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Are ecology and evolutionary biology “soft” sciences?
Abstract
Research in ecology and evolutionary biology (evo-eco) often tries to emulate the
“hard” sciences such as physics and chemistry, but to many of its practitioners
feels more like the “soft” sciences of psychology and sociology. I argue that this
schizophrenic attitude is the result of lack of appreciation of the full consequences
of the peculiarity of the evo-eco sciences as lying in between a-historical disciplines
such as physics and completely historical ones as like paleontology. Furthermore,
evo-eco researchers have gotten stuck on mathematically appealing but philosophically
simplistic concepts such as null hypotheses and p-values defi ned according to
the frequentist approach in statistics, with the consequence of having been unable to
fully embrace the complexity and subtlety of the problems with which ecologists and
evolutionary biologists deal with. I review and discuss some literature in ecology,
philosophy of science and psychology to show that a more critical methodological
attitude can be liberating for the evo-eco scientist and can lead to a more fecund
and enjoyable practice of ecology and evolutionary biology. With this aim, I briefl y
cover concepts such as the method of multiple hypotheses, Bayesian analysis, and
strong inference.
... This Bayesian approach allows for a more complete and nuanced appreciation of our results by 1) emphasizing estimated model parameters and resulting estimated dependent variables that are 2) expressed as likelihood distributions: the posterior distribution. Overall, we and a growing part of the research community deems Bayesian inference more appropriate because of its analogy with how ecological and evolutionary research is practiced (Pigliucci, 2002). ...
... The predictability of evolutionary change or ecological dynamics has historically been rather poor (Pigliucci, 2002). As such, predictability in population spread has gathered some interest but has been debated as well (Melbourne and Hastings, 2009;Giometto et al., 2014). ...
... Inspired by the seemingly high predictive power of many physics disciplines and molecular biology, ecologists seek to develop robust forecasting approaches from a fundamental understanding that may be applied to many fields of ecology (Melbourne and Hastings, 2009;Giometto et al., 2014). Our study is another reminder that this will not be easily attained as stochasticity and historicity have a big impact on ecological outcome relative to reliable drivers of these ecological dynamics (Pigliucci, 2002;Maris et al., 2018). We would like to stress that this incapability of making predictions does not make the field of ecology scientifically any less successful at describing reality, the general goal of a science. ...
... [24], p. 20. 80 Uno tentativi di conferire carattere di certezza ad aermazioni induttive di questo tipo potrebbe essere quello di assumere l'uniformità della natura, da cui seguirebbe il suo comportarsi in modo regolare. Oltre ad alcune dicoltà che si andrebbero a creare, però, il problema principale è che si tratterebbe comunque di un'assunzione, che non può essere dimostrata se non induttivamente, portando a una circolarità. ...
... mia). 84 Per alcuni esempi di questi dibattiti, si vedano [80] e [46]. 85 Dall'enciclopedia Treccani: ...
Il periodo contemporaneo ha visto una crescente rottura nel rapporto di fiducia fra scienza e società. Il presente lavoro si pone l'obiettivo di analizzare il modo in cui la scienza è stata descritta dalla comunicazione scientifica, sulla base dell'assunto che quest'ultima abbia un ruolo di primo piano nel creare e influenzare la percezione sociale della scienza. Dall'analisi del discorso portato avanti attraverso i mezzi di comunicazione, si evidenzia come venga privilegiato un racconto idealizzato dei risultati della scienza, piuttosto che una descrizione realistica della sua pratica quotidiana. Si suggerisce che tale narrazione possa risultare controproducente in un contesto in cui l'accesso ai meccanismi della scienza in costruzione è facilitato, creando nel pubblico una dissonanza fra la scienza che vede e quella che gli viene raccontata; tale processo provoca una delusione e un conseguente sentimento di diffidenza. Sulla base di questa consapevolezza si analizzano le dinamiche sociali e psicologiche che portano all'instaurarsi della fiducia, fattore che si rivela essere ineliminabile in epistemologia sociale, e si evince come il credere nella scienza non dipenda tanto da fattori razionali come l'effettiva conoscenza della materia, quanto da considerazioni valoriali, culturali o emotive. Alla luce di ciò, si argomenta che una comunicazione pubblica realistica, privata degli aspetti idealizzati e che non nasconde o minimizza le criticità, unita a un atteggiamento orizzontale di apertura e ascolto reciproco, possa rivelarsi vincente nel riabilitare il ruolo e l'affidabilità della scienza all'interno della società.
The contemporary period has seen a growing failure in the relationship of trust between science and society. The present work aims to analyze the way in which science has been described by scientific communication, based on the assumption that the latter has a leading role in creating and influencing the social perception of science. From the analysis of the narrative carried out through the media, it is evident that an idealized account of the results of science is privileged, rather than a realistic description of its daily practice. It is suggested that such a narrative may be counterproductive in a context in which access to the mechanisms of "science in construction" is facilitated, as it might well create a dissonance in the public between the science they see and the one they are told about; this process can cause disappointment and a consequent feeling of distrust. Based on the awareness that trust is an essential factor in social epistemology, the social and psychological dynamics that lead to the construction of trust are analyzed: it turns out that believing in science does not depend so much on rational factors like actual knowledge of the subject, as rather on values and cultural or emotional considerations. In conclusion, it is argued that a realistic public communication, deprived of idealized aspects and which does not hide or minimize critical issues, combined with a horizontal attitude of openness and mutual listening, can prove to be successful in rehabilitating the role and reliability of science within society.
... A related idea is that, due to the theoretical differences between physics and evolutionary biology, we should not waste our time seeking general principles. Instead, we should accept the particularity of evolutionary biology and only focus on local and circumstantiated models of evolution (Mitchell & Dietrich, 2006;Pigliucci, 2002;Waters, 2011). Some of the authors arguing for such a "fragmentalist" view selectively focus on the aspects that distinguish physics from evolutionary biology, ignoring other features that are possibly common to the two disciplines. ...
... Since evolutionary biology, unlike physics, is unable to attain such standards, then it would be unable to provide well-defined and general theoretical frameworks. While some authors (e.g., Fodor & Piattelli-Palmarini, 2010;Popper, 1974) take this as evidence that evolutionary biology is something like an "inferior science", others interpret it as evidence that science does not require the formulation or identification of laws (Beatty, 1995;Lockwood, 2007;Mayr, 2004;O'Hara, 2005;Pigliucci, 2002). ...
Due to its high degree of complexity and its historical nature, evolutionary biology has been traditionally portrayed as a messy science. According to the supporters of such a view, evolutionary biology would be unable to formulate laws and robust theories, instead just delivering coherent narratives and local models. In this article, our aim is to challenge this view by showing how the Price equation can work as the core of a general theoretical framework for evolutionary phenomena. To support this claim, we outline some unnoticed structural similarities between physical theories (in particular, classical mechanics) and evolutionary biology. More specifically, we shall argue that the Price equation, in the same way as fundamental formalisms in physics, can serve as a heuristic principle to formulate and systematise different theories and models in evolutionary biology.
... The predictability of evolutionary change or ecological dynamics has historically been rather poor 41 (Pigliucci, 2002). As such, predictability in population spread has gathered some interest but has been 42 strongly debated as well (Giometto, Rinaldo, Carrara, & Altermatt, 2014; Melbourne & Hastings, 2009). ...
... will not be easily found as stochasticity and historicity have a big impact on ecological outcome relative 343 to identified tangible drivers of these ecological dynamics (Maris et al., 2018;Pigliucci, 2002). We 344 would like to stress that this incapability of making predictions does not make the field of ecology 345 scientifically any worse at describing reality, the general goal of a science. ...
Fragmentation of natural landscapes results in habitat and connectedness loss, making it one of the most impactful avenues of anthropogenic environmental degradation. Populations living in a fragmented landscape can adapt to this context, as witnessed in changing dispersal strategies, levels of local adaptation and changing life-history traits. This evolution, however, can have ecological consequences beyond a fragmented range. Since invasive dynamics are driven by the same traits affected by fragmentation, the question arises whether fragmented populations evolve to be successful invaders.
In this study we assess population spread during three generations of two-spotted spider mite (Tetranychus urticae) population in a replicated experiment. Experimental populations evolved independently in replicated experimental metapopulations differing only in the level of habitat connectedness as determined by the inter-patch distance.
We find that habitat connectedness did not meaningfully explain variation in range expansion speed. Rather, variation within experimental populations that shared the same level of connectedness during evolution was larger than the one across these levels. Therefore, we conclude that experimental populations evolved different range expansion capacities as a result of their specific evolutionary background independent but of the connectedness of the landscape. While population spread capacities may be strongly affected by aspects of a population's evolutionary history, predicting it from identifiable aspects of the evolutionary history may be hard to achieve.
... Un gran número de otros defectos prácticos, estadísticos y lógicos para el enfoque de inferencia fuerte han sido bien documentados (Lawson 2010, Holling y Allen 2002, Pigliucci 2002, Dayton y Sala 2001, Beyers 1998, Weiner 1995, Francis y Hare 1994, Wenner 1989Quinn y Dunham 1983). La inferencia fuerte se basa en probar un árbol de hipótesis binarias que se divide continuamente, pero muchos fenómenos ecológicos ocurren a lo largo de un continuo (O'Donohue y Buchanan 2001). ...
... Aunque ha habido un reciente auge de los argumentos de formas más inclusivas de inferencia científica, las ideas subyacentes no son inventos modernos. El filósofo de la ciencia y biólogo evolutivo Massimo Pigliucci señala que el filósofo del siglo XIX William Whewell utilizó el término "Conciliación de inducción" para describir un proceso mediante el cual capas de diferentes pruebas tomadas desde una amplia gama de puntos de vista apuntan a una respuesta similar, como en el Estudio de extinción masiva de los Álvarez (Pigliucci 2002). Más bien, observamos una mayor atención a las filosofías ecológicas más inclusivas porque reflejan la realidad de cómo debemos lograr la comprensión ecológica en el siglo XXI. ...
Este libro trata de aprovechar el poder de la observación para participar en este momento único del estudio de la ecología. En esencia, toda la ecología se trata principalmente de la observación de la naturaleza, pero en la realidad de la ecología académica, las observaciones se transforman rápidamente en teorías que se prueban en una computadora o en tratamientos experimentales de campo o en un laboratorio donde se manipulan para probar hipótesis bien definidas. Estas son formas importantes de lograr la comprensión ecológica, métodos que han dominado la ecología durante más o menos el último medio siglo, pero tienen limitaciones que se hacen evidentes a medida que van cambiando los sistemas ecológicos.
Aquí nos centramos en la “ecología basada en la observación”, que definimos como la ecología que se basa en observaciones de sistemas que no han sido manipulados con fines científicos. Esta es una definición amplia que abarca una variada gama de poderosas formas de observar y dar sentido a los sistemas ecológicos. Descubrir estos enfoques, sus fortalezas y sus debilidades, es de lo que trata este libro.
... Ecologists aspire to foster knowledge on global environmental changes induced by human activities, such as climate change, biological invasions and habitat loss. To efficiently tackle such challenges, clear, robust, and well-defined epistemological premises about the main determinants of species distribution and species distribution change are needed to design realistic experiments (Pigliucci, 2002;Currie, 2019). Epistemological premises are not just philosophical murmuring but allow us to set the boundaries of the modelling exercise, increasing model robustness in depicting natural patterns and resulting in clear practical applications (Currie, 2019;Dawson et al., 2023). ...
In this synthesis paper, we stress the importance of incorporating causal relationships for the modelling of species distribution. Here, we propose the modelling relation as a conceptual framework for modelling complex and hierarchical processes underlying the distribution of living organisms. We provide an application of the modelling relation using a virtual species example and a structural equation modelling approach. The modelling relation allows setting the boundaries of the modelling exercise, increasing model robustness in depicting natural patterns, eventually resulting in clear practical applications tightly linked to the ecology of the target species.
... Ecologists aspire to foster knowledge on global environmental changes induced by human activities, such as climate change, biological invasions and habitat loss. To efficiently tackle such challenges, clear, robust and welldefined epistemological premises about the main determinants of species dis-tribution and species distribution change are needed to design realistic experiments (Pigliucci, 2002;Currie, 2019). Epistemological premises are not just philosophical murmuring, but allow us to set the boundaries of the modelling exercise, increasing model robustness in depicting natural patterns and resulting in clear practical applications (Currie, 2019). ...
Understanding the causal processes determining the geographical distribution of species is a fundamental question in ecology but has relevant implications in epidemiology. Infectious diseases are a public health concern for humans, livestock, and wildlife, and their relevance has fostered the interest in tools allowing the delineation of areas at risk for pathogen transmission.
In the past two decades, the prompt availability of new spatio-temporal explicit datasets and coding environments has led to extensive use of modelling tools to infer the geographical distribution of the species involved in infectious disease systems. However, the validity of these models was questioned, underlining the lack of biological realism and causal-based reasoning as the main limitations.
In this doctoral dissertation, I tried to include biological realism and a causal-based perspective on correlative and mechanistic modelling approaches aiming to infer the spatio-temporal distribution of vector and host species involved in vector-borne disease systems.
I first applied the modelling relation framework in a species distribution modelling exercise through the Structural Equation Modelling approach, a methodology that includes and evaluates causal pathways within a linear modelling framework. I moved towards mechanistic models and built dynamAedes, a spatially-explicit model inferring the population dynamic of four Aedes mosquito species at different spatial scales. I then explored how the choice of the model parameters and spatial scales affect the outcomes of an epidemiological model estimating the number of Chikungunya’s secondary cases. Finally, since host abundance is an epidemiological parameter as substantial as vector abundance, I presented a downscaling methodology to disaggregate livestock censuses aggregated at different administrative unit levels.
The results highlighted how a causal-based approach increases the biological realism and predictive accuracy of the modelling approaches tested. However, the knowledge of essential biological parameters is scattered, fragmented and not standardized, affecting the models’ outcome quality and reliability. The choice of the spatial scale affects as well the models' outputs, as coarser training and testing datasets produce, on average, better results because of the effects of the Modifiable Areal Unit Problem.
To amend such limitations and promote the effective use of spatial-explicit model outputs for public health decisions, clear communication and dialogue with policymakers are essential to enable them to understand the assumptions of the models and the uncertainty of their predictions.
... Instead, we believe that a new perspective is needed for a truly effective engineering of biology; one that sees a designed biosystem as a starting point in a lineage of possibilities. Although much of evolutionary biology has concerned itself with organisms' histories 19 , bioengineers must consider the future and, specifically, how a biosystem will continue to evolve when used 20 . Here we describe a framework that enables this transition and offers a way to specify, test and conceive the properties of biosystems in terms of their evolutionary potential and not just their phenotype (Fig. 1). ...
Biological technologies are fundamentally unlike any other because biology evolves. Bioengineering therefore requires novel design methodologies with evolution at their core. Knowledge about evolution is currently applied to the design of biosystems ad hoc. Unless we have an engineering theory of evolution, we will neither be able to meet evolution’s potential as an engineering tool, nor understand or limit its unintended consequences for our biological designs. Here, we propose the evotype as a helpful concept for engineering the evolutionary potential of biosystems, or other self-adaptive technologies, potentially beyond the realm of biology.
... Whilst much of evolutionary biology has concerned itself looking backwards at an organism's history 17 , bioengineers must consider the future, and specifically how a biosystem will continue to evolve when used 18 . Here, we describe a framework to enable this transition offering a way to specify, test and conceive the properties of biosystems in terms of their evolutionary potential, and not just their phenotype (Figure 1). ...
Biological technologies are fundamentally unlike any other because biology evolves. Bioengineering therefore requires novel design methodologies with evolution at their core. Knowledge about evolution is currently applied to the design of biosystems ad hoc. Unless we have a unified engineering theory of evolution, we will neither be able to meet evolution’s potential as a design tool, nor understand or limit its unintended consequences on our designs. Our concept of the evotype offers a conceptual framework for engineering the evolutionary potential of biosystems. We show how a biosystem’s evolutionary properties might be rationally designed by engineering aspects of genetic variation, designed function, and natural selection. This idea could apply to all biosystems – from individual proteins to communities of whole-cells or even entire ecosystems – whether the goal is to direct evolution in the design process, or to limit its impacts during application. These principles could even be used beyond the realm of bioengineering to design entirely synthetic evolving auto-adaptive technologies.
... This Bayesian approach allows for a more complete and nuanced appreciation of our results by 1) emphasizing estimated model parameters and resulting estimated dependent variables that are 2) expressed as likelihood distributions: the posterior distribution. Overall, we and a growing part of the research community deems Bayesian inference more appropriate because of its analogy with how ecological and evolutionary research is practiced (Pigliucci, 2002). ...
Individuals moving in heterogeneous environments can improve their fitness considerably by habitat choice. Induction by past exposure, genetic preference alleles and comparison of local performances can all drive this decision‐making process. Despite the importance of habitat choice mechanisms for eco‐evolutionary dynamics in metapopulations, we lack insights on the connection of their cue with its effect on fitness optimization. We selected a laboratory population of Tetranychus urticae Koch (two‐spotted spider mite) according to three distinct host‐choice selection treatments for ten generations. Additionally, we tested the presence of induced habitat choice mechanisms and quantified the adaptive value of a choice before and after ten generations of artificial selection in order to gather insight on the habitat choice mechanisms at play. Unexpectedly, we observed no evolution of habitat choice in our experimental system: the initial choice of cucumber over tomato remained. However, this choice became maladaptive as tomato ensured a higher fitness at the end of the experiment. Furthermore, a noteworthy proportion of induced habitat choice can modify this ecological trap depending on past environments. Despite abundant theory and applied relevance, we provide the first experimental evidence of an emerging trap. The maladaptive choice also illustrates the constraints habitat choice has in rescuing populations endangered by environmental challenges or in pest control.
... Recently, Bayesian Low 7.2-9.0 13-15 6.9-7.2 21858 0 07 0 0 S 47853 0 08 0 0 W approaches have been used in biodiversity studies (Reckhow 1990, Ellison 1996, Hilborn and Margel 1997, Pigliucci 2002, but see Dennis 1996), and some methods have been proposed for estimating biodiversity (Chao 2004). The Bayesian approach seems to be particularly promising for estimating the probability of the occurrence of rare species (Dixon et al. 2005). ...
The Atlantic Forest of Brazil has been identified as a biodiversity hotspot of global significance. We assessed chironomid (Diptera:Chironomidae) taxa richness in 2 vegetation types in this region: the Atlantic Rain Forest and the Atlantic Semi-deciduous Forest. Taxa were collected from 15 low-order streams across multiple habitats. A total of 191 morphospecies were recognized (125 Chironominae, 28 Tanypodinae, and 38 Orthocladiinae). We estimated chironomid richness using a Bayesian statistical approach. Species-richness estimates ranged from 200 (credibility interval, 195-207) to 267 (248-288). These results place low-order streams from Atlantic Forest among the most chironomid speciose areas in the world.
... Adaptation to environmental alterations, such as an increased competition for food, depends on the development of a series of physiological and/or behavioral changes (Wassermann & Futuyma, 1981;Zucoloto, 1993;Gould, 2002;Teixeira & Zucoloto, 2003). These changes may be due to phenotypic plasticity, that is, the property of a given genotype to produce different phenotypes in response to distinct environmental conditions (Stearns, 1992;Pigliucci, 2002;West-Eberhard, 2003;Teixeira et al., 2008Teixeira et al., , 2009. A genotype is non-plastic if it shows the same phenotype in all environments (Pigliucci, 2001). ...
It is largely known that the range of an insect diet is mostly determined by oviposition behavior, mainly in species with endophytic larvae such as Zabrotes subfasciatus. However, the proximate factors determining host choice and the subsequent steps leading to the expansion or reduction of the host number and occasional host shifts are largely unknown. We analyzed various factors determining host preference of Z. subfasciatus through the evaluation of: (i) oviposition preference of a wild population of Z. subfasciatus on the usual host (bean) and unusual hosts (lentil, chickpea and soy), and the performance of the offspring; (ii) artificial selection for increasing preference for hosts initially less frequently chosen; (iii) comparison of oviposition behavior between two different populations (reared for ∼30 generations in beans or chickpeas, respectively); (iv) oviposition timing on usual and unusual hosts; and (v) identification of preference hierarchies. We found that when using unusual hosts, there is no correlation between performance and preference and that the preference hierarchy changes only slightly when the population passes through several generations on the less frequently accepted host. We also found a positive response to artificial selection for increasing oviposition on the less preferred host; however, when the host-choice experiment involved two varieties of the usual host, the response was faster than when the choice involved usual and unusual hosts. Finally, beetles reared on an unusual host (chickpea) for 26 generations showed similar good fitness on both usual and unusual hosts, indicating that the use of a new host does not necessarily result in the loss of performance on the original host. Nevertheless, this population showed lower fitness on the usual host than that of the original population, suggesting an underlying partial trade-off phenomenon which may contribute to a broadening of diet of this insect species.
... We could not have anticipated, for example, which models to test against our data unless we knew which populations were nutrient limited and under what circumstances, and whether active shoot meristems were limiting for those populations and under what circumstances, facts that changed depending on the population being considered. This sort of problem is common in biology, due to the contingent evolutionary histories of living systems (Pigliucci 2002b), and illustrates that there is probably no one set of assumptions able to account for the tolerance of all plants, even for different populations of a single species (discussed by Hawkes and Sullivan 2001). We suggest that efforts at unifying all instances of tolerance under a single explanatory model will not be fruitful and that tolerance is best studied on a more local (genetically and geographically) level, where a given set of assumptions are more likely to be homogeneously valid and where particular models (such as individual ones from the LRM framework, for instance) can be applied after careful consideration and prior study. ...
Tolerance to apical meristem damage (AMD) is a form of plant defense against herbivory. Theoretical models come to different conclusions about the effects of inorganic soil nutrient levels on tolerance to AMD, and different plants have shown different relationships between these variables. To assign some order to these disparate patterns and to resolve conflicts among the models, the ‘limiting resources model’ (LRM) was developed. However, we believe that the LRM is actually comprised of several different models, which we describe. Our study marks the first comprehensive and simultaneous test of the entire LRM framework, treating it explicitly as separate models, which also evaluates the models’ underlying assumptions. We studied tolerance to AMD in laboratory-reared natural populations of Arabidopsis thaliana from three different regions of Europe, spanning a wide latitudinal gradient. We show that, in different populations of this species, basic responses to nutrients and damage are best described by different models, which are based on different assumptions and make different predictions. This demonstrates the need for complexity in our explanations, and suggests that no one existing model can account for all relationships between tolerance to AMD and nutrients. Our results also demonstrate that fruit production can provide a misleading approximation of fitness in A. thaliana, contrary to the common assumption in the literature.
... Such a shift is already well under way in fields outside of anthropology. 11,[13][14][15] ...
In their ambitious Evolutionary Anthropology paper, Winterhalder and Smith1 review the history, theory, and methods of human behavioral ecology (HBE). In establishing how HBE differs from traditional approaches within sociocultural anthropology, they and others laud its hypothetical-deductive research method.1–3 Our aim is to critically examine how human behavioral ecologists conduct their research, specifically how they analyze and interpret data as evidence for scientific hypotheses. Through computer simulations and a review of empirical studies of human sex ratios, we consider some limitations of the status quo and present alternatives that could strengthen the field. In particular, we suggest that because human behavioral ecologists often consider multiple hypotheses, they should use statistical approaches that can quantify the evidence in empirical data for competing hypotheses. Although we focus on HBE, the principles of this paper apply broadly within biological anthropology.
... By no means do I believe that predictive capacity is easily forthcoming in evolutionary theory, selectionist or otherwise. 9 It is hard work to make surprising, risky, and correct novel predictions for complex systems with strong historicity (see Pigliucci 2002). 10 However, through a well-designed causal-experimental protocol, Lenski managed to control and randomize experimental conditions in order to test selectionist evolutionary theory. ...
Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.
... " (Darwin & Seward 1903). Today it might seem odd that a scientist was at pains to justify his research to a pair of philosophers, and yet evolutionary biology still partially retains the unfortunate reputation of being a " soft science " (Pigliucci 2002), in part as a consequence of lingering philosophical confusion about the nature of historical versus experimental research (Cleland 2002). What the original Darwinism was really missing was not a solid philosophical foundation but rather a theory of heredity. ...
Evolutionary theory is undergoing an intense period of discussion and reevaluation. This, contrary to the misleading claims of creationists and other pseudoscientists, is no harbinger of a crisis but rather the opposite: the field is expanding dramatically in terms of both empirical discoveries and new ideas. In this essay I briefly trace the conceptual history of evolutionary theory from Darwinism to neo-Darwinism, and from the Modern Synthesis to what I refer to as the Extended Synthesis, a more inclusive conceptual framework containing among others evo-devo, an expanded theory of heredity, elements of complexity theory, ideas about evolvability, and a reevaluation of levels of selection. I argue that evolutionary biology has never seen a paradigm shift, in the philosophical sense of the term, except when it moved from natural theology to empirical science in the middle of the 19th century. The Extended Synthesis, accordingly, is an expansion of the Modern Synthesis of the 1930s and 1940s, and one that--like its predecessor--will probably take decades to complete.
... First, the process may require only a few generations (as in Waddington's experiments), which means that it could occur so rapidly as to pass below the radar screen of evolutionary biologists, unless they were explicitly looking for it. Secondly, evolutionary biology is a historical science (Pigliucci, 2002), and in historical research 'evidence' is not simply out there for the taking, it becomes an object of a search in light of specific hypotheses (we would do well to remember Darwin's words in a letter to Henry Fawcett: 'How odd it is that anyone should not see that all observation must be for or against some view if it is to be of any service!' Numerous cases, in diverse organisms, have been identified that are compatible with the hypothesis of GA (see Rollo, 1994; Pigliucci and Murren, 2003; West-Eberhard, 2003; Tardieu, 1999; Chapman et al., 2000; Cooley et al., 2001; Sword, 2002; Price et al., 2003; Heil et al., 2004; Mery and Kawecki, 2004; Palmer, 2004; Keogh et al., 2005), so it seems that there is plenty of reasonable ground for advocating more explicit tests of the possibility that GA occurs in natural populations. Additionally, since Pigliucci and Murren (Pigliucci and Murren, 2003) and Schlichting (Schlichting, 2004), several theoretical approaches continue to examine genetic assimilation under a variety of conditions (e.g. ...
In addition to considerable debate in the recent evolutionary literature about the limits of the Modern Synthesis of the 1930s and 1940s, there has also been theoretical and empirical interest in a variety of new and not so new concepts such as phenotypic plasticity, genetic assimilation and phenotypic accommodation. Here we consider examples of the arguments and counter-arguments that have shaped this discussion. We suggest that much of the controversy hinges on several misunderstandings, including unwarranted fears of a general attempt at overthrowing the Modern Synthesis paradigm, and some fundamental conceptual confusion about the proper roles of phenotypic plasticity and natural selection within evolutionary theory.
To understand how ecology will serve us in this era age of rapid environmental change, we need to understand that ecology is not a static discipline. It is continuously adapting to the changing world that ecologists find themselves living and working within. This chapter is about the most recent adaptation in ecology, which can be seen in both an increased use and increased diversity of observational approaches to understanding ecological phenomena. This adaptation, like stepwise adaptations in nature, hasn’t created an entirely new and unrecognizable entity, but rather has grown recursively from the past state of ecology. Accordingly, we first discuss what ecology was for much of its existence and then we explore how the urgency of environmental change and the opportunity to study that change in unprecedented ways is providing a pathway for adaptation of the science of ecology.
Questions and criticisms that arise around observational approaches boil down to one fundamental question: “Is this really science?” This question could be asked of any kind of research, but because observational approaches have been out of the scientific mainstream for a long time, and because they invite so many nonscientists as well as investigators from the so-called soft sciences to be part of the life sciences, it is frequently directed at observational studies. So now that these kinds of studies are being integrated into science, the natural follow-up to the fundamental question becomes “Are observational approaches scientific?”
The need to understand and address large-scale environmental problems that are difficult to study in controlled environmentsissues ranging from climate change to overfishing to invasive speciesis driving the field of ecology in new and important directions. Observation and Ecology documents that transformation, exploring how scientists and researchers are expanding their methodological toolbox to incorporate an array of new and reexamined observational approachesfrom traditional ecological knowledge to animal-borne sensors to genomic and remote-sensing technologiesto track, study, and understand current environmental problems and their implications. The authors paint a clear picture of what observational approaches to ecology are and where they fit in the context of ecological science. They consider the full range of observational abilities we have available to us and explore the challenges and practical difficulties of using a primarily observational approach to achieve scientific understanding. They also show how observations can be a bridge from ecological science to education, environmental policy, and resource management. Observations in ecology can play a key role in understanding our changing planet and the consequences of human activities on ecological processes. This book will serve as an important resource for future scientists and conservation leaders who are seeking a more holistic and applicable approach to ecological science.
Phenotypic integration refers to the study of complex patterns of covariation among functionally related traits in a given organism. It has been investigated throughout the 20th century, but has only recently risen to the forefront of evolutionary ecological research. In this essay, I identify the reasons for this late flourishing of studies on integration, and discuss some of the major areas of current endeavour: the interplay of adaptation and constraints, the genetic and molecular bases of integration, the role of phenotypic plasticity, macroevolutionary studies of integration, and statistical and conceptual issues in the study of the evolution of complex phenotypes. I then conclude with a brief discussion of what I see as the major future directions of research on phenotypic integration and how they relate to our more general quest for the understanding of phenotypic evolution within the neo-Darwinian framework. I suggest that studying integration provides a particularly stimulating and truly interdisciplinary convergence of researchers from fields as disparate as molecular generics, developmental biology, evolutionary ecology, palaeontology and even philosophy of science.
Science is about discovering new things, about better understanding processes and systems, and generally furthering our knowledge. Deep in science philosophy is the notion of hypotheses and mathematical models to represent these hypotheses. It is partially the quantification of hypotheses that provides the illusive concept of rigor in science. Science is partially an adversarial process; hypotheses battle for primacy aided by observations, data, and models. Science is one of the few human endeavors that is truly progressive. Progress in science is defined as approaching an increased understanding of truth – science evolves in a sense.
Phenotypic integration refers to the study of complex patterns of covariation among functionally related traits in a given organism. It has been investigated throughout the 20th century, but has only recently risen to the forefront of evolutionary ecological research. In this essay, I identify the reasons for this late flourishing of studies on integration, and discuss some of the major areas of current endeavour: the interplay of adaptation and constraints, the genetic and molecular bases of integration, the role of phenotypic plasticity, macroevolutionary studies of integration, and statistical and conceptual issues in the study of the evolution of complex phenotypes. I then conclude with a brief discussion of what I see as the major future directions of research on phenotypic integration and how they relate to our more general quest for the understanding of phenotypic evolution within the neo-Darwinian framework. I suggest that studying integration provides a particularly stimulating and truly interdisciplinary convergence of researchers from fields as disparate as molecular genetics, developmental biology, evolutionary ecology, palaeontology and even philosophy of science.
Abstract The effects of competition on populations of the bean weevil Zabrotes subfasciatus were analyzed during 41 generations under different competition levels. Three competition environments were established by maintaining the number of couples (6) and varying the amount of available host seeds: HC, high (limited availability of host: 1.35 g); IC, intermediate (intermediate availability of host: 6 g); and LC, low competition (abundance of host: 36 g). It was found that the distribution of the eggs laid on grains was different among treatments: in LC, for example, although females showed high fecundity (35.4 ± 5.6 eggs/female) the number of eggs laid on each grain was small (1.2 ± 0.4 eggs on each seed), thus avoiding larval competition of their offspring; whereas in HC treatment, females showed low fecundity (27.04 ± 4.5 eggs/female) but laid many eggs on each grain (15.03 ± 4.3 eggs). There were no changes in the ability to respond to different amounts of host via oviposition behavior (egg distribution) during 41 generations. However, HC females had more offspring than LC females under HC conditions. This suggests that HC insects evolved toward higher fitness in crowded conditions. In addition, after inverting the competition level, insects behaved independently of the treatment conditions they experienced through generations, thus showing that oviposition behavior is flexible. Taken together, our results show that Z. subfasciatus presents a broad range of behavioral and physiological responses which allows for quick and reversible adjustments to sudden changes in the amount of resources.
Recent polls suggest that fewer than 40 percent of Americans believe in Darwinâs theory of evolution, despite it being one of scienceâs best-established findings. More and more parents are refusing to vaccinate their children for fear it causes autism, though this link can been consistently disproved. And about 40 percent of Americans believe that the threat of global warming is exaggerated, despite near consensus in the scientific community that manmade climate change is real. Why do people believe bunk? And what causes them to embrace such pseudoscientific beliefs and practices? Noted skeptic Massimo Pigliucci sets out to separate the fact from the fantasy in this entertaining exploration of the nature of science, the borderlands of fringe science, andâborrowing a famous phrase from philosopher Jeremy Benthamâthe nonsense on stilts. Presenting case studies on a number of controversial topics, Pigliucci cuts through the ambiguity surrounding science to look more closely at how science is conducted, how it is disseminated, how it is interpreted, and what it means to our society. The result is in many ways a âtaxonomy of bunkâ that explores the intersection of science and culture at large. No oneânot the public intellectuals in the culture wars between defenders and detractors of science nor the believers of pseudoscience themselvesâis spared Pigliucciâs incisive analysis. In the end, Nonsense on Stilts is a timely reminder of the need to maintain a line between expertise and assumption. Broad in scope and implication, it is also ultimately a captivating guide for the intelligent citizen who wishes to make up her own mind while navigating the perilous debates that will affect the future of our planet.
Natural resource professionals recognize the negative impacts of human developments on the distribution, abundance, and, in
some cases, persistence of wildlife populations or species. Indeed, human activity in all its forms (Kerr and Currie 1995) is a primary cause of the global decline in biodiversity in general (Brooks et al.2002; Dudgeon et al. 2006; White and Kerr 2006) and wildlife in particular (Ceballos and Ehrlich 2002; Laliberte and Ripple 2004; Davies et al.2006). This recognition has led to a rapid increase in the number of studies designed to elucidate and document wildlife–human
interactions (fig. 3.1).
In this paper I argue that we can learn much about wild justice and the evolutionary origins of social morality – behaving fairly – by studying social play behavior in group-living animals, and that interdisciplinary cooperation will help immensely. In our efforts to learn more about the evolution of morality we need to broaden our comparative research to include animals other than non-human primates. If one is a good Darwinian, it is premature to claim that only humans can be empathic and moral beings. By asking the question What is it like to be another animal? we can discover rules of engagement that guide animals in their social encounters. When I study dogs, for example, I try to be a dogocentrist and practice dogomorphism. My major arguments center on the following big questions: Can animals be moral beings or do they merely act as if they are? What are the evolutionary roots of cooperation, fairness, trust, forgiveness, and morality? What do animals do when they engage in social play? How do animals negotiate agreements to cooperate, to forgive, to behave fairly, to develop trust? Can animals forgive? Why cooperate and play fairly? Why did play evolve as it has? Does being fair mean being more fit – do individual variations in play influence an individual''s reproductive fitness, are more virtuous individuals more fit than less virtuous individuals? What is the taxonomic distribution of cognitive skills and emotional capacities necessary for individuals to be able to behave fairly, to empathize, to behave morally? Can we use information about moral behavior in animals to help us understand ourselves? I conclude that there is strong selection for cooperative fair play in which individuals establish and maintain a social contract to play because there are mutual benefits when individuals adopt this strategy and group stability may be also be fostered. Numerous mechanisms have evolved to facilitate the initiation and maintenance of social play to keep others engaged, so that agreeing to play fairly and the resulting benefits of doing so can be readily achieved. I also claim that the ability to make accurate predictions about what an individual is likely to do in a given social situation is a useful litmus test for explaining what might be happening in an individual''s brain during social encounters, and that intentional or representational explanations are often important for making these predictions.
Making Sense of Evolution explores contemporary evolutionary biology, focusing on the elements of theoriesâselection, adaptation, and speciesâthat are complex and open to multiple possible interpretations, many of which are incompatible with one another and with other accepted practices in the discipline. Particular experimental methods, for example, may demand one understanding of âselection,â while the application of the same concept to another area of evolutionary biology could necessitate a very different definition. Spotlighting these conceptual difficulties and presenting alternate theoretical interpretations that alleviate this incompatibility, Massimo Pigliucci and Jonathan Kaplan intertwine scientific and philosophical analysis to produce a coherent picture of evolutionary biology. Innovative and controversial, Making Sense of Evolution encourages further development of the Modern Synthesis and outlines what might be necessary for the continued refinement of this evolving field.
The so-called "species problem" has plagued evolutionary biology since before Darwin's publication of the aptly titled Origin of Species. Many biologists think the problem is just a matter of semantics; others complain that it will not be solved until we have more empirical data. Yet, we don't seem to be able to escape discussing it and teaching seminars about it. In this paper, I briefly examine the main themes of the biological and philosophical literatures on the species problem, focusing on identifying common threads as well as relevant differences. I then argue two fundamental points. First, the species problem is not primarily an empirical one, but it is rather fraught with philosophical questions that require-but cannot be settled by-empirical evidence. Second, the (dis-)solution lies in explicitly adopting Wittgenstein's idea of "family resemblance" or cluster concepts, and to consider species as an example of such concepts. This solution has several attractive features, including bringing together apparently diverging themes of discussion among biologists and philosophers. The current proposal is conceptually independent (though not incompatible) with the pluralist approach to the species problem advocated by Mishler, Donoghue, Kitcher and Dupré, which implies that distinct aspects of the species question need to be emphasized depending on the goals of the researcher. From the biological literature, the concept of species that most closely matches the philosophical discussion presented here is Templeton's cohesion idea.
Presents an analysis of theory and research in social psychology which reveals that while methods of research are scientific in character, theories of social behavior are primarily reflections of contemporary history. The dissemination of psychological knowledge modifies the patterns of behavior upon which the knowledge is based. This modification occurs because of the prescriptive bias of psychological theorizing, the liberating effects of knowledge, and the resistance based on common values of freedom and individuality. In addition, theoretical premises are based primarily on acquired dispositions. As the culture changes, such dispositions are altered, and the premises are often invalidated. Several modifications in the scope and methods of social psychology are derived from this analysis. (53 ref.) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Theories in "soft" areas of psychology (e.g., clinical, counseling, social, personality, school, and community) lack the cumulative character of scientific knowledge because they tend neither to be refuted nor corroborated, but instead merely fade away as people lose interest. Even though intrinsic subject matter difficulties (20 are listed) contribute to this, the excessive reliance on significance testing is partly responsible (Ronald A. Fisher). Karl Popper's approach, with modifications, would be prophylactic. Since the null hypothesis is quasi-always false, tables summarizing research in terms of patterns of "significant differences" are little more than complex, causally uninterpretable outcomes of statistical power functions. Multiple paths to estimating numerical point values ("consistency tests") are better, even if approximate with rough tolerances; and lacking this, ranges, orderings, 2nd-order differences, curve peaks and valleys, and function forms should be used. Such methods are usual in developed sciences that seldom report statistical significance. Consistency tests of a conjectural taxometric model yielded 94% success with no false negatives. (3 p ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Aptitude * Treatment interactions are demonstrated with reference to G. Domino's studies (1968 and 1971) of instructor demand and student personality and J. K. Majasan's (1972) study which found that achievement in college psychology was greatest when the student's position on a scale of beliefs regarding behaviorism and humanism were similar to his instructor's. Further evidence on interactions in social psychology, personality, learning, and experimental psychology is cited. It is suggested that higher order interactions make it unlikely that social scientists will be able to establish generalizations applicable beyond the laboratory or that generalizations established in the field work will be maintained. Social research should be less concerned with hypothesis testing and more concerned with interpreting findings in local contexts. (59 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Examines exploratory and confirmatory data analysis, emphasizing the need for flexibility in technique supported by empirical trial. It is suggested that the restrictions of Campbellian measurement should be cast off. The need for using conjoint measurement in working with simultaneous changes is stressed, along with the need for more diverse bodies of data that can be measured in common ways. The use of correlation coefficients is regarded as an enemy of generalization. Exploratory and confirmatory data analysis are both considered to be essential, especially in detective work and guidance counselling. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Adaptation to a novel environment is expected to have a number of features. Among these is a temporal increase in fitness and some or all of its components. It is also expected that additive genetic variances for these fitness characters will fall. Finally, it is expected that at least some additive genetic correlations will decrease, from positive toward negative values.
In a study of several life‐history variables in a Drosophila subobscura population sampled from the wild and then cultured in the laboratory, we did not find any such longitudinal trends over the first 29 generations. However, a temporal comparison (over 14 generations) of the later generations of this laboratory‐adapted population with a new population, derived from a more recent wild‐caught sample, indicated clearly that laboratory adaptation was nonetheless occurring. This study suggests the need for extensive replication and control in studies of the features of adaptation to a novel environment.
After 4 decades of severe criticism, the ritual of null hypothesis significance testing—mechanical dichotomous decisions around a sacred .05 criterion—still persists. This article reviews the problems with this practice, including its near-universal misinterpretation of p as the probability that H 0 is false, the misinterpretation that its complement is the probability of successful replication, and the mistaken assumption that if one rejects H 0 one thereby affirms the theory that led to the test. Exploratory data analysis and the use of graphic methods, a steady improvement in and a movement toward standardization in measurement, an emphasis on estimating effect sizes using confidence intervals, and the informed use of available statistical methods is suggested. For generalization, psychologists must finally rely, as has been done in all the older sciences, on replication.
Many evolutionary studies use comparisons across species to detect evidence of natural selection and to examine the rate of character evolution. Statistical analyses in these studies are usually performed by means of a species phylogeny to accommodate the effects of shared evolutionary history. The phylogeny is usually treated as known without error; this assumption is problematic because inferred phylogenies are subject to both stochastic and systematic errors. We describe methods for accommodating phylogenetic uncertainty in evolutionary studies by means of Bayesian inference. The methods are computationally intensive but general enough to be applied in most comparative evolutionary studies.
The morphological order of evolutionary trees has been the traditional argument for the operation of directional causes in macroevolution. We show, in this work, that a similar order can be generated within stochastic systems bounded by minimal biological constraints. Our system generates an evolutionary tree by making random decisions about each lineage in each time interval given preset probabilities for branching, extinction and persistence (Raup, Gould, Schopf, and Simberloff, 1973). Morphology is determined in an independent and equally stochastic manner. Using ten hypothetical characters, the beginning lineage is given an all zero morphology. At each branching point, each character may change by one unit (in a positive or negative direction) according to preset probabilities for positive change, negative change, and no change. Our simulations display most of the ordered features generally associated with uni-directional selection: morphological coherence of monophyletic groups and incomplete filling of "morphological space"; regular "unfolding" of morphology (as seen in strong correspondence between phenetic and cladistic taxonomies); marked evolutionary "trends"; strong correlation among characters; large variation in rates of evolution; and specialization of derived forms. We attribute much of this order to abstract topological properties of the tree itself and urge that the data for inferences about directional causes be sought elsewhere (in functional morphology, for example). We suggest, with caution, that undirected selection may be the rule rather than the exception in nature, if a temporal unit of sufficient duration be used as the yardstick of measurement.
Genetic adaptation of wild populations to captivity can be a problem for studies of evolution and for programs of conservation and biological control. We examine how the life history of Drosophila melanogaster, the most commonly used organism for laboratory studies of evolution, evolves in response to two common methods of laboratory culture: in bottles and in population cages. We collected flies at the same site in nature at the same time of year in three consecutive years and compared freshly collected populations from the third collection with the products of 1 or 2 yr's laboratory culture, in a replicated experimental design. Preadult development time increased in the laboratory, particularly in cage culture. There was also an increase in larval competitive ability in both types of culture. Body size was little affected, increasing slightly and only in the bottle culture. Early fecundity increased in bottle culture, while late fecundity declined. Adult mortality rates were lowest in the fresh collections and showed a marked and progressive increase in bottle culture with a slight increase in population cage culture and apparently only in the first year of culture. Remating frequency increased in bottle but not cage culture. These evolutionary changes are most likely explained by increased larval competition in laboratory culture, especially in population cages, and by truncation of the adult period in the bottle culture, resulting in natural selection acting solely on the early part of the adult period.
Members of colonial plant species often occur as scattered individuals well beyond the borders of local populations. The ecological and genetical importance of these outliers to local populations and to the species as a whole have not been considered. A review of the reproductive biology of outliers and of sparse plants in general indicates that they produce fewer seeds per flower than plants within populations. Nevertheless, they successfully interbreed over large distances. I propose that outliers form large, diffuse assemblages of interbreeding plants that may fill the gaps between some local populations. These outlier assemblages may be prime sources of extraneous pollen and seeds, retard the divergence of local populations between which they reside, and form the nuclei for new populations. Outliers may receive more or less pest pressure than plants within populations. They serve as interpopulation bridges for pathogens and herbivores.
Advocates of the “strong programme” in the sociology of knowledge have argued that, because scientific theories are “underdetermined” by data, sociological factors must be invoked to explain why scientists believe the theories they do. I examine this argument, and the responses to it by J.R. Brown (1989) and L. Laudan (1996). I distinguish between a number of different versions of the underdetermination thesis, some trivial, some substantive. I show that Brown's and Laudan's attempts to refute the sociologists' argument fail. Nonetheless, the sociologists' argument falls to a different criticism, for the version of the underdetermination thesis that the argument requires, has not been shown to be true.
Can anything be less certain than chance? Nature can, according to these views.
Various estimates of the time at which the human mitochondrial Eve lived have ranged from as little as 60,000 yr to more than 500,000 yr ago. Because of this immense range, it is impossible to distinguish between single-origin and multiple-origins hypotheses for the evolution of our species. In an attempt to reduce the uncertainty, I have examined the largest available body of sequence information, comprising the mitochondrial control region, for clues to how the observed diversity arose. In this region it is possible to show, by examining the distribution of polymorphic sites, that transitions have occurred at some sites at a much higher rate than at others. Computer simulations can, when two rates for transitions are postulated, provide close approximations to the distribution of substitutions seen in the actual data. The ''best fit'' was obtained when the rate at 3/4 Of the sites was 4 times the transversion rate, and the rate at the remainder 160 times the transversion rate. The likelihood of such a high rate at some sites helps to explain why tree-building methods employing these data have provided so little phylogenetic information. Furthermore, it is possible to show that transversions do not appear to occur preferentially al these transition ''hot-spot'' sites and that such huge differences in substitution rates are not seen for transversions, suggesting that the rules governing the mutation and acceptance or rejection of transversions are different from those governing transitions. The great majority of transversions appear to occur at a low rate throughout the region. Thus, methods for determining the age of Eve that are based on recent divergence in human populations, or on applying a mutation probability matrix based on an assumption of uniform mutation rates, are likely to result in underestimates. The rate of accumulation of transversions is shown to be a more accurate estimator of the age of Eve. The conclusion is reached that Eve probably lived (depending on when the ancestors of humans and chimpanzees diverged) between 436,000 and 806,000 yr ago.
STATISTICSBayesian statistics, which allows researchers to use everything from hunches to hard data to compute the probability that a hypothesis is correct (see p. [1461][1]), is experiencing a renaissance in fields of science ranging from astrophysics to genomics and in real-world applications such as testing new drugs and setting catch limits for fish. Advances in computers and the limitations of traditional statistical methods are part of the reason for the new popularity of this approach, first proposed in a 1763 paper by the Reverend Thomas Bayes. In addition, advocates say it produces answers that are easier to understand and forces users to be explicit about biases obscured by reigning "frequentist" approaches. Detractors, on the other hand, fear that because Bayesian analysis can take into account prior opinion, it could spawn less objective evaluations of experimental results.
[1]: http://www.sciencemag.org/cgi/content/short/286/5444/1461
Most work done in philosophy of experiment has focused on experiments taken from the domain of physics. The present essay tests whether Allan Franklin's (1984, 1986, 1989, 1990) philosophy of experiment developed in the context of high energy physics can
be extended to include examples from evolutionary biology, such as H. B. D. Kettlewell's (1955, 1956, 1958) famous studies of industrial melanism in the peppered moth, Biston betularia. The analysis demonstrates that many of the techniques used by
evolutionary biologists exemplify the strategies Franklin lists, and identifies an additional strategy that can likewise be justified by appeal to Bayes's Theorem.
That biology provides explanations is not open to doubt. But how it does so must be a vexed question for those who deny that biology embodies laws or other generalizations with the sort of explanatory force that the philosophy of science recognizes. The most common response to this problem has involved redefining law so that those grammatically general statements which biologists invoke in explanations can be counted as laws. But this terminological innovation cannot identify the source of biology's explanatory power. I argue that because biological science is historical, the problem of biological explanation can be assimilated to the parallel problem in the philosophy of history, and that the problem was solved by Carl Hempel. All we need to do is recognize that the only laws that biology-in all its compartments from the molecular onward-has or needs are the laws of natural selection.
Selection experiments with Drosophila have revealed constraints on the simultaneous evolution of life history traits. However, the responses to selection reported by different research groups have not been consistent. Two possible reasons for these inconsistencies are (i) that different groups used different environments for their experiments and (ii) that the selection environments were not identical to the assay environments in which the life history traits were measured. We tested for the effect of the assay environment in life history experiments by measuring a set of Drosophila selection lines in laboratories working on life history evolution with Drosophila in Basel, Groningen, Irvine and London. The lines measured came from selection experiments from each of these laboratories. In each assay environment, we measured fecundity, longevity, development time and body size. The results show that fecundity measurements were particularly sensitive to the assay environment. Differences between assay and selection environment in the same laboratory or differences between assay environments between laboratories could have contributed to the differences in the published results. The other traits measured were less sensitive to the assay environment. However, for all traits there were cases where the measurements in one laboratory suggested that selection had an effect on the trait, whereas in other laboratories no such conclusion would have been drawn. Moreover, we provide good evidence for local adaptation in early fecundity for lines from two laboratories.
The dictionary definition of a law is: 'Generalized formulation based on a series of events or processes observed to recur regularly under certain conditions; a widely observable tendency'. I argue that ecology has numerous laws in this sense of the word, in the form of widespread, repeatable patterns in nature, but hardly any laws that are universally true. Typically, in other words, ecological patterns and the laws, rules and mechanisms that underpin them are contingent on the organisms involved, and their environment. This contingency is manageable at a relatively simple level of ecological organisation (for example the population dynamics of single and small numbers of species), and re-emerges also in a manageable form in large sets of species, over large spatial scales, or over long time periods, in the form of detail-free statistical patterns - recently called 'macroecology'. The contingency becomes overwhelmingly complicated at intermediate scales, characteristic of community ecology, where there are a large number of case histories, and very little other than weak, fuzzy generalisations. These arguments are illustrated by focusing on examples of typical studies in community ecology, and by way of contrast, on the macroecological relationship that emerges between local species richness and the size of the regional pool of species. The emergent pattern illustrated by local vs regional richness plots is extremely simple, despite the vast number of contingent processes and interactions involved in its generation. To discover general patterns, laws and rules in nature, ecology may need to pay less attention to the 'middle ground' of community ecology, relying less on reductionism and experimental manipulation, but increasing research efforts into macroecology.
Statistical analyses are used in many fields of genetic research. Most geneticists are taught classical statistics, which includes hypothesis testing, estimation and the construction of confidence intervals; this framework has proved more than satisfactory in many ways. What does a Bayesian framework have to offer geneticists? Its utility lies in offering a more direct approach to some questions and the incorporation of prior information. It can also provide a more straightforward interpretation of results. The utility of a Bayesian perspective, especially for complex problems, is becoming increasingly clear to the statistics community; geneticists are also finding this framework useful and are increasingly utilizing the power of this approach.
The surgical disconnection of the cerebral hemispheres creates an extraordinary opportunity to study basic neurological mechanisms: the organization of the sensory and motors systems, the cortical representation of the perceptual and cognitive processes, the lateralization of function, and, perhaps most importantly, how the divided brain yields clues to the nature of conscious experience. Studies of split-brain patients over the last 40 years have resulted in numerous insights into the processes of perception, attention, memory, language and reasoning abilities. When the constellation of findings is considered as a whole, one sees the cortical arena as a patchwork of specialized processes. When this is considered in the light of new studies on the lateralization of functions, it becomes reasonable to suppose that the corpus callosum has enabled the development of the many specialized systems by allowing the reworking of existing cortical areas while preserving existing functions. Thus, while language emerged in the left hemisphere at the cost of pre-existing perceptual systems, the critical features of the bilaterally present perceptual system were spared in the opposite half-brain. By having the callosum serve as the great communication link between redundant systems, a pre-existing system could be jettisoned as new functions developed in one hemisphere, while the other hemisphere could continue to perform the previous functions for both half-brains. Split-brain studies have also revealed the complex mosaic of mental processes that participate in human cognition. And yet, even though each cerebral hemisphere has its own set of capacities, with the left hemisphere specialized for language and speech and major problem-solving capacities and the right hemisphere specialized for tasks such as facial recognition and attentional monitoring, we all have the subjective experience of feeling totally integrated. Indeed, even though many of these functions have an automatic quality to them and are carried out by the brain prior to our conscious awareness of them, our subjective belief and feeling is that we are in charge of our actions. These phenomena appear to be related to our left hemisphere's interpreter, a device that allows us to construct theories about the relationship between perceived events, actions and feelings.
We investigate changes in resistance to desiccation and starvation during adaptation of Drosophila melanogaster to laboratory culture. We test the hypothesis that resistance to environmental stresses is lost under laboratory adaptation. For both traits, there was a rapid loss of resistance over a three-year period. The rapidity of the response suggested that mutation accumulation could not account for it. Rather, resistance to environmental stresses appeared to be lost as a correlated response to selection on another trait, such as early fertility, with which stress resistance is negatively genetically correlated. These results suggest that caution is needed when extrapolating from evolution of stress resistance in long-established laboratory stocks to patterns of responses and correlated responses in natural populations.
explicitly the chief programmatic fallacy committed by those who argue so strongly for the importance of heritability measures for human traits. The fallacy is that a knowledge of the heritability of some trait in a population provides an index of the efficacy of environmental or clinical intervention in altering the trait either in individuals or in the population as a whole. This fallacy, sometimes propagated even by geneticists, who should know better, arises from the confusion between the technical meaning of heritablility and the everyday meaning of the word. A trait can have a heritability of 1.0 in a population at some time, yet this could be completely altered in the future by a simple environmental change. If this were not the case, ‘inborn errors of metabolism’ would be forever incurable, which is patently untrue. But the misunderstanding about the relationship between heritability and phenotypic plasticity is not simply the result of an ignorance of genetics on the part of psychologists and electronic engineers. It arises from the entire system of analysis of causes through linear models, embodied in the analysis of variance and covariance and in path analysis. It is indeed ironic that while Morton and his colleagues dispute the erroneous programmatic conclusions that are drawn from the analysis of human phenotypic variation, they nevertheless rely heavily for their analytic techniques on the very linear models that are responsible for the confusion. I would like to look rather closely at the problem of the analysis of causes in human genetics and to try to understand how the underlying model of this analysis moulds our view of the real world. I will begin by saying some very obvious and elementary things about causes, but I will come thereby to some very annoying conclusions.
Scientists these days tend to keep up a polite fiction that all science is equal. Except for the work of the misguided opponent whose arguments we happen to be refuting at the time, we speak as though every scientist's field and methods of study are as good as every other scientist's, and perhaps a little better. This keeps us all cordial when it comes to recommending each other for government grants. But I think anyone who looks at the matter closely will agree that some fields of science are moving forward very much faster than others, perhaps by an order of mag nitude, if numbers could be put on such estimates. The discoveries leap from the head lines - and they are real advances in complex and difficult subjects, like molecular biology and high-energy physics. As Alvin Weinberg (1964), says "Hardly a month goes by without a stunning success in molecular biology being reported in the Proceed ing of the National Academy of Science." Why should there be such rapid advances in some fields and not in others? I think the usual explanations that we tend to think of-such as the tractability of the subject, or the quality or education of the men drawn into it, or the size of research contracts are important but inadequate. I have begun to believe that the primary factor in scienSource: Science (1965), 146:347-353. Copyright 1965 by the American Association for the Advancement of Science and reprinted by permission.