Theoretical and Experimental Ecology Station
The erosion of biodiversity is, along with climate change, one of the greatest challenges societies will face in this century and beyond (Dirzo et al. 2014, Hallmann et al. 2017, Ripple et al. al. 2017, IPBES 2019, IPCC 2019). Indeed, biodiversity is part of most human activities, directly or indirectly, by providing biological resources used for multiple purposes (food and health being the most obvious examples), by helping to maintain a wide range of ecological services on which all human activities depend, and by participating in the very framework of the material and spiritual life of the human species. The ongoing erosion of biodiversity is therefore likely to have far-reaching consequences for societies in the centuries to come. It is in this context that an integrative science of biodiversity is emerging (Loreau 2010), whose links with decision-making processes should be strengthened, in particular through the Intergovernmental Platform on Biodiversity and Services. Ecosystems (IPBES).
Theoretical ecology plays an essential role in shedding light on the cause and effect processes and relationships that take place in the particularly complex systems of ecosystems and socio-ecological systems. It also helps to better understand the impacts of changes in biodiversity by clarifying complex concepts, fundamental to the study of biodiversity and its causes and consequences, such as biodiversity, functioning and stability of ecosystems.
France has a strong community of theoretician and modelling ecologists, and the meetings of the GDR Theory and Modeling of Biodiversity play an important unifying role in this community. Our community finds considerable interest in comparing the approaches and coordinating the research efforts of the various research teams in France in this field.
The growth of the human population and its standard of living leads to overexploitation of land and oceans, disrupting the global climate and leading species to extinction. The ecological responses to these disturbances are inevitably complex and require measures which allow them to be accurately described. Collectively, these measures assess the overall "stability" of ecological systems. Both disturbances to natural systems and the concept of stability are multidimensional. On the other hand, our understanding of these is not. This means that we have a remarkably poor understanding of the effects of different characteristics of the ongoing planetary changes on ecological stability.
The fragmented and one-dimensional approach adopted by environmentalists has led to ambiguities about the nature of stability as well as a clear disconnection between the theoretical and empirical literature on the subject (Donohue et al. 2016). Most of the theoretical work in ecology has been interested in the local asymptotic stability of ecological systems in the vicinity of an equilibrium and generally quantified this form of stability by the “resilience” of a system (Donohue et al. 2016, Kéfi et al. al. 2019), i.e. by the speed of its asymptotic return to equilibrium as given by the dominant value of the community matrix (May 1973). Most empirical studies, on the other hand, have used more practical measures of stability, such as the inverse of the coefficient of variation over time of the variables studied (Tilman et al. 2006, Hector et al. 2010).
A first question that arises is that of the relationship between the different stability measures used in ecology (Donohue et al. 2013): which metrics are redundant between them and which ones contain different information? In recent years, work has started to elucidate the relationships between certain stability metrics (Arnoldi et al. 2016, 2018, Arnoldi and Haegeman 2016, Dominguez-Garcia et al. 2019).
Another question is that of the relationships between biodiversity and different measures of stability, as well as the mechanisms responsible for these relationships. Recent empirical research has shown that biodiversity can indeed increase or decrease stability, depending on the measure of stability considered (e.g., resistance and variability) (Pennekamp et al. 2018).
The disturbances are also multidimensional. A recent study has shown that the type of disturbance can modify the relationship between biodiversity and stability. For example, even considering a single metric of stability, a change in biodiversity can increase or decrease the temporal invariability depending on whether the disturbance mainly affects the most abundant or least abundant species within a community (Arnoldi et al. 2019). Likewise, the type of habitat loss that affects food webs can increase or decrease their stability, as measured by the temporal variability of populations (McWilliams et al. 2019). If habitat is contiguously or correlated (i.e., large portions of habitat are lost while others remain intact), population variability increases. On the contrary, if habitat is lost at random in a given landscape, the variability of populations decreases.
In addition, most of the research on the relationships between biodiversity and ecosystem stability has been conducted primarily at the local level. However, the loss of biodiversity considerably reduces a number of ecosystem services by altering the functioning and stability of ecosystems at large temporal and spatial scales, which are most relevant for conservation and management (Gonzalez et al. In press, Isbell et al. 2015). A new theoretical study shows that biodiversity is becoming increasingly important for the functioning of ecosystems at larger spatial scales (Thompson et al. 2018). Likewise, the sign and intensity of the relationships between biodiversity and ecological stability change from one spatial scale to another. In particular, the temporal stability of a population or an ecosystem increases with the spatial scale (Wang and Loreau 2016, Wang et al. 2017, Delsol et al. 2018).
The objective of this GDR on this subject is threefold:
(1) establish the theoretical links between the different dimensions of stability in the face of different types of disturbances;
(2) develop theoretical models to study and better understand the relationships between the stability of ecosystems and their biodiversity;
(3) link this new theory to the experiments underway in France.
THEME 2. DYNAMICS OF INTERACTION NETWORKS
Interactions between ecological entities, whether they are interactions between individuals of the same species or different species, or interactions between populations of the same species structured in space (e.g. via dispersion), are central elements in ecology. Understanding these interactions requires integrating them into a network, that is, an object that includes all of the relationships (network links) that link a collection of entities (network nodes). Because they summarize important ecological information, interaction networks are the basis of many fundamental questions in ecology, whether it is to understand the mechanisms that determine interactions between species or to predict the consequences of these interactions on the dynamics. ecological systems and their responses to various disturbances (loss of species, etc.).
During the past five years of GDR TheoMoDive, the thematic group on interaction networks has been particularly active (discussions and presentations at each annual meeting, organization of a workshop on the theme of temporal networks). This group made it possible in particular to better identify emerging themes on interaction networks and to compare work on these themes with very diverse modeling methods, such as for example stochastic block models (SBM and LBM), joint species distributions (jSDM) or pattern frequency analyses in networks. The new version of the GDR's "Network of interactions" thematic group will continue in this vein by focusing on two themes that have experienced great growth in recent years in the study of networks.
1. Understand how multiple interactions in networks determine the dynamics of ecological communities and the functioning of ecosystems
So far, the vast majority of network studies have focused on given types of interactions, studied in isolation from each other: food webs (predation interactions), host-parasite networks, mutualistic plant-pollinator networks etc. Certain interactions and groups of species have also been ignored in empirical and theoretical approaches. Thus, most of the food webs studied ignore the interactions with the abiotic components of the ecosystem, while we know that many organisms (the so-called "ecosystem engineers" species) strongly modify the abiotic properties of their environment. Integrating this diversity of interactions into the description of ecological networks has been a major issue in the field of network research over the past five years (Kéfi et al. 2015, Pilosof et al. 2017, Astegiano et al. 2017, Hutchinson et al. 2019). This multiplicity of types of interactions in networks also questions classical theoretical approaches which generally consider only one type of interaction at a time (Bastolla et al. 2005). The few existing works on this subject show that taking into account various types of interactions (trophic, mutualist, involving the abiotic environment or the recycling of nutrients) modifies our understanding of the links between complexity and stability of communities (Mougi and Kondoh 2012, Sauve et al. 2014, Sanders et al. 2014) and affect the relationship between diversity and ecosystem functioning (Miele et al. 2019). In this context, the thematic working group will aim to develop theoretical research and models with a more integrative approach to the study of networks considering the diversity of interactions in ecosystems.
2. Understand the spatial and temporal dynamics of interaction networks
Empirical studies of networks of interactions have historically focused mainly on snapshot descriptions of networks at a given point, ignoring the spatial and temporal variability of interactions between species. The last few years have seen the development of empirical studies considering the spatial and temporal variability of interaction networks, and at different scales, e.g. intra-annual variability (CaraDonna et al. 2017), interannual (Ponisio et al. 2017), or between sites (de Manincor et al. in press, Kaiser-Bunbury et al. 2017). In this context, the objective of the working group will be to bring out new theoretical models allowing us to understand the temporal dynamics of networks, over short periods of time (from one year to the next, taking into account demographic fluctuations within communities and the effects linked to metacommunities) and over longer periods of time, in particular via the evolution of interacting species in a context of planetary changes. On this aspect, the group will seek to diversify its approaches by relying both on the development of deterministic (coupled differential equations in particular), stochastic (e.g. Bayesian network type) and qualitative models (use of formal grammars to describe the set of possibilities). The group will also seek to strengthen modeling approaches on spatially structured interaction networks (meta-networks and meta-ecosystems, e.g. Gravel et al. 2016), in particular to understand how the spatial structure of networks affects their functioning and their stability or resilience.
The concepts and models linking local dynamics and regional dynamics are defined by means of the prefix “meta-”, by analogy with the first of them, metapopulation (population of populations). A metapopulation (Levins 1970) is a spatial network where each node can host a population of an organism (Hanski and Gilpin 1997). By extension, a metacommunity designates a spatial network where each node can host a community (Leibold et al. 2004). When these species are structured, either as a food web, or more generally as an ecosystem, we will also speak of a meta-network or a metaecosystem (Loreau et al. 2003, Massol et al. 2011). The "meta" approach aims to answer classic questions such as the stability or coexistence of species within communities, but also more applied questions, such as the functioning of ecosystems, the emerging topology of interaction networks. and conservation biology. The concepts of metacommunity and meta-ecosystem have produced great advances in the understanding of the structuring of ecological systems at different spatial scales and are able to generate predictions of testable patterns in natura (Leibold et al. 2004, Logue et al. 2011).
Over the past five years, the "Metacommunities" working group within the GDR TheoMoDive has regularly brought together a highly active community, particularly around new approaches and interfaces with other disciplines (e.g. use of qualitative models for predict the possible states of communities on a dynamic landscape). The scope of the "meta" approach has greatly diversified, exploring the fields of the spatial ecology of food webs, ecosystem functioning and biogeography. A spatial approach to the functioning of ecosystems based on theories and concepts related to metacommunities and meta-ecosystems has thus found its place in the landscape of scientific ecology. For example, considering the dynamics of nutrient recycling no longer at the local scale, but at the scale of a meta-ecosystem, taking into account the flows of detritus and nutrients, leads to more theories and predictions. rich on the dynamics of these systems (Gravel et al. 2010a, 2010b, Gounand et al. 2014, Marleau et al. 2015), as well as the integration of food webs in a spatially structured system (Rooney et al. 2008, Gravel et al. 2011, Calcagno et al. 2011, Pillai et al. 2011). In addition, metacommunity approaches are beginning to integrate the genetic evolution of species (Urban et al. 2008). For example, the evolution of species can affect local competitive hierarchies and therefore niche effects according to the “monopolization” hypothesis (De Meester et al. 2002), or even modulate the effects of climate change on biodiversity via an evolution of the niche of competitively interacting species (Norberg et al. 2012).
The objective of this working group for the next five years will be to coordinate and stimulate theoretical research carried out in France in the field of metacommunities and meta-ecosystems in order to improve understanding of the spatial dynamics of biodiversity, food webs, ecosystem functioning, species evolution and the effects of global change. More specifically, we plan to support two particularly significant questions in the ecology of spatialized systems.
1. The effects of processes at work in meta-ecosystems on the structure and functioning of landscapes subjected to anthropogenic disturbances
In the context of global change, ecosystem transformations and the destruction of natural habitats have progressed considerably over the past three centuries. These changes in the environment are major factors in the current biodiversity crisis and the decline in ecosystem services (Fahrig 2003, Gonzalez et al. 2009). The spatially implicit framework proposed by "meta" approaches makes it possible to address the dynamics of such changes in fragmented habitats and thus to produce methodological tools adapted to conservation issues. For example, the ecology of metapopulations has allowed the emergence of concepts of minimum size and capacity for the viability of metapopulations (Lande 1987, Ovaskainen and Hanski 2001). The objective of the working group will thus be to bring out new theoretical work extending this approach to meta-ecosystems and taking into account a spatially explicit framework, e.g. via ecosystem networks or via continuous space approaches (partial differential equations); this extension of spatial ecology to the ecosystem level will make it possible in particular to explore how the dynamics of biological communities interact with the spatial heterogeneity of nutrients, how this interaction contributes to the maintenance of biodiversity, and how it modulates the response of biodiversity to anthropogenic disturbances.
2. The effects of planetary changes (in particular, climate change) on the distribution of interacting species, at ecological and evolutionary time scales.
The combination of ecological and evolutionary forces that determine the local coexistence of species and extrinsic limits to dispersal shape the present and future distribution of species. Classical approaches (SDM) predict changes in the distribution of species based on their niche and climate projections, but neglect the dynamics of interaction with other species (e.g: predation, facilitation, co-evolution) and with the environment (ex: niche construction, adaptation). The integration of these aspects in biogeography via the meta-ecosystem approach and the incorporation of evolutionary dynamics in meta-ecosystems will make it possible to refine these predictions by identifying the main mechanisms of the extinction-colonization dynamics at the borders of the distributions of species.
THEME 4. DYNAMICS OF INTERACTIONS BETWEEN BIODIVERSITY AND SOCIETY
Historically, ecology has primarily started by studying the dynamics and functioning of populations, communities and natural ecosystems. As a result, the theoretical corpus of ecology is essentially based on ecological processes relatively independent of human activities and societies. However, it has become increasingly clear that these have a significant and globally negative impact on biodiversity (Pereira et al. 2010) and on the functioning of ecosystems and the biosphere (Vitousek et al. 1997, Cardinale 2012), in particular because of changes in land use, global warming and the exploitation of certain species. This observation has led, little by little, to the study of new ecosystems created or modified by humans (Hobbs et al. 2009), such as urban ecosystems (Barot et al. 2019) or agroecosystems (Wezel et al. 2009), just like natural ecosystems. At the same time, a current of research has developed around the concept of ecosystem services, their evaluation and their use in decision support (Costanza et al. 1997, Gomez-Baggethun et al. 2010). This research program has helped to show that human societies depend on biodiversity and the functioning of ecosystems and that it is therefore necessary to adapt our interactions with biodiversity so as not to threaten the services it provides us and to preserve the sustainability of our companies. In doing so, biodiversity and other components of ecosystems will often benefit from less impact. In other words, it is no longer just a question of studying ecological systems; it is also necessary to analyse socio-ecosystems and all the feedback mechanisms between biodiversity, physical and chemical processes and human societies. It is in part on this conceptual framework that the work of IPBES is based (Diaz et al. 2019).
Such an objective requires not only new empirical approaches describing the feedback mechanisms between human societies and biodiversity, but also and above all new developments in theory and modeling. On the one hand, predicting the dynamics resulting from these complex feedbacks cannot be done without new mathematical or computer tools. On the other hand, these tools will have to take into account mechanisms absent from models conventionally developed in ecology: for example, psychological, social, economic and political mechanisms leading to decisions and actions that influence biodiversity and ecosystems. For these reasons, several philosophers and ecologists propose to see the ecosystem as a whole, without particular polarization between humans and non-human components (Naess 1975, Gaucherel and Pommereau 2019). It requires considerable conceptual and technical development to answer many original scientific questions. For example, we can ask ourselves whether the taking into account of human societies leads to qualitatively original dynamics compared to the ecological dynamics traditionally studied, or again, what are the conditions for these feedbacks between societies and biodiversity to lead to a balance.
Opening up this field of research involves new theoretical research, often interdisciplinary, in which the GDR wishes to participate. This research includes modeling work focusing on a particular feedback mechanism (Martinet et al. 2007), possibly on a local scale, and more integrative models and on a global scale (Henderson and Loreau 2019), even qualitative approaches. inspired by theoretical computer science (Gaucherel and Pommereau 2019). They aim to analyse, understand and predict the dynamics of socio-ecosystems, but also have an important role to play in resolving the current environmental crisis, by shedding light on the range of possibilities and proposing possible solutions in line with the science of sustainability (Clark and Dickson 2003).
Ecology and evolution have long remained separate disciplines. The study of the dynamics of communities or food webs is often complex enough not to add an evolutionary component; conversely, in evolutionary biology, the dynamics of populations and communities are often ignored or simplified, in particular, in the case of theoretical models, to allow a mathematical analysis.
Recently, however, connections between ecology and evolution have multiplied. In France, in particular, this thematic merger has resulted in a visible rapprochement of communities of researchers in ecology and evolution through the change of the French Society of Ecology (sfe) into the French Society of Ecology and Evolution (sfe2) and a series of workshops, such as the Symposium `` At the border between ecology and evolution '', organized by Sfe2 and LabEx CeMEB in Montpellier.
The role of evolving ecology and the role of evolution in ecology are therefore increasingly taken into account, in line with historical models in evolutionary ecology. These models were particularly interested in feedbacks between demography and evolution (single-species models), the effect of spatial structure, but also interactions between species (competition, predation, parasitism, mutualism) and between communities (Govaert et al. 2019). Models explicitly representing interactions with the environment can also include eco-evolutionary dynamics (e.g. Estrela et al. 2019).
These models, however, are most often fairly simple and include little biodiversity (often only two or three species are modelled by a system of ordinary differential equations), although there are exceptions (Govaert et al. 2019). It is therefore high time to ask in a more concrete way the question of how evolution affects the dynamics of biodiversity. This question is particularly relevant since most of the global changes that directly threaten biodiversity and the functioning of ecosystems are also important selective forces.
It is therefore necessary to develop powerful approaches that allow us to understand the functioning of ecosystems in an evolutionary context. In their review article, Govaert et al. (2019) recommend in particular integrating more realism into eco-evolutionary models (for example, to consider the effect of plasticity or the structure of populations), but also to adopt mechanistic approaches, in particular by explicitly considering interactions between individuals (instead of phenomenological approaches). Another methodological challenge is to consider eco-evolutionary dynamics occurring on comparable time scales, instead of the temporal decoupling (useful for mathematical analysis) traditionally assumed.
The aim of the GDR is to coordinate theoretical developments, to create a network of researchers and to organize workshops on this topic. This theme can also be considered as cross-cutting within the GDR, with development issues affecting all subjects.
The coupling of theoretical models and empirical data makes it possible to strengthen our understanding of ecological processes by contrasting alternative ecological hypotheses formalized mathematically and by proposing a theoretical framework for the interpretation of ecological data. Nevertheless, although the first ecological theories relied heavily on empirical data (Kingsland 1995), a divide between theory and data has developed over the years, particularly during the second half of the last century. This has led to a specialization and a gap between theoretical ecologists, living in a world of Lotka-Volterra models and others, and specialists in field or experimental studies. Overcoming this cleavage would enrich models and theories by making them more realistic and strengthen empirical approaches by providing them with a theoretical framework with hypotheses to be tested. Faced with this observation, efforts have been made and the cleavage has been greatly reduced in recent years (Kendall 2015), which offers substantial opportunities for theorists to make more predictive theoretical models (Dietze et al. 2018) and thus increase our ability to falsify theoretical predictions. Moreover, beyond the production of hypotheses explaining the phenomena, the theory plays an important role in the clarification of the concepts and the meaning of the measured quantities, i.e., the theory makes it possible to verify that what one measures is what we want to measure (e.g Berlow et al. 2004). As part of the GDR, it is therefore natural to focus on approaches that allow better coupling between theory and data.
A promising approach is the development of methods for estimating the parameters of mechanistic models from experimental data such as time series (Ionides et al. 2006, Rosenbaum et al. 2019, Pennekamp et al. 2019). These approaches make it possible to calibrate theoretical models in order to then test their predictive power or to contrast various hypotheses on the functioning of a system, for example to explain fluctuations in the abundance of species (e.g. Kendall et al. 2005). Inference methods are used to fit systems of differential equations to time series derived from laboratory experiments or empirical data (Ellner et al. 2002, Rosenbaum and Rall 2018). The use of these methods is facilitated by the increase in the digital computing power of computers and opens up real prospects for theory-data coupling. Nevertheless, many questions remain, in particular on:
- the ability of the methods to recover the parameters of the theoretical models (i.e., identifiability);
- the type of data to be collected in the field;
- the architecture of the models to be adjusted to the data.
A particularly relevant project is the development of methods which make it possible to combine the non-linearity of ecological processes with stochasticity, which is omnipresent in ecology (e.g., Ionides et al. 2006).
As part of the study of the coexistence of competing plant species, a use of theory well connected to the data has shown both which quantities to measure in the field (Hart et al. 2018), which mechanistic models to adjust data to contrast ecological hypotheses (Adler et al. 2010), and how to reconcile the apparently contradictory results of experiments with those of in situ measurements (Tuck et al. 2018).
These few examples show that the links between theory and data apply to a set of thematic fields, hence the transversal aim of this axis in the GDR. The thematic working group devoted to this theme intends to focus its reflection on the issues of connection to empirical data, beyond the simple data-model adjustment, in particular through discussions and review articles. By bringing together ecologists of different backgrounds around the use of data in theoretical ecology, this activity of the GDR will make it possible to seek the consensus on which ecologists can agree and to explore the approaches which make it possible to strengthen the links between theory and data.
One of the recurring criticisms of the theory is about the commonly used assumption that systems are at or near equilibrium. However, the real systems observed seem to be much more dynamic (Lundberg et al. 2000, Inchausti and Halley 2003). The equilibrium hypothesis can be useful because it allows for the in-depth study of a system from a mathematical point of view, but it can also seem quite simply incompatible with field observations. The notion of stationary state, with distributions of states distributed with certain frequencies, was developed to overcome this problem, but disturbances and natural systems are not always stationary. To study systems out of equilibrium, theoretical tools exist and are being developed within the GDR Theory and Modeling of Biodiversity and the international scientific community of theoretical ecology. There are several factors that can push a system out of balance. Each has a different theoretical treatment.
1. Transient dynamics
The experiments carried out simply do not have time to reach equilibrium, hence the interest in the theory of studying transient dynamics on the way to equilibrium. Thus, the short term response of a system is very different from the long term response. As most of the theory concerns the long-term response, the development of a theory of short-term responses is particularly welcome (Arnoldi et al. 2018).
2. Fluctuations of extrinsic origin
More profoundly, systems might not tend to a steady state. When it comes to extrinsic fluctuations, one expects the existence of a state of equilibrium but which changes over time as the external conditions change, stochastically, cyclically (seasons) or gradually (change directional, such as climate change). Concepts and techniques developed by mathematicians in the theory of non-autonomous dynamics have recently been introduced in ecology (Chesson 2017) to study these phenomena.
3. Fluctuations of intrinsic origin
Fluctuations such as cycles and chaos can emerge in very simple systems. They have typically been studied in low dimensional systems (May 1976). Maintaining chaos in complex systems requires specific conditions and techniques to detect them (Roy et al. 2019).
This transversal approach raises the question of the link between theory and empirical data: what is the prevalence of ecological systems that are out of equilibrium? Is the theory still applicable, even on non-equilibrium systems? Should the theory be adapted to non-equilibrium systems? Can the intrinsic and extrinsic factors which cause this out of equilibrium dynamic be demonstrated and quantified?
To conclude, this transversal approach will aim to research and develop existing tools to study non-equilibrium systems and related issues. It will also push researchers at GDR to question the relevance of using these tools or developing new ones.
It is not common to question the laws of ecology; Yet this is exactly what this working theme is proposing within the GDR. What do we mean by that? A detour through neighbouring disciplines can enlighten us. With at least four centuries of hindsight, physics has a long tradition of perfecting laws, making it possible to explain in a reliable and universal way (by definition, proven and without exception) its phenomena (Barberousse et al. 2000, Hartmann and Frigg 2005). This is not the case with ecology and evolutionary sciences, and even with proven principles (by definition, which are not questioned) of theories (sets of principles) such as natural selection or Mendelian laws are still much debated (Mayr 2004, Morange 2017). Of course, models regularly challenge accepted principles and test their associated hypotheses (Israel 1996, Hartmann and Frigg 2005).
Biology is readily quite reductionist, ecology, more holistic, sometimes seeks universal laws (Hubbell 2001, Brown et al. 2002, Gaucherel 2013) and continually questions the reliability of the principles that it brings to light, even on the universality of the theories which could result from it. Whether or not it is believed that there are laws in ecology or not, several interesting corollary questions emerge from this question. For example, one is entitled to ask whether a law should relate to mechanisms (processes) or reasons (patterns)? Because while physical laws are generally based on mechanisms, some of them (e.g. gravitation) often resemble patterns and retain a phenomenological flavour (e.g. fractals and allometries). Some even question what the mechanisms are and what any causal explanation is worth (Israel 1996, Barberousse et al. 2000). And when ecology highlights allometric laws, it is part of this same tradition (Brown et al. 2002, Hatton et al. 2015). In addition, some laws are purely statistical (e.g. law of large numbers), far from any mechanism (Frank 2009).
And if ecologists highlighted a law in their field, would it have ecological specificities? In particular, biology and ecology all know the importance of scales and levels of organization in living things. Would an ecological law be affiliated with a particular level of organisation? Certain laws well known to ecologists attempt to explain the distribution of species, either by chance (Hubbell 2001) or by other observed regularities (Neill and Gignoux 2008, Tilman 2011). Several of them link several ecological compartments or several levels of organisation between them (Hardin 1960, MacArthur and Wilson 1963, Tilman 2011). Can these principles be considered as laws? We can guess that the status of such laws will not be similar to that of physical laws which appear, in the eyes of biologists, much more robust and universal (Putnam 1975, Gaucherel 2013). What exceptions, what variations, in these ecological laws, are we ready to accept? And further, how to manage the contradictions or the possible interactions between ecological laws?
Ecology does not have to follow the path of physics or chemistry, but it is entitled to be inspired by them. It can also be inspired by all related disciplines, from physics (Brown et al. 2002, Neill and Gignoux 2008), to economics, including linguistics (Gaucherel 2019). Several recent attempts go in this direction, and a field of research illustrates this growing interest in laws in ecology. Indeed, it would be daring to claim that ecological objects and phenomena violate physical laws, such as thermodynamics, or biological laws, such as natural selection (Harte 2002). Beyond the laws themselves, it is the history of neighbouring disciplines, particularly biology, that can prove to be a source of innovation in ecology (Morange 2017). The old debates on evolution, a field which made a noticeable irruption in ecology, show that it is interesting to seek laws where, previously, one still had only a list of processes and a classification. objects.
Still, the more pragmatic would question: What would be the use of such laws? Would they be there for the sole intellectual pleasure of theorists? Or would they have a real daily utility for managers, farmers or geneticists? Would such laws help to make predictions? Many think so, and claim that a better knowledge of the mechanisms and principles associated with central objects, such as the ecosystem or the population (Hardin 1960, Tilman 2011), would undoubtedly provide assistance to those who have to manage these objects on a daily basis. still poorly understood (Gaucherel 2019). Even if it turned out that ecology does not have laws, reflecting on this question would contribute as much to basic ecology as it does to applied ecology.
As part of this transversal axis we will interact with philosophers of science and we want to design a first list of general laws by doing an online survey.
Complementarity with the GDR Statistical Ecology
The GDR Statistical Ecology aims to develop and disseminate statistical methodologies adapted to the various fields of ecology, including in particular the algorithmic aspects of the fit to data (maximum likelihood, Markov Chain Monte Carlo), data management (data citizen, ...) and conceptual of applied statistics (e.g, frequentist vs Bayesian philosophy). The GDR Theory and Modeling of Biodiversity addresses questions upstream and downstream of the use of these methodologies: which data to seize for which questions? Which statistical models also make theoretical sense / how to theoretically interpret their parameters? Are there classical empirical analyses that the theory can prove are uninterpretable? How to reduce the complexity of theoretical models to fit them to necessarily limited data? Are there ecological questions of importance to the theory that currently escape empirical analysis?
The Scientific Council of GDR TheoMoDive is composed of:
Sébastien Barot - Institut d’Écologie et des Sciences de l’Environnement, Paris (UMR 7618)
Jérôme Chave - Laboratoire Évolution et Diversité Biologique, Toulouse (UMR 5174)
Claire de Mazancourt - Station d’Écologie Théorique et Expérimentale, Moulis (UMR 5321)
The GDR TheoMoDive offers, within the means available, grants for doctoral students and postdoctoral researchers who wish to do a research stay in one of the participating laboratories.
a brief description of the objectives of the proposed stay
a brief justification of the planned expenditure.
These requests are then examined by the Scientific Council of the GDR.
Annual meetings and workshops
The annual meetings make it possible to ensure the continuity of the reflections and work carried out within the GDR, to synthesize them and to identify new avenues of research. Their objective is less to draw up an exhaustive assessment of the work carried out than to stimulate common reflection.
As a result, they focus on new advances made, new developments underway and new projects in the pipeline, as well as on cross-cutting issues across GDR.
The GDR supports, within the means available, smaller workshops to advance reflections and research on the various research themes of the GDR.
Workshops at the interface of several themes or allowing new themes to emerge are also encouraged.
a description of the objectives of the workshop
a list of potential participants
a provisional program
These proposals are then examined by the Scientific Council of GDR.
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