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Guia para análise de redes ecológicas
Abstract
Este guia foi feito para ajudar iniciantes na análise de redes ecológicas. Muitas destas dicas servem para qualquer tipo de rede, mas a maioria tem um viés para a Ecologia, especialmente para o estudo de redes bipartidas animal-planta. Esperamos ajudar também colegas mais experientes, criando um compêndio dos programas e métricas mais usados.
... (2) Strength, which is the relative frequency of interaction of a bee species with a plant species; it is represented as the number of interactions between a bee species and a plant species divided by the number of visits by all bee species to that same plant. Thus, specialist bees have lower interaction strength values (Vázquez et al., 2007;Dormann, 2011;Schleuning et al., 2011;Mello et al., 2016). (3) Closeness, which is based on the number of steps on the shortest path (in terms of interactions) that link a particular species to all other species in the network; a low closeness value for a species means that it is distant from most other species in the network, indicating specialization in interactions (González et al., 2010). ...
Bee pollinators are key components of terrestrial ecosystems. Evidence is mounting that bees are globally in decline, and species with a higher degree of specialization are the most vulnerable to local extinction. However, ecological features that could explain bee specialization remain poorly tested, especially in tropical species. Here, we aim to determine the most specialized bee species and their associated ecological traits in tropical plant–bee interaction networks, answering three questions: (1) Which bees in the interaction networks are specialists? (2) Is body size related to their role as specialists in interaction networks? (3) Are there phylogenetic relationships between the bee species identified as specialists? We used fifteen quantitative plant–bee interaction networks from different Brazilian biomes covering 1,702 interactions (386 bee and 717 plant species). We used the normalized degree (standardized number of partners) as a metric to determine trophic specialization of bee species. Body size was estimated by measuring intertegular distance (ITD), i.e., the distance between the bases of the wings on the thorax. Evolutionary distinctiveness (ED) was used to quantify species uniqueness, i.e., the singularity of species in the phylogenetic tree. Relationships between dietary specialism, ITD and ED were assessed using generalized linear models. We detected 34 specialist bee species (9% of total species), distributed in 13 genera, and four families. ITD and ED were important variables explaining the specialization of tropical bee species. Specialists were larger and less phylogenetically distinct than expected by chance. Based on a large data set covering some of the main tropical biomes, our results suggest that loss of specialist bees from Brazilian plant–bee networks could have deleterious consequences for native plant species preferentially pollinated by large-bodied bees. Moreover, by affecting more evolutionarily distinct species, i.e., those with fewer extant relatives, the loss of specialist bees will likely affect few clades but can result on considerable loss of evolutionary history and phylogenetic diversity in the Brazilian bee communities. The results are important for decision-making concerning conservation measures for these species and may also encourage the development of sustainable management techniques for bees.
... For the network analysis, the degree of connection (number of recorded interactions between two species), centrality (the relative importance of species throughout the network) and modularity (the most connected bird and plant groups), were recorded. Network metrics were calculated in the Pajek 5.07 software aiming to identify the keystone species in each Brazilian biome (Mello et al., 2015;Mello et al., 2016). ...
Vegetation stability, resilience and regeneration can be achieved by various ecological processes, the most important of which is seed dispersion. Among animal groups, birds have the largest number of frugivorous species in the Neotropics. The aim of this study was to conduct a bibliometric analysis to detect general patterns and discover knowledge gaps in order to identify future directions for research into bird frugivory in Brazil. A gap analysis was carried out by obtaining 77 articles published online and evaluating their data in different ways. The results revealed that research on bird frugivory in Brazil was published in 33 scientific journals and financed by 18 national and international funding agencies. The number of publications increased over time, with the majority of them reporting research carried out in biomes of Central-West and South regions of Brazil. The most important bird species in frugivorous interactions in the most studied biomes were identified, including some non-native species. Our results corroborate several other studies, which together demonstrate a lack research on frugivorous interactions in the North and Northeast of Brazil, where there are very important biomes for conservation, such as the Amazon and Caatinga, for which knowledge of seed dispersal processes is needed.
O sucesso da polinização biótica depende da sincronização dos períodos de floração e da atividade dos polinizadores. O objetivo desta revisão foi compilar e analisar publicações abordando os principais efeitos da dinâmica temporal nas interações entre plantas e polinizadores em diferentes escalas, incluindo variações diárias, mensais, entre estações e entre anos. Fatores como período, intensidade e tempo de floração influenciam as interações planta-polinizadores e podem constituir estratégias para otimizar a atratividade e/ou diminuir a concorrência por polinizadores e, consequentemente, aumentar o sucesso reprodutivo. Estudos sobre polinizadores, principalmente insetos, concentram-se na sazonalidade ao longo do ano, principalmente apresentando variações e maior atividade de polinizadores na estação chuvosa. Tais variações podem ocorrer de acordo com as características dos ciclos biológicos das espécies, bem como em resposta à disponibilidade de recursos e variáveis climáticas. Importantes propriedades estruturais das redes de interações plantas-polinizadores, tais como aninhamento e conectância, permanecem constantes ao longo dos anos. Apesar disso, mudanças na composição e riqueza de espécies de plantas e polinizadores entre os anos alteram o número e a configuração das interações entre eles. Este fato sugere que a estrutura das redes de interação e a funcionalidade do sistema de polinização podem ser mantidas ao longo do tempo independente da composição das espécies e do arranjo entre elas. Estudos futuros devem investigar as causas das variações temporais nas interações entre plantas e polinizadores, principalmente as que podem estar relacionadas a alterações antrópicas, a fim de apontar ações que minimizem o impacto humano. INTERACTIONS BETWEEN PLANTS AND POLLINATORS IN A TEMPORAL PERSPECTIVE. The success of biotic pollination depends on the synchronization of flowering periods and activity of the pollinators. This review aimed to compile and analyze publications addressing the main effects of temporal dynamics on plant-pollinator interactions at different scales. Factors such as period, intensity, and flowering timing influence plant-pollinator interactions. These may constitute strategies to optimize attractiveness and/or decrease of the competition for pollinators, consequently enhancing reproductive success. Studies on pollinators, mostly insects, focus on the seasonality throughout the year, mainly showing variations and increased activity of pollinators in the rainy season. Such variations can occur according to the characteristics of the biological cycles of the species, as well as in response to the availability of resources and climatic variables. Important structural properties of the plant-pollinator networks such as nestedness and conectance remain constant over the years. Despite this changes in the composition and richness of pollinator and plant species occur between years and alter the number and configuration of the links between them. This suggests that the structure of the pollination networks may be independent of species composition and the arrangement between them and the functionality of the pollination system can be maintained over time. Future research should investigate the causes of temporal variations in interactions between plants and pollinators. Especially those related to anthropic alterations aiming identify actions that can minimize human impact.
In plant–animal interactions, species are commonly labeled as either mutualists or antagonists, based on the most common, most studied, or most easily observed outcome. Nevertheless, evidence from simple systems comprising 2–4 species suggests that those labels are an oversimplification: individual species often function in both roles, either simultaneously or at different places or times. We include both mutualistic and antagonistic interactions between mammals and seeds in a multilayer network, to explore for the first time the community-level consequences of the dual roles played by some species. We tested whether negative and positive interactions within a plant-frugivore network are separated into different modules, or whether they overlap due to the presence of frugivores that both kill and disperse seeds. The frugivorous diets of nonvolant small mammals were studied at one dry tropical forest site in southeastern Brazil by analyzing fecal samples from individuals captured in live traps. Seed viability was assessed with a tetrazolium test to determine the outcome of those interactions, as estimated by whether or not seeds survived gut passage. Interactions were analyzed as a weighted multilayer network, subdivided into one potentially mutualistic (live seeds deposited) and one antagonistic (dead seeds deposited) layer. The two layers had similar structure with high overlap between them. Some mammal species exhibited highly central, dual roles, acting both as antagonists and mutualists, in many cases of the same plant species. Dispersal service by most of these small mammals is accompanied by seed destruction, suggesting that the selective pressures exerted by those animals on the plants is much more complex than often assumed. Our results demonstrate that the complexity of plant–frugivore networks cannot be fully understood without proper incorporating measures of seed fate following gut passage. This article is protected by copyright. All rights reserved.
Hosts and parasites interact with each other in a variety of ways, and this diversity of interactions is reflected in the networks they form. To test for differences in interaction patterns of ecto- and endoparasites we analysed subnetworks formed by each kind of parasites and their host fish species in fish–parasite networks for 22 localities. We assessed the proportion of parasite species per host species, the relationship between parasite fauna composition and host taxonomy, connectance, nestedness and modularity of each subnetwork (
n
= 44). Furthermore, we evaluated the similarity in host species composition among modules in ecto- and endoparasite subnetworks. We found several differences between subnetworks of fish ecto- and endoparasites. The association with a higher number of host species observed among endoparasites resulted in higher connectance and nestedness, and lower values of modularity in their subnetworks than in those of ectoparasites. Taxonomically related host species tended to share ecto- or endoparasites with the same interaction intensity, but the species composition of hosts tended to differ between modules formed by ecto- and endoparasites. Our results suggest that different evolutionary and ecological processes are responsible for organizing the networks formed by ecto- and endoparasites and fish.
Ecologists are familiar with two data structures commonly used to represent landscapes. Vector-based maps delineate land cover types as polygons, while raster lattices represent the landscape as a grid. Here we adopt a third lattice data structure, the graph. A graph represents a landscape as a set of nodes (e.g., habitat patches) connected to some degree by edges that join pairs of nodes functionally (e.g., via dispersal). Graph theory is well developed in other fields, including geography (transportation networks, routing applications, siting problems) and computer science (circuitry and network optimization). We present an overview of basic elements of graph theory as it might be applied to issues of connectivity in heterogeneous landscapes, focusing especially on applications of metapopulation theory in conservation biology. We develop a general set of analyses using a hypothetical landscape mosaic of habitat patches in a nonhabitat matrix. Our results suggest that a simple graph construct, the minimum spanning tree, can serve as a powerful guide to decisions about the relative importance of individual patches to overall landscape connectivity. We then apply this approach to an actual conservation scenario involving the threatened Mexican Spotted Owl (Strix occidentalis lucida). Simulations with an incidence-function metapopulation model suggest that population persistence can be maintained despite substantial losses of habitat area, so long as the minimum spanning tree is protected. We believe that graph theory has considerable promise for applications concerned with connectivity and ecological flows in general. Because the theory is already well developed in other disciplines, it might be brought to bear immediately on pressing ecological applications in conservation biology and landscape ecology.
Most methods proposed to uncover communities in complex networks rely on combinatorial graph properties. Usually an edge-counting quality function, such as modularity, is optimized over all partitions of the graph compared against a null random graph model. Here we introduce a systematic dynamical framework to design and analyze a wide variety of quality functions for community detection. The quality of a partition is measured by its Markov Stability, a time-parametrized function defined in terms of the statistical properties of a Markov process taking place on the graph. The Markov process provides a dynamical sweeping across all scales in the graph, and the time scale is an intrinsic parameter that uncovers communities at different resolutions. This dynamic-based community detection leads to a compound optimization, which favours communities of comparable centrality (as defined by the stationary distribution), and provides a unifying framework for spectral algorithms, as well as different heuristics for community detection, including versions of modularity and Potts model. Our dynamic framework creates a systematic link between different stochastic dynamics and their corresponding notions of optimal communities under distinct (node and edge) centralities. We show that the Markov Stability can be computed efficiently to find multi-scale community structure in large networks.
Community-level network studies suggest that seed dispersal networks may share some universal properties with other complex systems. However, most of the datasets used so far in those studies have been strongly biased towards temperate birds, including not only dispersers, but also seed predators. Recent evidence from multi-taxon networks suggests that seed dispersal networks are not all alike and may be more complex than previously thought. Here, we used network theory to evaluate seed dispersal in a strongly impacted Atlantic Forest fragment in northeastern Brazil, where bats and birds are the only extant dispersers. We hypothesized that the seed dispersal network should be more modular then nested, and that the dispersers should segregate their services according to dispersal syndromes. Furthermore, we predicted that bat and bird species that are more specialized in frugivory would be more important for maintaining the network structure. The mixed network contained 56 plant species, 12 bat species, and eight bird species, and its structure was more modular (M = 0.58) then nested (NODF = 0.21) compared with another multi-taxon network and 21 single-taxon networks (with either bats or birds). All dispersed fruits had seeds smaller than 9 mm. Bats dispersed mainly green fruits, whereas birds dispersed fruits of various colors. The network contained eight modules: five with birds only, two with bats only, and one mixed. Most dispersers were peripheral, and only specialized frugivores acted as hubs or connectors. Our results strongly support recent studies, suggesting that seed dispersal networks are complex mosaics, where different taxa form separate modules with different properties, which in turn play complementary roles in the maintenance of the associated ecosystem functions and services.
The multitrophic level approach to ecology addresses the complexity of food webs much more realistically than the traditional focus on simple systems and interactions. Only in the last few decades have ecologists become interested in the nature of more complex systems including tritrophic interactions between plants, herbivores and natural enemies. Plants may directly influence the behaviour of their herbivores' natural enemies, ecological interactions between two species are often indirectly mediated by a third species, landscape structure directly affects local tritrophic interactions and below-ground food webs are vital to above-ground organisms. The relative importance of top-down effects (control by predators) and bottom-up effects (control by resources) must also be determined. These interactions are explored in this exciting volume by expert researchers from a variety of ecological fields. This book provides a much-needed synthesis of multitrophic level interactions and serves as a guide for future research for ecologists of all descriptions.
Networks provide a powerful approach to address myriad phenomena across
ecology. Ecological systems are inherently 'multilayered'. For instance,
species interact with one another in different ways and those interactions vary
spatiotemporally. However, ecological networks are typically studied as
ordinary (i.e., monolayer) networks. 'Multilayer networks' are currently at the
forefront of network science, but ecological multilayer network studies have
been sporadic and have not taken advantage of rapidly developing theory. Here
we present the latest concepts and tools of multilayer network theory and
discuss their application to ecology. This novel framework for the study of
ecological multilayer networks encourages ecologists to move beyond monolayer
network studies and facilitates ways for doing so. It thereby paves the way for
novel, exciting research directions in network ecology.
One of the unresolved issues in the ecology of parasites is the relationship between host specificity and performance. Previous studies tested this relationship in different systems and obtained all possible outcomes. This led to the proposal of two hypotheses to explain conflicting results: the trade-off and resource breadth hypotheses, which are treated as mutually exclusive in the literature and were corroborated by different studies. In the present study, we used an extensive database on avian malaria from Brazil and combined analyses based on specificity indices and network theory, in order to test which of those hypotheses might best explain our model system. Contrary to our expectations, there was no correlation between specificity and prevalence, which contradicts both hypotheses. In addition, we detected a strong modular structure in our host-parasite network and found that its modules were not composed of geographically close, but of phylogenetically close, host species. Based on our results, we reached the conclusion that trade-off and resource breadth hypotheses are not really mutually exclusive. As a conceptual solution we propose "The Integrative Hypothesis of Parasite Specialization", a novel theoretical model that explains the contradictory results found in our study and reported to date in the literature.
Network approaches have become a popular tool for understanding ecological complexity in a changing world. Many network descriptors relate directly or indirectly to specialization, which is a central concept in ecology and measured in different ways. Unfortunately, quantification of specialization and network structure using field data can suffer from sampling effects. Previous studies evaluating such sampling effects either used field data where the true network structure is unknown, or they simulated sampling based on completely generalized interactions. Here, we used a quantitative niche model to generate bipartite networks representing a wide range of specialization and evaluated potential sampling biases for a large set of specialization and network metrics for different network sizes. We show that with sample sizes realistic for species-rich networks, all metrics are biased towards overestimating specialization (and underestimating generalization and niche overlap). Importantly, this sampling bias depends on the true degree of specialization and is strongest for generalized networks. As a result, null models simulating generalized interactions may misrepresent sampling bias. We show that other methods used for empirical data may be biased in the opposite direction and strongly overestimate sampling completeness. Some network metrics are barely related between small and large sub-samples of the same network and thus may often not be meaningful. Small samples also overestimate interspecific variation of specialization within generalized networks. While new approaches to deal with these challenges have to be developed, we also identify metrics that are relatively unbiased and fairly consistent across sampling intensities and we identify a provisional rule of thumb for the number of observations required for accurate estimates. Our quantitative niche model can help understand variation in network structure capturing both sampling effects and biological meaning. This is needed to connect network science to fundamental ecological theory and to give robust quantitative answers for applied ecological problems.This article is protected by copyright. All rights reserved.