu with which individual organisms interact (McGill et al., 2006) (Figure 10.1c). Scientific Background Maintaining the different kinds of ecosystem services in a way that optimizes human well-being and economy is one of the most urgent tasks of our century, which challenges policy-makers as well as scientists. The frequency and intensity of land use, climate change, and other anthropogenically induced environmental disturbances are accelerating biodiversity declines worldwide. The negative impact of these processes on ecological systems (e.g., individuals, populations, communities, and food webs) may amplify each other: environmental changes can accelerate biodiversity loss and a reduced biodiversity may increase the sensitivity of ecological systems to environmental changes.
... A promising approach to linking plant functioning and ecosystem processes comes from trait-based scaling theory (Box 1). It assumes that for a given environment, for any trait closely associated with variation in plant growth or demography, there is a mean trait value and an optimal trait value that maximizes growth rate given the constraints of the environment Norberg et al., 2001;Savage, Webb, & Norberg, 2007). Recently, Feeley (2012) and Feeley et al. (2011) argued that the species composition of tropical forests is shifting because of increases in temperature associated with climate change. ...
... We assess six predictions from trait-based scaling theory (see Table 1; Enquist et al., 2015;Norberg et al., 2001;Savage et al., 2007). This theory builds on earlier work, including metabolic scaling theory (MST). ...
Aim
Tropical elevation gradients are natural laboratories to assess how changing climate can influence tropical forests. However, there is a need for theory and integrated data collection to scale from traits to ecosystems. We assess predictions of a novel trait‐based scaling theory, including whether observed shifts in forest traits across a broad tropical temperature gradient are consistent with local phenotypic optima and adaptive compensation for temperature.
Location
An elevation gradient spanning 3,300 m and consisting of thousands of tropical tree trait measures taken from 16 1‐ha tropical forest plots in southern Perú, where gross and net primary productivity (GPP and NPP) were measured.
Time period
April to November 2013.
Major taxa studied
Plants; tropical trees.
Methods
We developed theory to scale from traits to communities and ecosystems and tested several predictions. We assessed the covariation between climate, traits, biomass and GPP and NPP. We measured multiple traits linked to variation in tree growth and assessed their frequency distributions within and across the elevation gradient. We paired these trait measures across individuals within 16 forests with simultaneous measures of ecosystem net and gross primary productivity.
Results
Consistent with theory, variation in forest NPP and GPP primarily scaled with forest biomass, but the secondary effect of temperature on productivity was much less than expected. This weak temperature dependence appears to reflect directional shifts in several mean community traits that underlie tree growth with decreases in site temperature.
Main conclusions
The observed shift in traits of trees that dominate in more cold environments is consistent with an ‘adaptive/acclimatory’ compensation for the kinetic effects of temperature on leaf photosynthesis and tree growth. Forest trait distributions across the gradient showed overly peaked and skewed distributions, consistent with the importance of local filtering of optimal growth traits and recent shifts in species composition and dominance attributable to warming from climate change. Trait‐based scaling theory provides a basis to predict how shifts in climate have and will influence the trait composition and ecosystem functioning of tropical forests.
... With multitrait selection software, we can efficiently develop adaptable crop varieties that can withstand these challenges, ensuring sustainable agricultural practices and food security. It should be noted that multitrait selection is not only limited to genetic improvement in agriculture or animal science; along with GS, it also has important applications in fields such as forest preservation and restoration (Laverdière et al., 2022;Lenz et al., 2020) and biodiversity (Savage et al., 2007). ...
Selecting and mating parents in genomic selection are crucial in plant and animal breeding programs. During selection, researchers need to identify superior individuals to be parents considering multiple traits simultaneously, some of which act antagonistically; therefore, selection becomes complex. In this paper, we present an R package named MPS (Multitrait Parental Selection) to facilitate the selection process. MPS uses Bayesian optimization to identify superior individuals. Through the presented application examples, the MPS R package proves effective in multitrait genomic selection, enabling breeders to make informed decisions and achieve strong performance across multiple traits.
... A functional-trait-based approach offers a way to represent vegetation data at reach scale and beyond. Functional traits originate from ecological research and are morphological, physiological, and phenological attributes that can be measured at the individual plant level (Violle et al., 2007;Savage et al., 2007). These measured traits can either be an effect or response trait, whereby they either have an influence on or are influenced by their surrounding environment, respectively (Violle et al., 2007;Kattge et al., 2020). ...
Vegetation plays a critical role in the modulation of fluvial process and morphological evolution. However, adequately capturing the spatial and temporal variability and complexity of vegetation characteristics remains a challenge. Currently, most of the research seeking to address these issues takes place at either the individual plant scale or via larger-scale bulk roughness classifications, with the former typically seeking to characterise vegetation–flow interactions and the latter identifying spatial variation in vegetation types. Herein, we devise a method which extracts functional vegetation traits using UAV (uncrewed aerial vehicle) laser scanning and multispectral imagery and upscale these to reach-scale functional group classifications. Simultaneous monitoring of morphological change is undertaken to identify eco-geomorphic links between different functional groups and the geomorphic response of the system. Identification of four groups from quantitative structural modelling and two further groups from image analysis was achieved and upscaled to reach-scale group classifications with an overall accuracy of 80 %. For each functional group, the directions and magnitudes of geomorphic change were assessed over four time periods, comprising two summers and winters. This research reveals that remote sensing offers a possible solution to the challenges in scaling trait-based approaches for eco-geomorphic research and that future work should investigate how these methods may be applied to different functional groups and to larger areas using airborne laser scanning and satellite imagery datasets.
... Of course, the fact that real ecosystems have multiple species at each trophic level stands in sharp contrast to current models. However, the simplistic eco-evolutionary models might have some implications in real communities because a single trophic level in a community (e.g., all the prey species) may possibly be summarized by the total abundance and the community-weighted averages (CWA) of traits shared by composite species due to homoplasy or homology (Norberg et al. 2001;Savage et al. 2007;Tanaka and Yoshino 2009;Tanaka 2012). The dynamics of CWA can be driven by ecological processes without evolution, but it must be also influenced by trait evolution of individual species in real communities at the same time. ...
Eco-evolutionary feedback can result in periodic shifts with long intervals between alternative community states. Simulations using a food chain model with three trophic levels, namely the resource-prey–predator system, with evolution of an anti-predator trait possessed by the prey (prey trait) have shown long-term oscillations that ecological dynamics alone cannot attain. The alternative community states are characterized by stable states slowly changing with prey trait evolution and fast cycles at the lower two trophic levels. This shift of community dynamical states with large intervals was governed by the evolution of the prey trait. The abrupt state shifts between long and intermittent stationary periods were caused by the interaction between community ecological dynamics and trait evolution. We further examined the effects of genetic variation on the stability of the community. A faster evolutionary rate with larger genetic variance tended to stabilize eco-evolutionary dynamics.
... The trait-based approach is built on the assumption that a number of traits exist that link the environment to the performance of a plant, for example, growth and survival (Violle et al., 2007) and hence affect community composition and ecosystem functioning (Lavorel & Garnier, 2002;Garnier et al., 2016). This approach can better explain the variation in multiple ecosystem functions by focusing on the shifts of community functional compositions (Savage et al., 2007;Enquist et al., 2015), which have been extensively studied using aboveground plant traits (e.g. leaf traits). ...
Trait‐based approaches provide a useful framework to predict ecosystem functions under intensifying global change. However, our current understanding of trait‐functioning relationships mainly relies on aboveground traits. Belowground traits (e.g. absorptive root traits) are rarely studied although these traits are related to important plant functions.
We analyzed four pairs of analogous leaf and absorptive root traits of woody plants in a temperate forest and examined how these traits are coordinated at the community‐level, and to what extent the trait covariation depends on local‐scale environmental conditions. We then quantified the contributions of leaf and absorptive root traits and the environmental conditions in determining two important forest ecosystem functions, aboveground carbon storage, and woody biomass productivity.
The results showed that both morphological trait pairs and chemical trait pairs exhibited positive correlations at the community level. Absorptive root traits show a strong response to environmental conditions compared to leaf traits. We also found that absorptive root traits were better predictors of the two forest ecosystem functions than leaf traits and environmental conditions.
Our study confirms the important role of belowground traits in modulating ecosystem functions and deepens our understanding of belowground responses to changing environmental conditions.
... The current state of eco-evolutionary theory is not well equipped to deal with these questions. On one hand, quantitative genetics (Lande 1979;Lande and Arnold 1983) and other moment equation-based frameworks (Wirtz and Eckhardt 1996;Norberg et al. 2001;Savage et al. 2007;Sasaki and Dieckmann 2011;Merico et al. 2014) readily incorporate ITV into the models. However, even the versions of these models that can treat multiple species (Sasaki and Dieckmann 2011;Débarre et al. 2014) assume that the number of species is fixed rather than a dynamic outcome of eco-evolutionary community assembly. ...
How is trait diversity in a community apportioned between and within coevolving species? Disruptive selection may result in either a few species with large intraspecific trait variation (ITV) or many species with different mean traits but little ITV. Similar questions arise in spatially structured communities: heterogeneous environments could result in either a few species that exhibit local adaptation or many species with different mean traits but little local adaptation. To date, theory has been well-equipped to either include ITV or to dynamically determine the number of coexisting species, but not both. Here, we devise a theoretical framework that combines these facets and apply it to the above questions of how trait variation is apportioned within and between species in unstructured and structured populations, using two simple models of Lotka-Volterra competition. For unstructured communities, we find that as the breadth of the resource spectrum increases, ITV goes from being unimportant to crucial for characterizing the community. For spatially structured communities on two patches, we find no local adaptation, symmetric local adaptation, or asymmetric local adaptation, depending on how much the patches differ. Our framework provides a general approach to incorporate ITV in models of eco-evolutionary community assembly.
... Mechanistic studies of aquatic food-webs require an understanding of how plankton groups work as primary producers and consumers (Savage et al. 2007;Wallenstein and Hall 2012;Taherzadeh et al. 2019). The related functions are often formulated based on cell or body size as the main determinant of ecophysiology (Finkel et al. 2010;Serra-Pompei et al. 2020), of the trophic role of an organism in the ecosystem (Barnes et al. 2010;Boyce et al. 2015), or of both (Wirtz and Sommer 2013). ...
Mechanisticapproachestoplanktonfood-websoftenrelyonsize-basedmodels.Thesemodelsdescribe predator–preyrelationshipsbasedonpredator body or cell size. However, size-based representations of trophic relationships fail to encompass the diverse feeding behavior of dinoflagellates, which play an essential role in the food-web due to their abundance and ubiquity. Here, we introduce the specialization factor ( s ) as an effective trait, which aggregates over aspects of morphology, trophic strategy, and feeding behavior and quantifies the degree of specialization towards a specific prey size. We found that specialization to either the upper or lower edge of the prey size spectrum is connected to size independent trophic relations. As a result, dinoflagellates can be divided into three groups with distinct dependencies of optimal prey size on predator size: (1) mixotrophic engulfers specialized on small prey ( $$s=-1$$ s = - 1 ), (2) pallium feeders on large prey ( $$s=1$$ s = 1 ), and (3) neutral feeders ( $$s=0$$ s = 0 ) encompassing generalist engulfers and tube feeders. Our trait based approach elucidates the evolutionary significance of diverse feeding modes and specialization in dinoflagellates compared to phylogenetically older groups such as ciliates. It furthermore leads to a more accurate representation of trophic relationships of dinoflagellates in models and can provide, more generally, an efficient description of complex and diverse feeding relations in plankton food-webs.
... Much like the attributes of a plant type, plant functional traits are morphological, physiological, or phenological attributes that are measurable at the individual plant level (Savage, Webb and Norberg, 2007;Violle et al., 2007;Kattge et al., 2011). These measures can either be direct measures of a function such as photosynthesis or be a surrogate measure for a function such as leaf area. ...
The importance of vegetation within the fluvial domain is well established, influencing both flow and morphology, and has long been recognised as a key component of the river corridor. Despite this, adequately capturing the spatial and structural variability of vegetation for us to understand the eco-geomorphic feedbacks occurring at a range of scales remains a challenge. Currently, the focus of this research takes place at either the individual plant scale, looking into vegetation-flow interactions, or at larger scales, attempting to spatially discretise vegetation for bulk roughness metrics. Subsequently, hydrodynamic models are typically based around these bulk roughness values which exclude vegetation structure. The aim of this research is to attempt to bridge this gap and link the different scales of analysis to improve our understanding of eco-geomorphic interactions. This is achieved by: (1) Examining current remote sensing methods that may be used for fluvial research, (2) Developing a novel UAV based remote sensing system to collect plant scale data for reach scale analysis, (3) Extracting trait-based metrics for individual plants and upscaling these to reach scale extents, (4) Implementing these traits-based parameters in to a 2D hydrodynamic model. At present, the main trade offs in remote sensing centre around scale and resolution, whereby capturing larger areas reduces the detail of the phenomena being studied. Structure from Motion (SfM) photogrammetry has helped to bridge this gap yet fails to reconstruct topography in vegetated reaches and cannot resolve vegetation structure. These drawbacks have herein been overcome with the introduction of UAV based laser scanning techniques, capable of accurately capturing topography in vegetated reaches as well as resolving vegetation structure. This data can be used to extract traits-based vegetation metrics, identify individual guilds within a river corridor, and be scaled to spatially discretise vegetation structure at reach scales. Guilds are then evaluated against monitored morphological change to investigate eco-geomorphic feedbacks. These vegetation metrics and classifications are subsequently used to parameterise a 2D hydrodynamic model, showing the impact that vegetation discretisation methods have on model outputs. This research has developed methods for obtaining reach scale data on vegetation structure to better inform our understanding of eco-geomorphic feedbacks. The robustness and scalability of these methods presents future avenues of research, both within the fluvial domain and for other environmental research applications, where eco-geomorphic feedbacks have a major influence in shaping the Earth’s surface.
... However, trait-based ecology measures the properties of individuals, thus it must be scaled to community and ecosystems to predict their dynamics and functioning (Enquist et al., 2015). Additionally, it can be better explain the variation in multiple ecosystem functions by focusing on the shape and shifts of trait distributions in communities (Savage et al., 2007;Enquist et al., 2015). Therefore, examining how the functional composition of communities changes with environmental conditions is the key to understanding the role of persistent environment changes in driving community structure and ecosystem processes (Lavorel and Garnier, 2002;Funk et al., 2017;Wieczynski et al., 2019). ...
Understanding the trait–environment relationships has been a core ecological research topic in the face of global climate change. However, the strength of trait–environment relationships at the local and regional scales in temperate forests remains poorly known. In this study, we investigated the local and regional scale forest plots of the natural broad-leaved temperate forest in northeastern China, to assess what extent community-level trait composition depends on environmental drivers across spatial scales. We measured five key functional traits (leaf area, specific leaf area, leaf carbon content, leaf nitrogen content, and wood density) of woody plant, and quantified functional compositions of communities by calculating the “specific” community-weighted mean (CWM) traits. The sum of squares decomposition method was used to quantify the relative contribution of intraspecific trait variation to total trait variation among communities. Multiple linear regression model was then used to explore the community-level trait–environment relationships. We found that (i) intraspecific trait variation contributed considerably to total trait variation and decreased with the spatial scale from local to regional; (ii) functional composition was mainly affected by soil and topography factors at the local scale and climate factor at the regional scale, while explaining that variance of environment factors were decreased with increasing spatial scale; and (iii) the main environment driver of functional composition was varied depending on the traits and spatial scale. This work is one of the few multi-scale analyses to investigate the environmental drivers of community functional compositions. The extent of intraspecific trait variation and the strength of trait–environment relationship showed consistent trends with increasing spatial scale. Our findings demonstrate the influence of environmental filtering on both local- and regional-scale temperate forest communities, and contribute to a comprehensive understanding of trait–environment relationships across spatial scales.
... For example, a species with very low resistance to embolism may perform well in shallow WT but poorly in the deep WT forest where water stress is common. Scaling up, plant functional composition determines ecosystem function over environmental gradients and environmental change (Savage et al., 2007;Suding et al., 2008;Lavorel, 2013;Violle et al., 2014;Enquist et al., 2015). Applying this to our framework, we expect ecosystem functional responses (Table 1) over soil hydrological variation (Fig. 7a-c) to reflect the local longterm hydrological regime, with a larger dominance of species whose optimal responses are within frequent conditions of the local regime (e.g. ...
Tropical forest function is of global significance to climate change responses, and critically determined by water availability patterns. Groundwater is tightly related to soil water through the water table depth (WT), but historically neglected in ecological studies. Shallow WT forests (WT < 5 m) are underrepresented in forest research networks and absent in eddy flux measurements, although they represent c. 50% of the Amazon and are expected to respond differently to global‐change‐related droughts. We review WT patterns and consequences for plants, emerging results, and advance a conceptual model integrating environment and trait distributions to predict climate change effects. Shallow WT forests have a distinct species composition, with more resource‐acquisitive and hydrologically vulnerable trees, shorter canopies and lower biomass than deep WT forests. During ‘normal’ climatic years, shallow WT forests have higher mortality and lower productivity than deep WT forests, but during moderate droughts mortality is buffered and productivity increases. However, during severe drought, shallow WT forests may be more sensitive due to shallow roots and drought‐intolerant traits. Our evidence supports the hypothesis of neglected shallow WT forests being resilient to moderate drought, challenging the prevailing view of widespread negative effects of climate change on Amazonian forests that ignores WT gradients, but predicts they could collapse under very strong droughts.
... In fact, together with optimal temperature, size has been used as a major trait axis of marine phytoplankton in the celebrated DARWIN model (Follows et al., 2007;Barton et al., 2010;Dutkiewicz et al., 2020). With multiple traits, it becomes more complicated to evaluate the effect of trait diversity (including thermal diversity) on community temperature sensitivity because we not only need to consider the variance of one trait, but also the covariance between traits (Savage et al., 2007;Le Gland et al., 2020). Using the second order Taylor expansion, the community growth rate under a given set of environmental condition can be expressed as a function of the mean and (co)variances of the traits: ...
Scientists often use an exponential equation to model the responses of community metabolic rates to temperature, which however contradicts with the fact that the temperature performance curves of individual species are unimodal, and ignores the difference between intraspecific and interspecific temperature sensitivity. To address these issues, species thermal diversity needs to be considered. To explore how thermal diversity affects community temperature responses, I construct a nutrient-phytoplankton–zooplankton (NPZ) model in which phytoplankton is represented by multiple species with different temperature performance curves. Each curve is determined by a master thermal trait, optimal temperature. I then create two levels of phytoplankton thermal diversity by varying the zooplankton prey density-dependent feeding preference (if zooplankton prefers to feed on abundant prey, prey diversity is enhanced). I find that the responses of the community productivity to temperature is dampened at high diversity compared to low diversity, due to the lower interspecific temperature sensitivity than the intraspecific one. High thermal diversity also confers the community a better capacity to track the environmental temperature fluctuation and withstand high temperature inhibition. In addition, thermal diversity increases community mean optimal temperature. I propose that the community temperature sensitivity is not static and urge that distributions of thermal traits of natural assemblages ought to be measured.
... The effect-response framework has emerged within ecology as a powerful, if somewhat controversial (Savage et al. 2007, Luck et al. 2012, paradigm for understanding how the traits driving species' ecological assembly might be linked with their ecological functions Cabido 2001, Suding et al. 2008). Species' effect traits are associated with their ecological impact, including resource use, habitat modification, and contributions to nutrient cycling. ...
Functional traits mediate species' responses to, and roles within, their environment and are constrained by evolutionary history. While we have a strong understanding of trait evolution for macro‐taxa such as birds and mammals, our understanding of invertebrates is comparatively limited. Here, we address this gap in North American beetles with a sample of ground beetles (Carabidae), leveraging a large‐scale collection and digitization effort by the National Ecological Observatory Network (NEON). For 154 ground beetle species, we measured seven morphological traits, which we placed into a recently developed effect–response framework that characterizes traits by how they predict species' effects on their ecosystems or responses to environmental stressors. We then used cytochrome oxidase 1 sequences from the same specimens to generate a phylogeny and tested the evolutionary tempo and mode of the traits. We found strong phylogenetic signal in, and correlations among, ground beetle morphological traits. These results indicate that, for these species, beetle body shape trait evolution is constrained, and phylogenetic inertia is a stronger driver of beetle traits than (recent) environmental responses. Strong correlations among effect and response traits suggest that future environmental drivers are likely to affect both ecological composition and functioning in these beetles.
... If species have heritable variation in their traits, natural selection will act on that variation. In order to understand these effects, theorists and modelers have used models in quantitative genetics (Lande, 1979;Lande and Arnold, 1983) and moment-equation-based frameworks (Wirtz and Eckhardt, 1996;Norberg et al., 2001;Savage et al., 2007) where this variation and selection is taken into account. These types of models have been used to evaluate how intraspecific variation influences species coexistence (Barabás and D'Andrea, 2016) and how spatial gradients interact with standing variation (Norberg et al., 2012). ...
To understand how functional traits shape ecological communities it is necessary to understand both how traits across the community affect its functioning and how eco-evolutionary dynamics within the community change the traits over time. Of particular interest are so-called evolutionarily stable communities (ESCs), since these are the end points of eco-evolutionary dynamics and can persist over long time scales. One theoretical framework that has successfully been used for assembling ESCs is adaptive dynamics. However, this framework cannot account for intraspecific variation---neither locally nor across structured populations. On the other hand, in moment-based approaches, intraspecific variation is accommodated, but community assembly has been neglected. This is unfortunate as some questions regarding for example local adaptation vis-a-vis diversification into multiple species requires both facets. In this paper we develop a general theoretical framework that bridges the gap between these two approaches. We showcase how ESCs can be assembled using the framework, and illustrate various aspects of the framework using two simple models of resource competition. We believe this unifying framework could be of great use to address questions regarding the role of functional traits in communities where population structure, intraspecific variation, and eco-evolutionary dynamics are all important.
... In the context of global change (Worm et al., 2006), there is increasing interest in predicting ecosystem functioning and processes (Gogina et al., 2017) and many studies have focused on understanding the key role of organisms in benthic ecosystems (Gaston and Petchey, 2002;Queirós et al., 2015;Savage et al., 2007). The identity of species in terms of their activity and functional characteristics is known to influence both the intensity and the variability of ecosystem processes (Queirós et al., 2013;Renz et al., 2018;Solan et al., 2008). ...
In a changing environment, it is important to understand the contribution of faunal and microbial communities to ecosystem functioning. In this context, the present study aimed to explore the effect of organic matter inputs due to aquaculture on the interaction between microphytobenthos and macrofaunal traits related to bioturbation. The study was conducted in the vicinity of a fish farm in a semi-enclosed bay in Cephalonia (Eastern Mediterranean). Two different disturbance zones were compared – a control area and an area close to fish cages and, more specifically, at the edge of the Allowable Zone of Effect (AZE) subject to intermediate stress from aquaculture waste discharge. Bioturbation potential was the main driver shaping microphytobenthic community composition. While Euglenophytes prevailed in the benthic communities close to fish farms, Cyanobacteria were more abundant in the control area, indicating a shift from a microbially driven functioning to a more macrofaunal one near fish cages. Indeed, a shift from suspension feeding to predation and scavenging was recorded close to fish cages. This shift was caused by the interaction of different trophic groups, food availability, as well as the interference of the increased bioturbation in suspension feeding near fish cages. High bioturbation and bioirrigation potentials recorded near fish cages probably acted as moderators of the negative effects of organic matter deposition caused by fish farming. In conclusion, the benthic community close to fish cages was more diverse in terms of biological traits than at the control sites. This indicated the co-existence of species with different ecological strategies near fish cages.
... To date, the studies of a single functional trait have been widely conducted in many ecosystem types (Yu et al., 2018;Liu et al., 2019). However, there is evidence that studies based on only a single or few functional traits may limit the predictive power of the models of ecosystem responses (Savage et al., 2007). Instead, a suite of functional traits or the combination of functional traits such as the Leaf-Height-Seed strategy framework, which was considered to better reflect important functional axes that drive plant performance (Golodets et al., 2010;Wieczynski et al., 2019), are necessary to model ecosystem response to environmental change. ...
Understanding how environmental change alters the composition of plant assemblages is a major challenge in the face of global climate change. Researches accounting for site-specific trait values within forest communities help bridge plant economics theory and functional biogeography to better evaluate and predict relationships between environment and ecosystem functioning. Here, by measuring six functional traits (specific leaf area, leaf dry matter content, leaf nitrogen, and phosphorus concentration, leaf nitrogen/phosphorus, wood density) for 292 woody plant species (48,680 individuals) from 250 established permanent forest dynamics plots in five locations across the subtropical evergreen broadleaved forests (SEBLF) in China, we quantified functional compositions of communities by calculating four trait moments, i.e., community-weighted mean, variance, skewness, and kurtosis. The geographical (latitudinal, longitudinal, and elevational) patterns of functional trait moments and their environmental drivers were examined. Results showed that functional trait moments shifted significantly along the geographical gradients, and trait moments varied in different ways across different gradients. Plants generally showed coordinated trait shifts toward more conservative growth strategies (lower specific leaf area, leaf N and P concentration while higher leaf nitrogen/phosphorus and wood density) along increasing latitude and longitude. However, trends opposite to the latitudinal and longitudinal patterns appeared in trait mean values along elevation. The three sets of environmental variables (climate, soil and topography) explained 35.0–69.0%, 21.0–56.0%, 14.0–31.0%, and 16.0–30.0% of the variations in mean, variance, skewness, and kurtosis across the six functional traits, respectively. Patterns of shifts in functional trait moments along geographical gradients in the subtropical region were mainly determined by the joint effects of climatic and edaphic conditions. Climate regimes, especially climate variability, were the strongest driving force, followed by soil nutrients, while topography played the least role. Moreover, the relationship of variance, skewness and kurtosis with climate and their geographical patterns suggested that rare phenotypes at edges of trait space were selected in harsher environments. Our study suggested that environmental filtering (especially climate variability) was the dominant process of functional assembly for forest communities in the subtropical region along geographical gradients.
... However, this simple upscaling approach necessarily assumes that species' biomasses are constant relative to the timescale of the stressor's influence (such that it changes species' physiological rates but not their abundances). This approach can be extended via trait-driver theory, which allows species' traits (e.g., body size) that determine population responses to (multiple) stressors to dynamically modify population biomasses in the system [49,50]. However, this approach is currently limited in that it cannot accommodate realistic trophic and nontrophic interactions between species' populations. ...
Multiple stressors, such as warming and invasions, often occur together and have nonadditive effects. Most studies to date assume that stressors operate in perfect synchrony, but this will rarely be the case in reality. Stressor sequence and overlap will have implications for ecological memory – the ability of past stressors to influence future responses. Moreover, stressors are usually defined in an anthropocentric context: what we consider a short-term stressor, such as a flood, will span multiple generations of microbes. We argue that to predict responses to multiple stressors from individuals to the whole ecosystem, it is necessary to consider metabolic rates, which determine the timescales at which individuals operate and therefore, ultimately, the ecological memory at different levels of ecological organization.
... The concept of biological division of labor is chief among the reasons that increased bioproductivity can be observed in consortia (Brenner et al. 2008;Werner et al. 2014;Lindemann et al. 2016). Individual members in a complex community adopt specialized roles, allowing niche differentiation and functional complementarity that can enable more efficient resource utilization (Savage et al. 2007). This is reflected in higher bioproductivity yields (e.g., total biomass) from communities compared to populations containing one species, an observation that also applies in rationally designed systems (Eiteman et al. 2008;Shong et al. 2012). ...
Natural microbial communities consist of assemblies of species possessing distinct metabolic capacities. Diversification within the consortia leads to the division of labor between species, whereby the global population exhibits functional capabilities that are possessed by only a fraction of its members. Furthermore, community diversity is also associated with higher bioproductivities and robustness compared to microbial “monocultures”. In this review, we highlight both natural and engineered interactions between photosynthetic microbes and other organisms, with an emphasis on learning design principles of microbial communities through the process of building them from the “bottom up”. Rational design of relatively simple microbial communities is likely to substantially improve our understanding of much more complex natural consortia that have important ecological significance. Furthermore, a deeper understanding of effective design principles of microbial communities could enable the application of light-driven microbial cultures for a variety of environmental and biotechnological goals.
... The concept of biological division of labor is chief among the reasons that increased bioproductivity can be observed in consortia (Brenner et al. 2008;Werner et al. 2014;Hays et al. 2015;Lindemann et al. 2016). Individual members in a complex community adopt specialized roles, allowing niche differentiation and functional complementarity that can enable more efficient resource utilization (Savage et al. 2007). This is reflected in higher bioproductivity yields (e.g., total biomass) from communities compared to populations containing one species, an observation that also applies in rationally designed systems (Eiteman et al. 2008;Shong et al. 2012). ...
This book is about the role played by microbes in their community mode in sustaining ecosystems. The descriptions given in its chapters indicate clearly that microbial communities are more effective in delivering multifaceted benefits to the soil-plant system than those offered by microbial monocultures in planktonic modes. The role these communities play in a multitude of microbe-microbe and plant-microbe interactions have not yet been fully exploited to gain benefits in this field as well as to achieve sustainability in agriculture practices. Amply discussed are the beneficial characteristics and metabolic capacities of specific microbial groups and the use of microbial traits for the benefit of plant growth. The book suggests the need to develop new microbial technologies to utilize plant-associated microbes for increased crop productivity and agroecosystem balance in order to ensure sustainability. This also provides an effective guidance to scientists, academics, researchers, students and policy makers of the sphere to achieve the above outcomes.
... This raises the intriguing possibility that intricate interactions between microorganisms exchanging N intermediates are widespread in natural populations. Such a 'division of labour' may be beneficial as it could increase community productivity 55,56 . In addition, if a mosaic of functionally distinct symbiont strains is needed to run complete metabolic pathways, this could provide selective pressure to maintain symbiont diversity within individual hosts. ...
Genetic diversity of closely related free-living microorganisms is widespread and underpins ecosystem functioning, but most evolutionary theories predict that it destabilizes intimate mutualisms. Accordingly, strain diversity is assumed to be highly restricted in intracellular bacteria associated with animals. Here, we sequenced metagenomes and metatranscriptomes of 18 Bathymodiolus mussel individuals from four species, covering their known distribution range at deep-sea hydrothermal vents in the Atlantic. We show that as many as 16 strains of intracellular, sulfur-oxidizing symbionts coexist in individual Bathymodiolus mussels. Co-occurring symbiont strains differed extensively in key functions, such as the use of energy and nutrient sources, electron acceptors and viral defence mechanisms. Most strain-specific genes were expressed, highlighting their potential to affect fitness. We show that fine-scale diversity is pervasive in Bathymodiolus sulfur-oxidizing symbionts, and hypothesize that it may be widespread in low-cost symbioses where the environment, rather than the host, feeds the symbionts.
... This raises the intriguing possibility that intricate interactions between microorganisms exchanging N intermediates are widespread in natural populations. Such a 'division of labour' may be beneficial as it could increase community productivity 55,56 . In addition, if a mosaic of functionally distinct symbiont strains is needed to run complete metabolic pathways, this could provide selective pressure to maintain symbiont diversity within individual hosts. ...
Genetic diversity of closely-related free-living microbes is widespread and underpins ecosystem functioning, but most evolutionary theories predict that it destabilizes intimate mutualisms. Indeed, symbiont strain diversity has long assumed to be restricted in intracellular bacteria associated with animals. Here, we sequenced the metagenomes and metatranscriptomes of 18 Bathymodiolus mussel individuals from four species, covering their known distribution range at deep-sea hydrothermal vents in the Atlantic. We show that as many as 16 strains of intracellular, sulfur-oxidizing symbionts coexist in individual Bathymodiolus mussels. Co-occurring symbiont strains differed extensively in key metabolic functions, such as the use of energy and nutrient sources, electron acceptors and viral defense mechanisms. Most strain-specific genes were expressed, highlighting their adaptive potential. We show that fine-scale diversity is pervasive in Bathymodiolus symbionts, and hypothesize that it may be widespread in low-cost symbioses where the environment, not the host, feeds the symbionts.
... Trait-based ecological scaling theory predicts that plant traits will change in response to increasing global temperatures and provides a basis for evaluating the potential effects on albedo. This theory posits that there is an optimal set of traits to maximize plant growth for any given environment [8][9][10][11] . However, in a rapidly changing climate, the extant and optimal trait values may differ and be out of equilibrium. ...
Tropical forest leaf albedo (reflectance) greatly impacts how much energy the planet absorbs; however; little is known about how it might be impacted by climate change. Here, we measure leaf traits and leaf albedo at ten 1-ha plots along a 3,200-m elevation gradient in Peru. Leaf mass per area (LMA) decreased with warmer temperatures along the elevation gradient; the distribution of LMA was positively skewed at all sites indicating a shift in LMA towards a warmer climate and future reduced tropical LMA. Reduced LMA was significantly (P< 0.0001) correlated with reduced leaf near-infrared (NIR) albedo; community-weighted mean NIR albedo significantly (P< 0.01) decreased as temperature increased. A potential future 2 °C increase in tropical temperatures could reduce lowland tropical leaf LMA by 6–7 g m−2 (5–6%) and reduce leaf NIR albedo by 0.0015–0.002 units. Reduced NIR albedo means that leaves are darker and absorb more of the Sun’s energy. Climate simulations indicate this increased absorbed energy will warm tropical forests more at high CO2 conditions with proportionately more energy going towards heating and less towards evapotranspiration and cloud formation.
... Multi-level interactions play an important role in explaining the characteristics of systems that arise as collective behaviors or responses among different components. As an example in conservation biology, mammalian herbivory, invertebrate herbivory, and nutrient levels all interact to affect the survival, growth rates, and fecundity of rare plant species in a forest ecosystem (McGill et al., 2006;Savage et al., 2007;Webb et al., 2010;Dávalos et al., 2014;Enquist et al., 2015). Given this importance across diverse fields, many different interaction classification methodologies have been introduced. ...
Interactions are ubiquitous and have been extensively studied in many ecological, evolutionary, and physiological systems. A variety of measures—ANOVA, covariance, epistatic additivity, mutual information, joint cumulants, Bliss independence—exist that compute interactions across fields. However, these are not discussed and derived within a single, general framework. This missing framework likely contributes to the confusion about proper formulations and interpretations of higher-order interactions. Intriguingly, despite higher-order interactions having received little attention, they have been recently discovered to be highly prevalent and to likely impact the dynamics of complex biological systems. Here, we introduce a single, explicit mathematical framework that simultaneously encompasses all of these measures of pairwise interactions. The generality and simplicity of this framework allows us to establish a rigorous method for deriving higher-order interaction measures based on any of the pairwise interactions listed above. These generalized higher-order interaction measures enable the exploration of emergent phenomena across systems such as multiple predator effects, gene epistasis, and environmental stressors. These results provide a mechanistic basis to better account for how interactions affect biological systems. Our theoretical advance provides a foundation for understanding multi-component interactions in complex systems such as evolving populations within ecosystems or communities.
... Examples of such natural 66 microbial consortia include metabolically interacting communities in soil (Venail and 67 Vives, 2013) and in the mammalian gut (Rakoff-Nahoum et al., 2016). Distributing 68 metabolic capabilities over multiple species, a form of functional complementarity, can 69 increase productivity of the consortium through more efficient resource utilization 70 ((Pande et al., 2014;Savage et al., 2007). 71 ...
In nature, microbes interact antagonistically, neutrally or beneficially. To shed light on the effects of positive interactions in microbial consortia we introduced metabolic dependencies and metabolite overproduction into four bacterial species. While antagonistic interactions govern the wildtype consortium behavior, the genetic modifications alleviated antagonistic interactions and resulted in beneficial interactions. Engineered cross-feeding increased population evenness, a component of ecological diversity, in different environments including in a more complex gnotobiotic mouse gut environment. Our findings suggest that metabolite cross-feeding could be used as a tool for intentionally shaping microbial consortia in complex environments.
Importance
Microbial communities are ubiquitous in nature. Bacterial consortia live in and on our body and in our environment and more recently, biotechnology is applying microbial consortia for bioproduction. As part of our body, bacterial consortia influence us in health and disease. Microbial consortia function is determined by its composition, which in turn is driven by the interactions between species. Further understanding of microbial interactions will help us deciphering how consortia function in complex environments and may enable us to modify microbial consortia for health and environmental benefits.
... The first explanation, frequently termed the 'sampling hypothesis,' is that more diverse communities are statistically more likely to contain members with varying tolerance to environmental stressors, so that, as conditions change, organisms displaying a higher degree of fitness under given conditions fill the functional void left by intolerant members (Loreau et al., 2001). In contrast, niche differentiation, and more specifically, functional complementarity, leads to gains in productivity-that is, 'overyielding'through more efficient resource utilization and elevated resistance to environmental perturbation (Savage et al., 2007). More recently, a view of communities as functionally degenerate networks has asserted that rewiring of individual member functions and interactions between members may buffer overall community function against environmental perturbation (Hastings, 2010;Shade et al., 2012). ...
Microbes live in dynamic environments where nutrient concentrations fluctuate. Quantifying fitness (birth and death) in a wide range of environments is critical for understanding microbial evolution as well as ecological interactions where one species alters the fitness of another. Here, using high-throughput time-lapse microscopy, we have quantified how Saccharomyces cerevisiae mutants incapable of synthesizing an essential metabolite grow or die in various concentrations of the required metabolite. We establish that cells normally expressing fluorescent proteins lose fluorescence upon death and that the total fluorescence in an imaging frame is proportional to the number of live cells even when cells form multiple layers. We validate our microscopy approach of measuring birth and death rates using flow cytometry, cell counting, and chemostat culturing. For lysine-requiring cells, very low concentrations of lysine are not detectably consumed and do not support cell birth, but delay the onset of death phase and reduce the death rate. In contrast, in low hypoxanthine, hypoxanthine-requiring cells can produce new cells, yet also die faster than in the absence of hypoxanthine. For both strains, birth rates under various metabolite concentrations are better described by the sigmoidal-shaped Moser model than the well-known Monod model, while death rates depend on the metabolite concentration and can vary with time. Our work reveals how time-lapse microscopy can be used to discover non-intuitive microbial dynamics and to quantify growth rates in many environments.
... Recently, aggregated trait-based modeling using adaptive traits to dynamically simulate average community properties has been suggested as an alternative approach to investigate community dynamics (e.g. [11][12][13][14][15][16]). Aggregated trait based modelling with adaptive traits does not resolve details of the communities investigated but only models few statistical properties of the community, typically the community biomass and the average and the variance of the community trait distribution. ...
Trait selection and co-existence in phytoplankton communities in partially mixed water columns is investigated using trait based modelling. In the models employed, trait selection results from phytoplankton competition for two limiting resources, light and nutrients. The study employs spatially resolved models, in which the phytoplankton community is represented as a large number of trait-groups characterized by fixed trait combinations (trade-offs). Results from the trait-group resolving model (RM) are compared to results from an aggregated trait based model with adaptive traits (AM). Differences in specific production resulting from a trade-off between the half saturation constants of light and nutrients are sufficient to support evolutionary stable co-existence confirming that co-existence does not require differences in resource consumption. If abiotic conditions lead to the selection of a single trait group in RM, AM provides excellent approximations of the development of total biomass, average community trait and trait variance in the phytoplankton community. However, if selection leads to bimodal trait distributions, e.g. to co-existence of two trait groups (or species), functionally important properties of the phytoplankton community cannot be adequately represented by the aggregated information provided by AM. Because the increase in variance due to the development of bimodal trait distributions cannot be distinguished from an increase in variance due to an increase in trait diversity, the development of trait variance in AM models is not a reliable measure of trait diversity. Furthermore, AM may not provide reliable simulations of trophic interactions if the performance of the consumers depends on the traits of their resources. However, AM may support exploration of the consequences of environmental conditions and of the parameterization of species for co-existence within communities.
... The deviations between the aggregate and full models depended on all five factors investigated: the aggregate property considered (i.e., the changes in the biomass, trait, or variance), the strength and curvature of the non-linearity in the fitness function, the type of aggregate model, the variance, and the shape of the trait distribution. We found distinct patterns for the first two factors: The quality of the fit consistently declined from the biomass to the trait dynamics and particularly to the variance dynamics, and with increasing non-linearity of the fitness function as expected from theory (Savage et al. 2007;Merico et al. 2009). The impact of the other three factors was more complex and context dependent. ...
The shape of trait distributions may inform about the selective forces that structure ecological communities. Here, we present a new moment-based approach to classify the shape of observed biomass-weighted trait distributions into normal, peaked, skewed, or bimodal that facilitates spatio-temporal and cross-system comparisons. Our observed phytoplankton trait distributions exhibited substantial variance and were mostly skewed or bimodal rather than normal. Additionally, mean, variance, skewness und kurtosis were strongly correlated. This is in conflict with trait-based aggregate models that often assume normally distributed trait values and small variances. Given these discrepancies between our data and general model assumptions we used the observed trait distributions to test how well different aggregate models with first- or second-order approximations and different types of moment closure predict the biomass, mean trait, and trait variance dynamics using weakly or moderately nonlinear fitness functions. For weakly non-linear fitness functions aggregate models with a second-order approximation and a data-based moment closure that relied on the observed correlations between skewness and mean, and kurtosis and variance predicted biomass and often also mean trait changes fairly well and better than models with first-order approximations or a normal-based moment closure. In contrast, none of the models reflected the changes of the trait variances reliably. Aggregate model performance was often also poor for moderately nonlinear fitness functions. This questions a general applicability of the normal-based approach, in particular for predicting variance dynamics determining the speed of trait changes and maintenance of biodiversity. We evaluate in detail how and why better approximations can be obtained.
As climate change unravels, ecosystems are facing a warming of the climate and an increase in extreme heat events that are unprecedented in recent geological history. We know very little of the ability of oceanic phytoplankton communities, key players in the regulation of Earth's climate by the oceans, to adapt to these changes. Quantifying the resilience of phytoplankton communities to environmental stressors by means of adaptive evolution is however crucial to accurately predict the response of marine ecosystems to climate change. In this work, we use an eco-evolutionary model to simulate the adaptive response of marine phytoplankton to temperature changes in an initially temperate oligotrophic water-column. By exploring a wide range of scenarios of phytoplankton adaptive capacity, we find that phytoplankton can adapt to temperature increases-even very large ones-as long as they occur over the time scale of a century. However, when rapid and extreme events of temperature change are considered, the phytoplankton adaptive capacity breaks down in a number of our scenarios in which primary productivity plummets as a result. This suggests that current Earth System Models assuming perfect phytoplankton adaptatedness to temperature might be overestimating the phytoplankton's resilience to climate change.
As climate change unravels, ecosystems are facing a warming of the climate and an increase in extreme heat events that are unprecedented in recent geological history. We know very little of the ability of oceanic phytoplankton communities, key players in the regulation of Earth's climate by the oceans, to adapt to these changes. Quantifying the resilience of phytoplankton communities to environmental stressors by means of adaptive evolution is however crucial to accurately predict the response of marine ecosystems to climate change. In this work, we use an eco-evolutionary model to simulate the adaptive response of marine phytoplankton to temperature changes in an initially temperate oligotrophic water-column. By exploring a wide range of scenarios of phytoplankton adaptive capacity, we find that phytoplankton can adapt to temperature increases, even very large ones, as long as they occur over the time scale of a century. However, when rapid and extreme events of temperature change are considered, the phytoplankton adaptive capacity breaks down in a number of our scenarios in which primary productivity plummets as a result. This suggests that current Earth System Models implicitly assuming perfect and instantaneous phytoplankton adaptation to temperature might be overestimating the phytoplankton's resilience to climate change.
Pesticides constitute an integral part of modern agriculture. However, there are still concerns about their effects on non-target organisms. To address this the European Commission has imposed a stringent regulatory scheme for new pesticide compounds. Assessment of the aquatic toxicity of pesticides is based on a range of advanced tests. This does not apply to terrestrial ecosystems, where the toxicity of pesticides on soil microorganisms, is based on an outdated and crude test (N mineralization). This regulatory gap is reinforced by the recent methodological and standardization advances in soil microbial ecology. The inclusion of such standardized tools in a revised risk assessment scheme will enable the accurate estimation of the toxicity of pesticides on soil microorganisms and on associated ecosystem services. In this review we (i) summarize recent work in the assessment of the soil microbial toxicity of pesticides and point to ammonia-oxidizing microorganisms (AOM) and arbuscular mycorrhizal fungi (AMF) as most relevant bioindicator groups (ii) identify limitations in the experimental approaches used and propose mitigation solutions, (iii) identify scientific gaps and (iv) propose a new risk assessment procedure to assess the effects of pesticides on soil microorganisms.
Upon their application pesticides end up in soil where they interact with the soil microbial community. Considering the pivotal role of soil microorganisms in ecosystem homeostasis and the growing evidence about their potential toxicity response to pesticide exposure, there is an urgent need to revisit the relevant regulatory framework. This is necessary in light of the enormous methodological and standardization advances in soil microbial ecology in the last 20 years and the outdated assessment scheme currently in place. In this chapter we highlight the key elements of a new risk assessment scheme including (a) the definition of microbial indicator groups like ammonia-oxidizing microorganisms and arbuscular mycorrhizal fungi (b) the parallel determination of the level and the duration of the exposure including transformation products (c) the need for implementation in environmental risk analysis of advanced and standardized tools. Based on all these a new tiered-risk assessment scheme is proposed. Emerging issues in soil microbial ecotoxicology are discussed including (a) the assessment of pesticide soil microbial toxicity at ecosystem level and (b) the assessment of the soil microbial toxicity of biopesticides, pesticide mixtures and pesticide transformation products on soil microorganisms. We conclude by highlighting emerging scientific questions that are expected to puzzle the soil microbial ecotoxicologists working with pesticides in the next decade.
Vegetation plays a critical role in the modulation of fluvial process and morphological evolution. However, adequately capturing the spatial variability and complexity of vegetation characteristics remains a challenge. Currently, most of the research seeking to address these issues takes place at either the individual plant scale or via larger scale bulk classifications, with the former seeking to characterise vegetation-flow interactions and the latter identifying spatial variation in vegetation types. Herein, we devise a method which extracts functional vegetation traits using UAV laser scanning and multispectral imagery, and upscale these to reach scale guild classifications. Simultaneous monitoring of morphological change is undertaken to identify eco-geomorphic links between different guilds and the geomorphic response of the system in the context of long-term decadal changes. Identification of four guilds from quantitative structural modelling based on analysis of terrestrial and UAV based laser scanning and two further guilds from image analysis was achieved. These were upscaled to reach-scale guild classifications with an overall accuracy of 80 % and links to magnitudes of geomorphic activity explored. We show that different vegetation guilds have a role in influencing morphological change through the stabilisation of banks, but that limits on this influence are evident in the prior long-term analysis. This research reveals that remote sensing offers a solution to the difficulty of scaling traits-based approaches for eco-geomorphic research, and that these methods may be applied to larger areas using airborne laser scanning and satellite imagery datasets.
Functional traits mediate species' responses to and roles within their environment, and are constrained by evolutionary history. While we have a strong understanding of trait evolution for macro-taxa such as birds and mammals, our understanding of invertebrates is comparatively limited. Here we address this gap in North American beetles with a sample of ground beetles (Carabidae), leveraging a large-scale collection and digitization effort by the National Ecological Observatory Network (NEON). For 154 ground beetle species, we measured seven morphological traits, which we placed into a recently-developed effect-response framework that characterizes traits by how they predict species' effects on their ecosystems or responses to environmental stressors. We then used cytochrome oxidase one sequences from the same specimens to generate a phylogeny and tested evolutionary tempo and mode of the traits. We found strong phylogenetic signal in, and correlations among, morphological ground beetle traits. These results indicate that, for these species, beetle body shape trait evolution is constrained, and phylogenetic inertia is a stronger driver of beetle traits than (recent) environmental responses. Strong correlations among effect and response traits suggest that future environmental drivers are likely to affect both ecological composition and functioning in these beetles.
Trait-based approaches focus on the functional traits that define how organisms interact with the environment and each other. They represent an efficient way to capture different aspects of diversity in ecological models, which is essential for understanding community structure and ecosystem functioning, both now and in the future. There is an extensive history of trait-based approaches in theoretical ecology, enriched by an expanding array of complementary frameworks. In this chapter, we give a pedagogical introduction to one such framework—adaptive dynamics—explaining how to both set up and analyse models and surveying a range of applications. Then we show how adaptive dynamics relates to other frameworks, including species sorting, ecological quantitative genetics, and moment methods, highlighting the differences and connections between them. We then consider how these basic theories can be extended to incorporate temporal and spatial heterogeneity and multiple traits. Finally, we outline some frontiers of trait-based theory, including connections with empirical systems, linking trait- and species-based approaches, and embedding trait-based approaches in Earth system models.
De par la difficulté à relier dans un même cadre mécaniste et dynamique, la composition, la structure et la fonction de ses acteurs, le fonctionnement des communautés végétales reste encore mal connu. Récemment les traits fonctionnels ont été proposés comme un outil quantitatif et comparatif permettant de faire le lien entre dynamique et fonctionnement des communautés. Les traits sont des adaptations morphologiques ou écophysiologiques en réponse aux facteurs physiques et biotiques du milieu (traits de réponse). Ces traits génèrent en retour un effet sur le fonctionnement du milieu (traits d’effet). La connexion entre traits de réponse et traits d’effet permet ainsi de lier les plantes à leur environnement. Mais les mécanismes sous-jacents à ce lien restent encore peu explorés et constituent l'objectif d'étude de la thèse. Nous avons utilisé les traits des espèces végétales dans un modèle biogéochimique. GEMINI (Grassland Ecosystem Model with INdividual centered Interactions) que nous avons développé, calibré et utilisé sur 13 espèces de graminées pérennes représentatives de la flore des prairies permanentes mésiques. Les sorties du modèle ont ensuite été comparées à des mesures de la production et de l’abondance de ces espèces en culture pure et en mélange. Nous avons validé dans un premier temps une hypothèse originale du modèle concernant la stoechiométrie de l'équilibre carbone/azote des plantes. Cette hypothèse de coordination de la photosynthèse qui prévoit une colimitation par les réactions claires et par les réactions sombres, a été testée sur une base de données regroupant 31 espèces appartenant à 6 types fonctionnels. Cette hypothèse explique sans biais 92 % de la variance totale de la teneur en N par unité de surface foliaire grâce aux variations de trois traits photosynthétiques. Les équations d’allocation entre structure foliaire et protéines photosynthétiques du modèle ont ainsi été vérifiées et calibrées. Dans un second temps, les traits fonctionnels liés à l’absorption de l’azote, à son utilisation et à sa résorption au cours de la sénescence ont été mesurés en culture pure au champ sur les 13 espèces. Nous avons montré de manière mécaniste les relations fondamentales existant entre les traits racinaires et les traits foliaires (taille vs activité physiologique). De plus, des compromis fonctionnels interspécifiques ont été mis en évidence entre : 1) les capacités racinaires d’absorption de NO3 - et de NH4 +, 2) la surface racinaire développée dans un patch de ressource et la capacité d’absorption de l’azote. Ces résultats ont permis d’intégrer traits racinaires et aériens dans les stratégies liées à l’azote, puis de paramétrer le modèle GEMINI. Les simulations réalisées à la suite des modifications portées au modèle indiquent plusieurs propriétés émergentes : 1) après défoliation, ou privation d’azote, les ajustements plastiques de la taille relative des compartiments et de leur activité physiologique rétablissent un équilibre fonctionnel aboutissant à une colimitation de la croissance végétale par la lumière, le CO2 et l’azote. 2) à l’équilibre, la taille et la densité des talles simulées varient entre espèces en raison d’un coefficient puissance -3/4. Le modèle permet de simuler les variations de la production végétative entre espèces et entre traitements de coupe et d’azote, en culture pure et en mélange. Les classements observés d’abondance relative des graminées dans des mélanges de 6 espèces sont significativement prédits. Enfin, le modèle simule un effet positif de la diversité spécifique, avec une production des mélanges de 6 espèces supérieure à celle de l’ensemble des cultures pures. Lorsque le modèle est simplifié, en omettant de simuler la morphogénèse ou la coordination de la croissance, son pouvoir de prédiction est fortement dégradé. La version actuelle du modèle offre des perspectives intéressantes afin d'étudier des questions fondamentales en écologie des communautés et en écologie fonctionnelle. Nous fournissons un exemple d'application s'intéressant à l'origine des covariations entre traits morphologiques observés dans la nature. Pour quatre traits représentatifs des stratégies des 13 espèces étudiées ici, une étude systématique dans l’espace à 4 dimensions formé par ces traits a montré que : 1) la valeur mesurée des traits maximise la croissance simulée, 2) en réponse à une carence en azote, la plasticité observée des traits maximise la croissance simulée des espèces. Ces résultats ont permis de comprendre les contraintes résultant des compromis intra et interspécifiques entre traits et de souligner l’importance de la plasticité pour la performance de ces graminées sur des gradients de ressource.
Les communautés végétales constituent des systèmes complexes au sein desquels de nombreuses espèces, pouvant présenter une large variété de traits fonctionnels, interagissent entre elles et avec leur environnement. En raison de la quantité et de la diversité de ces interactions les mécanismes qui gouvernent les dynamiques des ces communautés sont encore mal connus. Les approches basées sur la modélisation permettent de relier de manière mécaniste les processus gouvernant les dynamiques des individus ou des populations aux dynamiques des communautés qu'ils forment. L'objectif de cette thèse était de développer de telles approches et de les mettre en oeuvre pour étudier les mécanismes sous-jacents aux dynamiques des communautés. Nous avons ainsi développé deux approches de modélisation. La première s'appuie sur un cadre de modélisation stochastique permettant de relier les dynamiques de populations aux dynamiques des communautés en tenant compte des interactions intra- et interspécifiques et de l'impact des variations environnementale et démographique. Cette approche peut-être aisément appliquée à des systèmes réels et permet de caractériser les populations végétales à l'aide d'un petit nombre de paramètres démographiques. Cependant nos travaux suggèrent qu'il n'existe pas de relation simple entre ces paramètres et les traits fonctionnels des espèces, qui gouvernent pourtant leur réponse aux facteurs externes. La seconde approche a été développée pour dépasser cette limite et s'appuie sur le modèle individu-centré Nemossos qui représente de manière explicite le lien entre le fonctionnement des individus et les dynamiques de la communauté qu'ils forment. Afin d'assurer un grand potentiel d'application à Nemossos, nous avons apportés une grande attention au compromis entre réalisme et coût de paramétrisation. Nemossos a ainsi pu être entièrement paramétré à partir de valeur de traits issues de la littérature , son réalisme a été démontré, et il a été utilisé pour mener des expériences de simulations numériques sur l'importance de la variabilité temporelle des conditions environnementales pour la coexistence d'espèces fonctionnellement différentes. La complémentarité des deux approches nous a permis de proposer des éléments de réponse à divers questions fondamentales de l'écologie des communautés incluant le rôle de la compétition dans les dynamiques des communautés, l'effet du filtrage environnemental sur leur composition fonctionnelle ou encore les mécanismes favorisant la coexistence des espèces végétales. Ici ces approches ont été utilisées séparément mais leur couplage peut offrir des perspectives intéressantes telles que l'étude du lien entre le fonctionnement des plantes et les dynamiques des populations. Par ailleurs chacune des approches peut être utilisée dans une grande variété d'expériences de simulation susceptible d'améliorer notre compréhension des mécanismes gouvernant les communautés végétales.
From biosynthesis to bioremediation, microbes have been engineered to address a variety of biotechnological applications. A promising direction in these endeavors is harnessing the power of designer microbial consortia that consist of multiple populations with well-defined interactions. Consortia can accomplish tasks that are difficult or potentially impossible to achieve using monocultures. Despite their potential, the rules underlying microbial community maintenance and function (i.e. the task the consortium is engineered to carry out) are not well defined, though rapid progress is being made. This limited understanding is in part due to the greater challenges associated with increased complexity when dealing with multi-population interactions. Here, we review key features and design strategies that emerge from the analysis of both natural and engineered microbial communities. These strategies can provide new insights into natural consortia and expand the toolbox available to engineers working to develop novel synthetic consortia.
Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait–climate relationships that differ dramatically—27% of significant results change in sign and 71% disagree on sign, significance, or both—from traditional species-weighted methods. We find that ( i ) functional diversity generally declines with increasing latitude and elevation, ( ii ) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and ( iii ) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.
Ecological communities are complex adaptive systems that exhibit remarkable feedbacks between their biomass and trait dynamics. Trait-based aggregate models cope with this complexity by focusing on the temporal development of the community's aggregate properties such as its total biomass, mean trait and trait variance. They are based on particular assumptions about the shape of the underlying trait distribution, which is commonly assumed to be normal. However, ecologically important traits are usually restricted to a finite range, and empirical trait distributions are often skewed or multimodal. As a result, normal distribution-based aggregate models may fail to adequately represent the biomass and trait dynamics of natural communities. We resolve this mismatch by developing a new moment closure approach assuming the trait values to be beta-distributed. We show that the beta distribution captures important shape properties of both observed and simulated trait distributions, which cannot be captured by a Gaussian. We further demonstrate that a beta distribution-based moment closure can strongly enhance the reliability of trait-based aggregate models. We compare the biomass, mean trait and variance dynamics of a full trait distribution (FD) model to the ones of beta (BA) and normal (NA) distribution-based aggregate models, under different selection regimes. This way, we demonstrate under which general conditions (stabilizing, fluctuating or disruptive selection) different aggregate models are reliable tools. All three models predicted very similar biomass and trait dynamics under stabilizing selection yielding unimodal trait distributions with small standing trait variation. We also obtained an almost perfect match between the results of the FD and BA models under fluctuating selection, promoting skewed trait distributions and ongoing oscillations in the biomass and trait dynamics. In contrast, the NA model showed unrealistic trait dynamics and exhibited different alternative stable states, and thus a high sensitivity to initial conditions under fluctuating selection. Under disruptive selection, both aggregate models failed to reproduce the results of the FD model with the mean trait values remaining within their ecologically feasible ranges in the BA model but not in the NA model. Overall, a beta distribution-based moment closure strongly improved the realism of trait-based aggregate models.
Ecosystems vary widely in their responses to biodiversity change, with some losing function dramatically while others are highly resilient. However, generalizations about how species- and community-level properties determine these divergent ecosystem responses have been elusive because potential sources of variation (e.g., trophic structure, compensation, functional trait diversity) are rarely evaluated in conjunction. Ecosystem vulnerability, or the likely change in ecosystem function following biodiversity change, is influenced by two types of species traits: response traits that determine species' individual sensitivities to environmental change, and effect traits that determine a species' contribution to ecosystem function. Here we extend the response-effect trait framework to quantify ecosystem vulnerability and show how trophic structure, within-trait variance, and among-trait covariance affect ecosystem vulnerability by linking extinction order and functional compensation. Using in silico trait-based simulations we found that ecosystem vulnerability increased when response and effect traits positively covaried, but this increase was attenuated by decreasing trait variance. Contrary to expectations, in these communities, both functional diversity and trophic structure increased ecosystem vulnerability. In contrast, ecosystem functions were resilient when response and effect traits covaried negatively, and variance had a positive effect on resiliency. Our results suggest that although biodiversity loss is often associated with decreases in ecosystem functions, such effects are conditional on trophic structure, and the variation within and covariation among response and effect traits. Taken together, these three factors can predict when ecosystems are poised to lose or gain function with ongoing biodiversity change. This article is protected by copyright. All rights reserved.
We refer to a theoretical trait space (TTS) as an n-dimensional hypervolume (“hypercube”) characterizing the range of values and covariations among multiple functional traits, in the absence of explicit filtering mechanisms. We previously constructed a 32-dimensional TTS for North American trees by fitting the Allometrically Constrained Growth and Carbon Allocation (ACGCA) model to USFS Forest Inventory and Analysis (FIA) data. Here, we sampled traits from this TTS, representing different individual “trees,” and subjected these trees to a series of gap dynamics simulations resulting in different annual light levels to explore the impact of environmental filtering (light stress) on the trait space. Variation in light limitation led to non-random mortality and a refinement of the TTS. We investigated potential mechanisms underlying such filtering processes by exploring how traits and the environment relate to mortality rates at the tree, phenotype (a specific set of trait values), and stand (a specific gap scenario) levels. The average light level at the forest floor explained 42% of the stand-level mortality, while phenotype- and tree-level mortality were best explained by six functional traits, especially radiation-use efficiency, maximum tree height, and xylem conducting area to sapwood area ratio (γX). These six “mortality” traits and six traits related to the leaf and wood economics spectra were used to construct trait hypercubes represented by trees that died or that survived each gap scenario. For trees that survived, the volume of their refined trait space decreased linearly with increasing stand-level mortality (up to ~50% mortality); the location also shifted, as indicated by non-zero distances between the hypercube centroids of surviving trees compared to dead trees and the original TTS. Overall, the patterns were consistent with empirical studies of functional traits, in terms of which traits predict mortality and the direction of the relationships. This work, however, also identified potentially important functional traits that are not commonly measured in empirical studies, such as γX and senescence rates of relatively long-lived tissues. This article is protected by copyright. All rights reserved.
THE functioning and sustainability of ecosystems may depend on their
biological diversity1-8. Elton's9 hypothesis that
more diverse ecosystems are more stable has received much
attention1,3,6,7,10-14, but Darwin's proposal6,15
that more diverse plant communities are more productive, and the related
conjectures4,5,16,17 that they have lower nutrient losses and
more sustainable soils, are less well studied4-6,8,17,18.
Here we use a well-replicated field experiment, in which species
diversity was directly controlled, to show that ecosystem productivity
in 147 grassland plots increased significantly with plant biodiversity.
Moreover, the main limiting nutrient, soil mineral nitrogen, was
utilized more completely when there was a greater diversity of species,
leading to lower leaching loss of nitrogen from these ecosystems.
Similarly, in nearby native grassland, plant productivity and soil
nitrogen utilization increased with increasing plant species richness.
This supports the diversity-productivity and diversity-sustainability
hypotheses. Our results demonstrate that the loss of species threatens
ecosystem functioning and sustainability.
Standardised procedures have been used to measure 67 traits in 43 common plants of the British flora. This paper provides an interpretation of the most consistent patterns in the resulting matrix by means of correlation, ordination and classification analyses. Only a weak coupling was observed between attributes of the regenerative and established phases of the life history. However, within each phase, attributes were strongly aggregated into sets and a high proportion of the variation between species coincided with a single axis. Attributes of the established phase displayed remarkably consistent trends, with a strong 'Axis 1' being identified by three different multivariate methods. There was a marked correlation between foliar concentrations of N, P, K, Ca and Mg, high concentrations of which coincided with the capacity for rapid growth in productive conditions and an inability to sustain yield under limiting supplies of nutrients. A diverse array of other traits, less immediately involving mineral nutrients, were also entrained in Axis 1; these included life history, root and shoot foraging, the morphology, longevity, tensile strength and palatability of leaves, and the decomposition rate of leaf litter. This pattern occurred in both monocotyledons and dicotyledons and appeared to reflect a tradeoff between attributes conferring an ability for high rates of resource acquisition in productive habitats and those responsible for retention of resource capital in unproductive conditions. The second axis of variation evident in the established phase was related to phylogeny and distinguished between monocotyledons and dicotyledons on the basis of a diverse set of traits including genome size, cell size, root and shoot foraging characteristics and vascular tissues. A third axis was detected in which ephemerals and perennials were separated by differences in attributes such as breeding system, leaf decomposition rate and a set of traits reflecting the small stature of many short-lived plants. In the regenerative phase, the leading axis was clearly related to the widely recognised tradeoff between seed size and seed number and was consistent with current understanding of seed banks, and with modern theories explaining species coexistence in terms of complementary responses to temporal and spatial variation in vegetation gap dynamics. The data provide strong evidence of functional integration between evolutionary specialisations in root and shoot and support Donald's unified theory of competitive ability. The data are not consistent with theories of functional types based upon evolutionary tradeoffs in allocation between root and shoot. We suggest that the evidence assembled here and elsewhere in the current literature points to the existence of primary functional types, including those recognised by Ramenskii and Grime. These functional types can be reconciled with the individuality of plant ecologies in the field and provide an effective basis For interpretation and prediction at various scales from the plant community to regional floras. There are particular opportunities for prediction of successional trajectories, the role of herbivores in vegetation succession and the response of vegetation to eutrophication and extreme climatic events. It is also suggested that aspects of this investigation may provide a Darwinian underpinning for Odum's theory of ecosystem maturation.
Biological diversity appears to enhance the resilience of desirable ecosystem states, which is required to secure the production of essential ecosystem services. The diversity of responses to environmental change among species contributing to the same ecosystem function, which we call response diversity, is critical to resilience. Response diversity is particularly important for ecosystem renewal and reorganization following change. Here we present examples of response diversity from both terrestrial and aquatic ecosystems and across temporal and spatial scales. Response diversity provides adaptive capacity in a world of complex systems, uncertainty, and human-dominated environments. We should pay special attention to response diversity when planning ecosystem management and restoration, since it may contribute considerably to the resilience of desired ecosystem states against disturbance, mismanagement, and degradation.
The potential consequences of biodiversity loss for ecosystem functioning and services at local scales have received considerable attention during the last decade, but little is known about how biodiversity affects ecosystem processes and stability at larger spatial scales. We propose that biodiversity provides spatial insurance for ecosystem functioning by virtue of spatial exchanges among local systems in heterogeneous landscapes. We explore this hypothesis by using a simple theoretical metacommunity model with explicit local consumer-resource dynamics and dispersal among systems. Our model shows that variation in dispersal rate affects the temporal mean and variability of ecosystem productivity strongly and nonmonotonically through two mechanisms: spatial averaging by the intermediate-type species that tends to dominate the landscape at high dispersal rates, and functional compensations between species that are made possible by the maintenance of species diversity. The spatial insurance effects of species diversity are highest at the intermediate dispersal rates that maximize local diversity. These results have profound implications for conservation and management. Knowledge of spatial processes across ecosystems is critical to predict the effects of landscape changes on both biodiversity and ecosystem functioning and services.
While evolutionary ecologists emphasize different ways in which plants can evolutionarily respond to herbivory, such as resistance
or tolerance, community ecology has lagged in its understanding of how these different plant traits can influence interactions,
abundance, composition, and diversity within more complex food webs. In this paper, we present a series of models comparing
community level outcomes when plants either resist or tolerate herbivory. We show that resistance and tolerance can lead to
very different outcomes. A particularly important result is that resistant species should often coexist locally with other,
less resistant competitors, whereas tolerant species should not be able to coexist locally with less tolerant competitors,
although priority effects allow them to coexist regionally. We also use these models to suggest some insights into the evolution
of these traits within more complex communities. We emphasize how understanding the differential effects of plant tolerance
and resistance in food webs provides greater appreciation of a variety of empirical patterns that heretofore have appeared
enigmatic.
Investigations of the role of competition, predation and abiotic stress in shaping natural communities were a staple for previous generations of ecologists and are still popular themes. However, more recent experimental research has uncovered the largely unanticipated, yet striking influence of facilitation (i.e. positive species interactions) on the organization of terrestrial and aquatic communities. Modern ecological concepts and theories were well established a decade before the current renaissance of interest in facilitation began, and thus do not consider the importance of a wide variety of facilitative interactions. It is time to bring ecological theory up to date by including facilitation. This process will not be painless because it will fundamentally change many basic predictions and will challenge some of our most cherished paradigms. But, ultimately, revising ecological theory will lead to a more accurate and inclusive understanding of natural communities.
ONE of the ecological tenets justifying conservation of biodiversity is that diversity begets stability. Impacts of biodiversity on population dynamics and ecosystem functioning have long been debated1-7, however, with many theoretical explorations2-6,8-11 but few field studies12-15. Here we describe a long-term study of grasslands16,17 which shows that primary productivity in more diverse plant communities is more resistant to, and recovers more fully from, a major drought. The curvilinear relationship we observe suggests that each additional species lost from our grasslands had a progressively greater impact on drought resistance. Our results support the diversity-stability hypothesis5,6,18,19, but not the alternative hypothesis that most species are functionally redundant19-21. This study implies that the preservation of biodiversity is essential for the maintenance of stable productivity in ecosystems.
Variation in plant functional traits results from evolutionary and environmental drivers that operate at a variety of different scales, which makes it a challenge to differentiate among them. In this article we describe patterns of functional trait variation and trait correlations within and among habitats in relation to several environmental and trade-off axes. We then ask whether such patterns reflect natural selection and can be considered plant strategies. In so doing we highlight evidence that demonstrates that
(1) patterns of trait variation across resource and environmental gradients (light, water, nutrients, and temperature) probably reflect adaptation, (2) plant trait variation typically involves multiple-correlated traits that arise because of inevitable trade-offs among traits and across levels of whole-plant integration and that must be understood from a wholeplant perspective, and
(3) such adaptation may be globally generalizable for like conditions; i.e., the set of traits (collections of traits in syndromes) of taxa can be considered as “plant strategies.”
Ecosystem resistance to a single stressor relies on tolerant species that can compensate for sensitive competitors and maintain ecosystem processes, such as primary production. We hypothesize that resistance to additional stressors depends increasingly on species tolerances being positively correlated (i.e. positive species co-tolerance). Initial exposure to a stressor combined with positive species co-tolerance should reduce the impacts of other stressors, which we term stress-induced community tolerance. In contrast, negative species co-tolerance is expected to result in additional stressors having pronounced additive or synergistic impacts on biologically impoverished functional groups, which we term stress-induced community sensitivity. Therefore, the sign and strength of the correlation between species sensitivities to multiple stressors must be considered when predicting the impacts of global change on ecosystem functioning as mediated by changes in biodiversity.
Why do species live where they live? What determines the abundance and diversity of species in a given area? What role do species play in the functioning of entire ecosystems? All of these questions share a single core conceptâthe ecological niche. Although the niche concept has fallen into disfavor among ecologists in recent years, Jonathan M. Chase and Mathew A. Leibold argue that the niche is an ideal tool with which to unify disparate research and theoretical approaches in contemporary ecology. Chase and Leibold define the niche as including both what an organism needs from its environment and how that organism's activities shape its environment. Drawing on the theory of consumer-resource interactions, as well as its graphical analysis, they develop a framework for understanding niches that is flexible enough to include a variety of small- and large-scale processes, from resource competition, predation, and stress to community structure, biodiversity, and ecosystem function. Chase and Leibold's synthetic approach will interest ecologists from a wide range of subdisciplines.
In seasonal environments, the main selection pressure on the timing of reproduction (the ultimate factor) is synchrony between offspring requirements and food availability. However, reproduction is initiated much earlier than the time of maximum food requirement of the offspring. Individuals should therefore start reproduction in response to cues (the proximate factors), available in the environment of reproductive decision making, which predict the later environment of selection. With increasing spring temperatures over the past decades, vegetation phenology has advanced, with a concomitant advancement in the reproduction of some species at higher trophic levels. However, a mismatch between food abundance and offspring needs may occur if changes in the environment of decision making do not match those in the environment of selection. Date of egg laying in a great tit (Parus major) population has not advanced over a 23-year period, but selection for early laying has intensified. We believe that this is the first documented case of an adaptive response being hampered because a changing abiotic factor affects the environment in which a reproductive decision is made differently from the environment in which selection occurs.
Different types of plants influence the structure and dynamics of the ecosystems they dominate. By identifying plant functional types, it may be possible to predict, monitor and manage impacts of environmental change.
The applicability of ecological principles, as they are discernible in pelagic systems, to the functioning of ecosystems generally, is re-examined: there are obvious similarities, most especially the base of photosynthetic plants, the array of consumers, the microbial returns and the intermediate trophic linkages. The reactions to environmental variability seem more conclusive in the pelagic but the observation makes no allowance for the differences in organismic temporal and spatial scaling: generation for generation, the plankton year is equivalent to the terrestrial interstadial. If the correct scaling factor is applied, the observable traits in the population and community ecology of the plankton may well provide appropriate models for the analogous high-order processes in terrestrial ecosystems but whose time scales are often much too extended relative to the life spans of ecologists to be verified. Ecosystem variability and resource fluctuation determine that biotic responses alternate between progressive expansion into the capacity of the resources and rapid contraction when the base is constrained. The deductions strongly support the themes of the 'new ecology' (Price et al. 1984) and oppose the retention of theories relating to steady states. The ability to determine the state ecosystem from the difference in its productive yield and the rate of its exploitative dissipation (the 'exergy flux' of Jorgensen 1992) is applied to suppositions about the impact of human activities on the providence of Planet Earth. World population is suggested to be closer to the thermodynamic supportive capacity than has been indicated previously. The mechanisms that promote high species diversity in the plankton are argued to be equally important on land. Patch diversity and separation, together with the stochastic frequencies and strength of structural setbacks (disturbances), are critical in both instances but there is great disparity in the spatial and temporal scaling, and in the contiguity of patches. The roles of disturbance frequency, the spectrum of patch ages, their interconnectedness and the transfer of propagules among patches are highlighted on the basis of planktonic biodiversities. The impact of planktonic-plant growth is considered in relation to the quality of water and, in particular, to its ability to constitute unacceptable and excessive biomass levels in lakes and rivers enriched with plant nutrients (chiefly phosphorus and nitrogen). The quantitative description of this eutrophication and the choice of methods available for its remediation are briefly reviewed. The steps necessary to secure effective nutrient-load reductions are not always the most practical compared to the application of physical mixing and biological control. Criteria for the successful application of these alternatives are rehearsed; the framework of a decision-support model is outlined. Special consideration is given to overcoming the problems caused by potentially-toxic cyanobacterial blooms and by the impacts of acid precipitation in base-poor catchments. Approaches towards striking sustainability in the management of the world's resources are identified. These call for greater management of demand, the application of low-energy, low-tech methods of waste-water recovery and a much more 'ecocentric' resolve to protect water quality for its own sake. The challenge to return all abstracted water to the hydrological cycle in at least as good or better quality requires us to care for the terrestrial environment too. This 'ecosystem approach' to water management is thus sympathetic to the properties of ecosystems generally. By placing these to the fore and seeking always to enhance them, good quality water and attractive habitat are no longer ruined by exploitation but, rather, are augmented by it. The techniques of managing ecosystems are most readily learned from the observation of systems dominated by aquatic microbes.
Functional complementarity occurs when ecosystem processes are maintained at constant levels despite stresses that induce shifts in the populations driving those processes. Understanding when such complementarity occurs depends on an integration of perspectives from population and ecosystem ecology. Here, we examine the extent to which functional complementarity is linked with compensatory dynamics among species that carry out a particular ecosystem function. Our approach combines analyses of long-term zooplankton data from a whole-lake acidification experiment with a theoretical treatment of species compensation. Results from the acidification of Little Rock Lake, WI indicated that the biomass of cladocerans, copepods, rotifers, and total zoo-plankton remained at high levels despite the loss of component species from each group. Compensatory increases by other taxa were responsible for this complementarity of function. Theoretical considerations indicated that the degree of compensation occurring among species in response to environmental change increased in response to two different factors: the functional similarity of interacting species and the degree to which an environmental change acts nonuniformly on their interactions. Finally, we tested the extent to which compensation in unperturbed systems could predict functional complementarity. We analyzed a 7-year record from the reference basin of Little Rock Lake and found that substantial compensation occurred only in the natural dynamics of rotifers and cladocerans during some seasons. Complementarity in response to acidification was evident, however, among copepods and total zooplankton in addition to rotifers and cladocerans, and could not have been predicted solely on the basis of compensation prior to stress. Taken together, our analyses reveal how functional complementarity is linked to a variety of compensatory interactions among species responding to stress.
We model the evolution of anti-predator ability in a prey species whose predator has a saturating functional response. Increased anti-predator ability is assumed to require decreased food intake. The anti-predator ability is specified by the value of a continuous trait, whose evolutionary dynamics are determined by the rate of change of fitness as a function of the trait value. This situation can produce a perpetual evolutionary increase in the anti-predator trait, with a concomitant decrease in foraging (or other fitness-enhancing activities); the end result of the process is often extinction of the prey species. This outcome is most likely if the predator population size is maintained by some alternative prey species. Conditions that can promote or counteract this tendency toward self-extinction are discussed.
The ecological consequences of biodiversity loss have aroused considerable interest and controversy during the past decade.
Major advances have been made in describing the relationship between species diversity and ecosystem processes, in identifying
functionally important species, and in revealing underlying mechanisms. There is, however, uncertainty as to how results obtained
in recent experiments scale up to landscape and regional levels and generalize across ecosystem types and processes. Larger
numbers of species are probably needed to reduce temporal variability in ecosystem processes in changing environments. A major
future challenge is to determine how biodiversity dynamics, ecosystem processes, and abiotic factors interact.
One of the more intriguing and challenging developments in ecology and in limnology and oceanography is the expansion of the temporal and spatial scales that are being addressed by current work. Researchers are realizing that individual communities and ecosystems are not isolated from each other but rather that they are connected by exchanges of individuals (through dispersal) and materials (through spatial fluxes). From a conceptual perspective, there is a need to develop theories and hypotheses about the roles of these exchanges on different community and ecosystem attributes. Here we focus on the concept of metacommunities, to address how plankton communities are structured and how this may generate patterns of variation in planktonic ecosystems. Our premise is that planktonic systems can be understood in the framework of metacommunities and that the regulation of these metacommunities alter how they work as ''complex adaptive systems.'' We hypothesize that connectivity through dispersal of local communities that are embedded in aquatic metacommunities show a range of dynamic behaviors related to their capacity to respond adaptively to environmental change. Much work in limnetic ecosystems has shown the rich array of community and ecosystem processes that regulate ponds, lakes, and larger bodies of water such as large lakes, seas, and oceans. This work has shown that limnetic eco- systems as a whole respond strongly to joint effects of abi- otic resources (bottom-up effects) and of factors affecting
A basic principle of natural selection on correlated characters is expressed as an adaptive topography for the vector of mean phenotypes in a population. Under some simple conditions on the pattern of phenotypic and genetic covariation within populations, selection only on body size, certain types of multivariate selection, and random genetic drift in a stochastic phylogeny are each expected to produce allometric evolution, i.e., straight lines or linear regressions on logarithmic coordinates. The orientation of these lines is determined by genetic parameters of the populations. Using this theory, phylogenetic or comparative information can be combined with experimental data on population genetic parameters to test hypotheses about past selective forces. Data from selection experiments on brain and body weights in mice support the conclusions that [1] the short-term differentiation of brain and body sizes in very closely related mammalian forms resulted either from directional selection mostly on body size with changes in brain sizes largely a genetically correlated response, or from random genetic drift; [2] during the long-term allometric diversification within most mammalian orders there has been more net directional selection on brain sizes than on body sizes. It is suggested that encephalization in primates decreased the genetic correlation between brain size and body size within populations, which facilitated further encephalization in the human lineage by avoiding antagonistic selection on brain and body sizes. The evolution of brain:body ontogeny is briefly discussed.
Biodiversity plays a vital role for ecosystem functioning in a
changing environment. Yet theoretical approaches that incorporate
diversity into classical ecosystem theory do not provide a general
dynamic theory based on mechanistic principles. In this paper, we
suggest that approaches developed for quantitative genetics can be
extended to ecosystem functioning by modeling the means and variances
of phenotypes within a group of species. We present a framework that
suggests that phenotypic variance within functional groups is linearly
related to their ability to respond to environmental changes. As a
result, the long-term productivity for a group of species with high
phenotypic variance may be higher than for the best single species,
even though high phenotypic variance decreases productivity in the
short term, because suboptimal species are present. In addition, we
find that in the case of accelerating environmental change, species
succession in a changing environment may become discontinuous. Our work
suggests that this phenomenon is related to diversity as well as to the
environmental disturbance regime, both of which are affected by
anthropogenic activities. By introducing new techniques for modeling
the aggregate behavior of groups of species, the present approach may
provide a new avenue for ecosystem analysis.
One of the tenets of the conservation movement has been that areas containing many species--those of high biodiversity--are
particularly worth saving, since ecosystems of high diversity show improved ecosystem function. As Grime explains in his Perspective,
this tenet is being replaced by another view, which is bolstered by three reports in this week's issue (pages
1296,
1300, and
1302). These studies all show that it is actually the specific features of the species in an ecosystem that determine its function--not
their number.
Photosynthetic responses to acclimation temperature were investigated in seedlings of eight Australian rainforest tree species. Australian rainforests extend over 33° of latitude, providing an opportunity to compare temperature responses of temperate and tropical species. • Net photosynthesis was measured in leaves developed under a constant (22°C : 14°C) or fluctuating (17°C : 9°C−27°C : 19°C) day/night temperature regime. These leaves were then subjected to a series of constant temperature regimes and net photosynthesis was measured 14 d after acclimation to each new regime. • Acclimation potential was not affected by the contrasting temperature regimes. The temperate species showed at least 80% of maximum net photosynthesis over a larger span of acclimation temperature than the tropical species. • The lack of an effect of the contrasting temperature regimes on acclimation potential may reflect either that adjustments were unnecessary for temperate species, which already have broad photosynthetic responses to temperature, and tropical species were incapable of adjustments, or that in general species respond to the mean temperature regime and not to the amount of fluctuation in the regime. The higher acclimation potential shown by the temperate species is consistent with the larger seasonal and day-to-day variation in temperature of the temperate climate compared with the tropical climate.
Summary • We tested the hypothesis that biological trait-based plant functional groups pro- vide sufficient differentiation of species to enable generalization about a variety of plant ecophysiological traits or responses to nitrogen (N). • Seedlings of 34 North American grassland and savanna species, representing 5 functional groups, were grown in a glasshouse in an infertile soil with or without N fertilization. • Forbs, C 3 and C 4 grasses, on average, had similar relative growth rates (RGR), followed in declining order by legumes and oaks, but RGR varied greatly among species within functional groups. All measured attributes differed significantly among functional groups, of these, only RGR and photosynthesis differed among functional groups in response to N. All groups, except the legumes, had significantly greater photosynthetic and respiration rates at elevated N supply. Principal components analyses and cluster analyses yielded groupings that corresponded only moderately well to the biologically based a priori functional groupings. • Variation in RGR among species and treatments was positively related to net CO 2 exchange (photosynthesis and respiration) and net assimilation rate, but unrelated to leaf area ratio. Photosynthetic and respiration rates were related to tissue %N among treatments and species. Our data indicate that RGR and related traits differ among the functional groups in significant ways, but in a complex pattern that does not yield simple generalizations about relative performance, controls on RGR, or response to resource supply rate.
Ecosystem resistance to a single stressor relies on tolerant species that can compensate for sensitive competitors and maintain ecosystem processes, such as primary production. We hypothesize that resistance to additional stressors depends increasingly on species tolerances being positively correlated (i.e. positive species co-tolerance). Initial exposure to a stressor combined with positive species co-tolerance should reduce the impacts of other stressors, which we term stress-induced community tolerance. In contrast, negative species co-tolerance is expected to result in additional stressors having pronounced additive or synergistic impacts on biologically impoverished functional groups, which we term stress-induced community sensitivity. Therefore, the sign and strength of the correlation between species sensitivities to multiple stressors must be considered when predicting the impacts of global change on ecosystem functioning as mediated by changes in biodiversity.
Complementarity and sampling effects may both contribute to increased invasion resistance at higher diversity. We measured plant invader biomass across a long-term experimental plant diversity gradient. Invader species’ biomass was inhibited in more diverse plots, largely because of the presence of strongly competitive C4 bunchgrasses, consistent with a sampling effect. Invader biomass was negatively correlated with resident root biomass, and positively correlated with soil nitrate concentrations, suggesting that competition for nitrogen limited invader success. Resident root biomass increased and soil nitrate concentrations decreased with the presence of C4 grasses and also across the diversity gradient, suggesting that diverse plots are more competitive because of the presence of C4 grasses. In addition to this evidence for a sampling effect, we also found evidence for a complementarity effect. Specifically, the percentage of plots that had lower invader biomass than did the best resident monoculture (i.e. that had invader ‘underyielding’) increased across the species richness gradient. This pattern cannot be explained by a sampling effect and is a unique signature of complementarity effects. Our results demonstrate the importance of multiple mechanisms by which diversity can increase invasion resistance.
The present paper is an attempt to provide a set of models which will be more useful in the analysis of macro evolutionary events than the classical models of population genetics. This is accomplished by placing increased emphasis on phenotypic parameters. While it is not possible to be completely successful in describing evolution in purely phenotypic terms, it seems that in many circumstances appropriate for natural populations this can be done. In the first section, Simpson's concept of adaptive zones is clarified by the construction of an adaptive topography for phenotypes, similar to Wright's adaptive topography for gene frequencies. This shows that for most phenotypic characters under natural selection, the evolution of the average phenotype in a population is always toward an adaptive zone of high mean fitness (W) in the phenotype space. Frequency dependent selection may cause the average phenotype to evolve away from its adaptive zone, decreasing the mean fitness of individuals in the population; different types of frequency dependent selection are classified as to whether or not they lead to such maladaptive evolution. A simple formula for estimating the minimum selective mortality per generation necessary to explain observed rates of phenotypic evolution is derived (assuming that genetic drift was not involved). The minimum mortality rates needed to explain observed rates of evolution in tooth characters of Tertiary mammals are very small, typically about one selective death per million individuals per generation. This leads to consideration of the hypothesis that these changes were caused by random genetic drift. Using statistical tests, it is found that the observed evolution of these mammalian tooth characters could have occurred by random genetic drift in rather large populations, with effective sizes in the tens or hundreds of thousands. Such statistical tests would be most interesting in cases where the adaptive significance of an evolutionary event is uncertain. Other hypotheses are also examined, including the existence of a selective threshold between two adaptive zones which might have been crossed by random genetic drift. The models indicate that if stabilizing selection is weak and an adaptive threshold is not very far away, random genetic drift between adaptive zones may be an important mechanism of evolution in populations of effective size in the hundreds or thousands. These results support the contention that random genetic drift may play a significant role in phenotypic evolution.
The dominant protocol to study the effects of plant diversity on ecosystem functioning has involved synthetically assembled communities, in which the experimental design determines species composition. By contrast, the composition of naturally assembled communities is determined by environmental filters, species recruitment and dispersal, and other assembly processes. Consequently, natural communities and ecosystems can differ from synthetic systems in their reaction to changes in diversity. Removal experiments, in which the diversity of naturally assembled communities is manipulated by removing various components, complement synthetic-assemblage experiments in exploring the relationship between diversity and ecosystem functioning. Results of recent removal experiments suggest that they are more useful for understanding the ecosystem effects of local, nonrandom extinctions, changes in the natural abundance of species, and complex interspecific interactions. This makes removal experiments a promising avenue for progress in ecological theory and an important source of information for those involved in making land-use and conservation decisions.
1) The concept of plant functional type proposes that species can be grouped according to common responses to the environment and.or common effects on ecosystem processes. However, the knowledge of relationships between traits associated with the response of plants to environmental factors such as resources and disturbances( response traits), and traits that determine effects of plants on ecosystem function(effect traits), such as biogeochemical cycling or propensity to disturbance, remains rudimentary.
2) We present a framework using concepts and results from community ecology, ecosystem ecology and evolutionary biology to provide this linkage. Ecosystem functioning is the end result of the operation of multiple environmental filters in a heirarchy of scales which, by selecting individuals with appropriate responses, result in assemblages with varying trait composition. Functional linkages and trade-offs among traits, each of which relates to one or several processes, determine whether or not filtering by different factors gives a match, and whether ecosystem effects can easily be deduced from knowledge of the filters.
3) To illustrate this framework we analyse a set of key environmental factors and ecosystem processes. While traits associated with response to nutrient gradients strongly overlapped with those determining net primary production, little direct overlap was found between response to fire and flammability
4) We hypothesise that these patterns reflect general trends. Responses to resource availability would be determined by traits that also involved in biogeochemical cycling because both these responses and effects are driven by the trade-off between acquisition and conservation. On the other hand, regeneration and demographic traits associated with with response to disturbance, which are known to have little connection with adult traits involved in plant ecophysiology, would be of little relevance to ecosystem processes.
5) This framework is likely to be broadly applicable, although caution must to exercised to use trait linkages and trade-offs appropriate to the scale, environmental conditions and evolutionary context. It may direct the selection of plant functional types for vegetation models at a range of scales, and help with the design of experimental studies of relationships between plant diversity and ecosystem properties.
A general model of competition between several species in a variable environment is presented and analyzed using a general method that unifies treatment of different specific models. This method yields broad conclusions that are independent of the details of a model. It is used here to show that mechanisms of coexistence and competitive exclusion are largely restricted to three broad categories. One of these categories includes classical mechanisms that do not depend on fluctuations over time. Another category includes mechanisms which may be referred to collectively as the storage effect. These mechanisms involve species-specific responses to environmental fluctuations, a relationship between fluctuations in competition and fluctuations in the environment, and an interaction between environment and competition. The final category depends on fluctuating competition and nonlinear responses to competition that differ between species. These general results are illustrated with analyses of several specific models, including a Lotka-Volterra model, a model of nonlinear resource consumption, and models of recruitment fluctuations for iteroparous organisms and for annual plants.
To account for changes in the distribution of species grouped together in an ecosystem compartment we introduce averaged physiological parameters and derive equations for their dynamics. These parameters may describe shifts from larger to smaller species or between species with high and low demand of some nutrient, for example. Specifically, in a model for the phytoplankton of Lake Constance, these effective variables describe the shift between diatomic and non-diatomic as well as between rapidly and slowly growing algae. With reasonable values for the remaining biological and physical parameters and a simple model for zooplankton grazing, the dynamics of the effective variables then reproduces the succession of algal species in Lake Constance, as observed and described by Sommer (1987, Progr. Phycol. Res., 5: 123-178).
Environmental factors regulate biodiversity through species sorting processes. Species distributions in communities affect ecosystem processes and environmental factors. These dynamics are determined by the properties (traits) of species in the community. The optimal temperatures for growth, the minimal amount of resource that sustains positive mass balance, and the amount of energy allocated to predator defenses are examples of such traits. Over time, the trait distributions in communities may change in response to environmental changes, which, in turn, changes the processes and consequently the structure of the system. The result of such processes is the focus of complex adaptive systems (CAS) theory. This paper gives an overview of how CAS theory can contribute to understanding the role of biodiversity on the ability of functional groups that make up the ecosystem to change their species compositions in response to changes in the environment. Any trait that requires investment of energy, mass, or time is subjected to a tradeoff for alternative use of this resource. Such interspecies tradeoff relationships can be used to make predictions about past environmental conditions, as well as the response of the properties of a group of species, e.g., total productivity and species distributions, to future changes in the environment. The trait-based framework presented here makes explicit predictions regarding the relation between the environment, trait distributions, and ecosystem processes. Trait variance, a measure of the width of the distribution of traits in the community, is proportional to the rate at which species within functional groups can replace each other in response to environmental changes. This adaptive capacity is crucial for the ecosystem's ability to maintain certain processes under times of change. Examples of empirical tradeoffs are given as well as how to formalize them to use in the CAS framework.
A method is developed that describes the effects on an arbitrary number of autosomal loci of selection on haploid and diploid stages, of nonrandom mating between haploid individuals, and of recombination. We provide exact recursions for the dynamics of allele frequencies and linkage disequilibria (nonrandom associations of alleles across loci). When selection is weak relative to recombination, our recursions provide simple approximations for the linkage disequilibria among arbitrary combinations of loci. We show how previous models of sex-independent natural selection on diploids, assortative mating between haploids, and sexual selection on haploids can be analyzed in this framework. Using our weak-selection approximations, we derive new results concerning the coevolution of male traits and female preferences under natural and sexual selection. In particular, we provide general expressions for the intensity of linkage-disequilibrium induced selection experienced by loci that contribute to female preferences for specific male traits. Our general results support the previous observation that these indirect selection forces are so weak that they are unlikely to dominate the evolution of preference-producing loci.
Sometimes predators tend to concentrate on common varieties of prey and overlook rare ones. Within prey species, this could result in the fitness of each variety being inversely related to its frequency in the population. Such frequency-dependent or 'apostatic' selection by predators hunting by sight could maintain polymorphism for colour pattern, and much of the supporting evidence for this idea has come from work on birds and artificial prey. These and other studies have shown that the strength of the observed selection is affected by prey density, palatability, coloration and conspicuousness. When the prey density is very high, selection becomes 'anti-apostatic': predators preferentially remove rare prey. There is still much to be learned about frequency-dependent selection by predators on artificial prey: work on natural polymorphic prey has hardly begun.
We develop a general population genetic framework for analyzing selection on many loci, and apply it to strong truncation and disruptive selection on an additive polygenic trait. We first present statistical methods for analyzing the infinitesimal model, in which offspring breeding values are normally distributed around the mean of the parents, with fixed variance. These show that the usual assumption of a Gaussian distribution of breeding values in the population gives remarkably accurate predictions for the mean and the variance, even when disruptive selection generates substantial deviations from normality. We then set out a general genetic analysis of selection and recombination. The population is represented by multilocus cumulants describing the distribution of haploid genotypes, and selection is described by the relation between mean fitness and these cumulants. We provide exact recursions in terms of generating functions for the effects of selection on non-central moments. The effects of recombination are simply calculated as a weighted sum over all the permutations produced by meiosis. Finally, the new cumulants that describe the next generation are computed from the non-central moments. Although this scheme is applied here in detail only to selection on an additive trait, it is quite general. For arbitrary epistasis and linkage, we describe a consistent infinitesimal limit in which the short-term selection response is dominated by infinitesimal allele frequency changes and linkage disequilibria. Numerical multilocus results show that the standard Gaussian approximation gives accurate predictions for the dynamics of the mean and genetic variance in this limit. Even with intense truncation selection, linkage disequilibria of order three and higher never cause much deviation from normality. Thus, the empirical deviations frequently found between predicted and observed responses to artificial selection are not caused by linkage-disequilibrium-induced departures from normality. Disruptive selection can generate substantial four-way disequilibria, and hence kurtosis; but even then, the Gaussian assumption predicts the variance accurately. In contrast to the apparent simplicity of the infinitesimal limit, data suggest that changes in genetic variance after 10 or more generations of selection are likely to be dominated by allele frequency dynamics that depend on genetic details.
Ecosystem processes are thought to depend on both the number and identity of the species present in an ecosystem, but mathematical theory predicting this has been lacking. Here we present three simple models of interspecific competitive interactions in communities containing various numbers of randomly chosen species. All three models predict that, on average, productivity increases asymptotically with the original biodiversity of a community. The two models that address plant nutrient competition also predict that ecosystem nutrient retention increases with biodiversity and that the effects of biodiversity on productivity and nutrient retention increase with interspecific differences in resource requirements. All three models show that both species identity and biodiversity simultaneously influence ecosystem functioning, but their relative importance varies greatly among the models. This theory reinforces recent experimental results and shows that effects of biodiversity on ecosystem functioning are predicted by well-known ecological processes.