Ecological Modelling

Should what is left of nature be contained in a Single Large or Several Small (SLoSS) areas? This question of what would minimize the impact severity of habitat destruction on biodiversity loss is much debated, mainly because studies generally focus on different spatial and temporal scales. Using a semi-spatially explicit, (near-)neutral, individual-based model, we investigate the effects of fragmentation on biodiversity loss at two spatial (landscape-versus subcommunity level) and two temporal scales (static versus dynamic effects). Our results show that the role of spatial configuration of habitat destruction depends on when and at what scale we measure biodiversity loss. When considering the more realistic assumption that species differ in dispersal capacity, differences between spatial configurations are likely to be amplified. Our results indicate that the spatial configuration of habitat loss needs to be considered when evaluating the risks of further habitat destruction.

Fires are generally considered to promote biodiversity, although the exact relationship is unclear, because it can be affected by several factors, including fire regime and ecosystem type. Given the ongoing global change, a better understanding of this connection is needed to assess the extent to which projected increases in fire frequency may affect current biodiversity trends. A major challenge lies in vegetation-fire feedback, which often mediates changes in fire regimes. To shed light on the role of fires in promoting or limiting biodiversity, we studied the compositional and functional diversity of simulated plant communities along a gradient of fire frequencies. We extended an existing model to include a large number of species. The model reproduces plant successional dynamics and is parameterized to represent Boreal and Mediterranean communi-ties. Fire events are stochastic, with frequencies that depend on community flammability, and plants have different fire responses, thus creating a vegetation-fire feedback. For both ecosys-tems, we found that fires generally had a positive effect on both compositional and functional diversity. Furthermore, in most cases, both peaked at intermediate fire frequencies. Interestingly, compositional and functional diversity were correlated but did not reach their maximum values in the same communities. This seemingly underlines that a certain degree of functional similarity may be necessary to achieve maximum species richness. These results stem from the vegetation-fire feedback, highlighting its importance for predicting ecosystem responses to global change, including biodiversity losses and wildfire regime shifts.

Conservation and ethical consideration for animal welfare in the wild appear to be synergetic because they both care for non-human animals. However, many practices such as culling seem to achieve conservation purposes but at the cost of producing a lot of wild-animal suffering, antagonizing conservationists and animal rights advocates. To explore this tension, we model the suffering of animals in wild ecosystems by resorting to classical population dynamics equations and using death rates as a metric of suffering. Our results show that, depending on the structure and parameters of the ecosystem, animal rights advocates and conservationists can have either opposing or compatible interests, where conserving species can go hand in hand with reducing the overall suffering. These models contribute to the concrete question of how to cope with suffering in the wild and may help ecosystem managers who are regularly confronted with interventions in the wild.

Larval dispersal and connectivity are key processes that drive marine metapopulation dynamics, and therefore should be well characterized when designing effective management strategies. While temperature and food availability can structure marine species connectivity patterns, their relative contribution has not been thoroughly investigated in highly fragmented archipelagos. We used biophysical modeling of larval dispersal to explore the connectivity patterns of species with complex life-cycles across French Polynesia (FP), a territory formed by more than a hundred small, geographically isolated islands covering an area as large as Europe. We first simulated ten years of larval dispersal to investigate the spatial and temporal (seasonal and interannual) variability in larval dispersal pathways for different hypothetical species exhibiting a range of Larval Precompetency Period (LPP) values. Then, using the black-lip pearl oyster (Pinctada margaritifera) as a model species, we accounted for variability in the LPP induced by temperature and food availability, as derived from a Dynamic Energy Budget (DEB) model. The model showed that food availability and meso-scale turbulence (eddies) in the Marquesas jointly constrained larval dispersal, reducing its potential connectivity with other archipelagos in FP. However, accounting for food and temperature effects on larval development, barely changed the connectivity pattern at regional scale due to the remoteness of this archipelago. The DEB simulations further revealed seasonal and interannual variability in connectivity driven by environmental conditions. Our results highlight the importance of considering temperature and food in biophysical models to adequately capture dispersal, connectivity and to identify appropriate management units at the regional scale.

How a particular threat influences extinction risk may depend on biological traits. Empirical studies relating threats and traits are needed, but data are scarce, making simulations useful. We implemented an eco-evolutionary model to analyse how five threat types influence the extinction risk of virtual organisms differing in body size, maturity age, fecundity, and dispersal ability. Results show that direct killing mostly affected slow-living and low dispersal organisms. Habitat loss and fragmentation both affected larger and less fecund organisms, but drove contrasting responses according to dispersal ability. Habitat degradation and the introduction of invasive competitors had similar effects, mostly affecting large, fast-living, and highly fecund organisms. Many of the reported results confirm previous studies, while others were never tested, creating new hypotheses for future empirical work. Statement of authorshipFC, LC and PC designed the study, FC implemented the model and ran the statistical analyses. FC and PC wrote the first draft, and all authors contributed substantially to further revisions.

On a global scale, fisheries harvest an estimated 96 million tonnes of fish biomass annually, making them one of the most important drivers of marine ecosystem biodiversity. Yet little is known about the interactions between fisheries and the dynamics of complex food webs in which the harvested species are embedded. We have developed a synthetic model that combines resource economics with complex food webs to examine the direct effects of fishing on exploited species and the indirect impact on other species in the same community. Our model analyses show that the sensitivity of the targeted species increases with its trophic level and decreases with its local interaction complexity (i.e. its number of interactions with prey, predators, and competitors). In addition, we also document a strikingly positive effect of community species richness on the resilience of the harvested species to this disturbance. The indirect effects on other species show specific patterns of spreading across trophic modules that differ systematically from how other disturbances spread across ecological networks. While these results call for further research on how human resource exploitation in general and fishery in particular affect ecological dynamics and biodiversity in naturally complex systems, they also allow for some cautious conclusions. Taken together, our results suggest that the sustainability concerning fishery yield and ecosystem integrity can be maximised by focusing the harvest on low trophic level species with a high local interaction complexity in high biodiversity ecosystems. In this sense, our complex network approach offers a promising avenue for integrating the necessities of generating economic revenue with the protection of natural biodiversity.

Natural Protected Areas (NPAs) are the main biodiversity conservation strategy in Mexico. Generally, NPAs are established on the territories of indigenous and rural groups driving important changes in their local resource management practices. In this paper we study the case of Otoch Maax Yetel Kooh, an NPA in the Yucatan Peninsula, Mexico, that has been studied in a multidisciplinary way for more than twenty years. This reserve and its buffer zone is homeland to Yucatec Mayan communities that until recently used to manage their resources following a multiple use strategy (MUS), which involves local agricultural practices and has been proposed as resilience-enhancing mechanism. However, due to the restrictions imposed by the decree of the reserve and the growth of tourism in the region, some of these communities have started to abandon the MUS and specialize on tourism-related activities. We build a dynamical computational model to explore the effects of some of these changes on the capacity of this NPA to conserve the biodiversity and on the resilience of households to some frequent disturbances in the region. The model, through the incorporation of agent-based and boolean network modelling, explores the interaction between the forest, the monkey population and some productive activities done by the households (milpa agriculture, ecotourism, agriculture, charcoal production). We calibrated the model, explored its sensibility, compared it with empirical data and simulated different management scenarios. Our results suggest that those management strategies that do not exclude traditional activities may be compatible with conservation objectives, supporting previous studies. Also, our results support the hypothesis that the MUS, throughout a balanced integration of traditional and alternative activities, is a mechanism to enhance household resilience in terms of income and food availability, as it reduces variability and increases the resistance to some disturbances. Our study, in addition to highlighting the importance of local management practices for resilience, also illustrates how computational modeling and systems perspective are effective means of integrating and synthesizing information from different sources.

Understanding the conditions that favor the persistence of metapopulations inhabiting riverine landscapes is a critical challenge in guiding conservation and restoration efforts aimed at preserving the biodiversity and ecological integrity of freshwater environments. In this work, we propose a modeling framework to investigate the transient persistence of fluvial metapopulations, i.e., the temporary occupation of riverscape patches by a metapopulation that is expected to go extinct in the long run. The theoretical foundation of our approach is rooted in the concept of ecological reactivity, which provides an effective complement to asymptotic stability analysis for studying the short-term response of ecological systems to impulsive perturbations to otherwise stable equilibria. Our results indicate that, under ecohydrological conditions conducive to a reactive metapopulation extinction equilibrium, even a metapopulation that is asymptotically bound to extinction can colonize parts of the riverscape for non-negligible periods of time. We find that the temporal scales associated with these transient phenomena, in the presence of repeated positive perturbations of the extinction equilibirum, may allow for reactive pseudo-persistence, i.e., an arbitrarily long delay in the eventual extinction of the metapopulation that may occur well below the deterministic extinction threshold. By identifying the ecohydrological drivers of reactive metapopulation persistence, as well as the riverscape patches that contributes the most to transient metapopulation dynamics over different temporal scales, our analysis may provide valuable suggestions for the spatial prioritization of conservation and restoration efforts.

Biological invasions are among the major drivers of biodiversity and are increasing worldwide. Among the invasive species, mammals have a particularly profound impact on native ecosystems. As primary decomposers of mammalian feces, dung beetles are critical in ecosystem functioning, and their community structure is closely linked to their services. However, the introduction of invasive mammals threatens these beetles and potentially disrupts their ecosystem services. Therefore, it is necessary to understand the resulting changes in communities. We developed a novel population dynamics model focusing on the interactions among mammals, feces, and dung beetles. Our results indicate that such invasions increase the risk of extinction of specialist dung beetles that cannot utilize the feces of invasive mammals. The risk of extinction is particularly high when generalist dung beetles show a preference for native feces, leading to intensified interspecific competition for resources. Additionally, the extinction risk of specialist dung beetles increases when invasive mammals display irruptive population dynamics. In conclusion, our findings demonstrated that non-native mammalian invasions disrupt the coexistence of native dung beetle communities, potentially leading to losses in biodiversity and ecosystem function. These risks should be considered in future empirical studies to evaluate the impact of invasive mammals on dung beetle communities.

O_LIThe success of species invasions depends on multiple factors acting over the four invasion stages transport, colonisation, establishment, and landscape spread. Each of these stages is influenced simultaneously by particular species traits and abiotic factors. While the importance of many of these determinants has already been investigated in relative isolation, they are rarely studied in combination and even then mostly ignore the final phase, i.e., landscape spread. C_LIO_LIHere we address this shortcoming by exploring the effect of both species traits and abiotic factors on the success of invasions using an individual-based mechanistic model, and relate those factors to the stages of invasion. This approach enables us to explicitly control abiotic factors (temperature as surrogate for productivity, disturbance and propagule pressure) as well as to monitor whole-community trait distributions of environmental adaptation, mass and dispersal abilities. We simulated introductions of plant individuals to an oceanic island to assess which abiotic factors and species traits contribute to invasion success. C_LIO_LIWe found that the most influential factors were higher propagule pressure and a particular set of traits. This invasion trait syndrome was characterized by a relative similarity in functional traits of invasive species to natives, while invasives had on average higher environmental tolerances, higher body mass and increased dispersal abilities, i.e., were more generalist and dispersive. C_LIO_LIOur results highlight the importance in management practice of reducing the import of alien species, especially from similar habitats. C_LI

We investigate the impact of disturbances on forest ecosystems by examining transient population dynamics in a controlled experiment carried out in a tropical rainforest. We first model the mean species abundance with a simple consumer-resource model, which is then extended into two multi-species frameworks for community dynamics: a neutral model, which emphasises the ability of any species to recover independently of the others; and a non-neutral one, where species interactions play an important role in reconstructing ecosystems structure and patterns. The results indicate that, while both frameworks accurately describe correlation functions and mean-variance relations, the non-neutral model more effectively captures community structure as revealed by an evenness indicator. This suggests that interspecific interactions significantly influence the ecosystems ability to respond to disturbances, providing deeper insights into the recovery dynamics of forest ecosystems.

In the last decade, marine ecosystem models have been increasingly used to project interspecific biodiversity under various global change and management scenarios, considering ecological dynamics only. However, fish populations may also adapt to climate and fishing pressures, via evolutionary changes, leading to modifications in their life-history that could either mitigate or worsen, or even make irreversible, the impacts of these pressures. Building on the multispecies individual-based model Bioen-OSMOSE, an eco-evolutionary fish community model, Ev-Osmose, has been developed to account for evolutionary dynamics together with physiological and ecological dynamics in fish diversity projections. A gametic inheritance module describing the individuals genetic structure has been implemented. The genetic structure is defined by finite numbers of loci and alleles per locus that determine the genetic variability of growth, maturation and reproductive effort. Climate change and fishing activities will generate selection pressures on fish life-history traits that will respond through microevolution. This paper is an overview of the Ev-OSMOSE model. To illustrate the ability of the Ev-OSMOSE model to represent realistic fish community dynamics, genotypic and phenotypic traits mean and variance and consistent evolutionary patterns, we applied the model to the North Sea ecosystem. The simulated outputs are confronted to observed data of commercial catch, maturity ogives and length at age and to estimates of biomass for each modeled species. In addition to the evaluation of their mean value, the emerging traits variability is confronted to length-at-age and maturity data. To ensure the consistency of genetic inheritance and the resulting evolutionary patterns, we assessed the transmission of traits genotypic value across cohorts. Overall, the state of the modelled ecosystem was convincing at all these different biological levels. These results open perspectives for using Ev-OSMOSE in different marine regions to project the eco-evolutionary impact of various global change and management scenarios on different biological levels.

In the framework of resource-competition models, it has been argued that the number of species stably coexisting in an ecosystem cannot exceed the number of shared resources. However, plankton seems to be an exception of this so-called "competitive-exclusion principle". In planktic ecosystems, a large number of different species stably coexist in an environment with limited resources. This contradiction between theoretical expectations and empirical observations is often referred to as "The Paradox of the Plankton". This project aims to investigate biophysical models that can account for the large biodiversity observed in real ecosystems in order to resolve this paradox. A model is proposed that combines classical resource competition models, metabolic trade-offs and stochastic ecosystem assembly. Simulations of the model match empirical observations, while relaxing some unrealistic assumptions from previous models. Paradox: from Greek para: "distinct from", and doxa: opinion. Sainsbury (1995) defines a paradox as "an apparently unacceptable conclusion derived by apparently acceptable reasoning from apparently acceptable premises". Paradoxes are useful research tools as they suggest logical inconsistencies. In order to spot the flaw, the validity of all the premises has to be carefully assessed. Plankton: refers to the collection of organisms that spend part or all of their lives in suspension in water (Reynolds 2006). Plankton, or plankters, are "organisms that have velocities significantly smaller than oceanic currents and thus are considered to travel with the water parcel they occupy" (Lombard et al. 2019). Phytoplankters refer to the members of the plankton that perform photosynthesis.

Stability is a key attribute of complex food webs that has been for a long time in the focus of studies. It remained an intriguing question how large and complex food webs are persisting if smaller and simple ones tend to be more stable at least from a mathematic perspective. Presuming that with the increasing size of food webs their stability also grows, we analyzed the relationship between number of nodes in food webs and their stability based on 450 food webs ranging from a few to 200 nodes. Our results show that stability increases non-linearly with food web size based both on return times after disturbance and on robustness calculated from secondary extinction rates of higher trophic levels. As a methodologic novelty we accounted for food web generation time in the return time calculation process. Our results contribute to the explanation of large and complex food web persistence: in spite of the fact that with increasing species number the stability of food webs decreases at small node numbers, there is a constant stability increase over a large interval of increasing food web size. Therefore, in food web stability studies, we stress the use of food web generation times.Competing Interest StatementThe authors have declared no competing interest.View Full Text

The functioning of plant-pollinator mutualistic networks is crucial for ecosystem service provisioning and biodiversity maintenance. However, multiple drivers of global change are causing an alarming decline of wild pollinators abundance and richness. We propose an ecological, process-based mathematical model describing the dynamics of pollinators and plants, properly mediated by reward resources. Our model explicitly accounts for the main interactions of both facilitative and competitive nature that occur both within and between the two guilds. We apply our model to a broad set of real communities in fragmented landscapes to investigate the mechanisms that link the architecture of the interaction networks, the pollinators temporal persistence and abundance at the community level, and their rarity at the landscape level. Our results suggest that few generalist pollinators form a core of abundant, persistent and widely distributed species, while a lower number of mutualistic partners is generally associated with low abundance, low persistence and high turnover between patches. Specialists, however, are crucial to maintaining high levels of biodiversity within the community. This finding highlights the importance of ecological connectivity, through which local extinctions can be counter-balanced by recolonizations. Our analysis shows how a mechanistic model accounting for the structure of plant-pollinator networks can serve as a tool to investigate important ecological mechanisms driving community composition, dynamics and the resulting species distribution patterns.

The biodiversity and ecosystem functioning (BEF) relationship is expected to be scale-dependent. The autocorrelation of environmental heterogeneity is hypothesized to explain this scale dependence because it influences how quickly biodiversity accumulates over space or time. However, this link has yet to be demonstrated in a formal model. Here we use a Lotka-Volterra competition model to simulate community dynamics when environmental conditions vary across either space or time. Species differ in their optimal environmental conditions, which results in turnover in community composition. We vary biodiversity by modelling communities with different sized regional species pools and ask how the amount of biomass per unit area depends on the number of species present, and the spatial or temporal scale at which it is measured. We find that more biodiversity is required to maintain functioning at larger temporal and spatial scales. The number of species required increases quickly when environmental autocorrelation is low, and slowly when autocorrelation is high. Both spatial and temporal environmental heterogeneity led to scale dependence in BEF, but autocorrelation had larger impacts when environmental change was temporal. These findings show how the biodiversity required to maintain functioning is expected to increase over space and time.

Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment.

The occurrence of wolf populations in human-dominated landscapes is challenging worldwide because of conflicts with human activities. Modeling is an important tool to predict wolf dynamics and expansion, and help in decision making concerning management and conservation. However, some individual behaviors and pack dynamics of the wolf life cycle are still unclear to ecologists. Here we present an individual-based model (IBM) to project wolf populations while exploring the lesser-known processes of the wolf life cycle. IBMs are bottom-up models that simulate the fate of individuals interacting with each other, with population-level properties emerging from the individual-level simulations. IBMs are particularly adapted to represent social species such as the wolf that exhibits complex individual interactions. Our IBM predicts wolf demography including fine-scale individual behavior and pack dynamics based on up-to-date scientific literature. We explore four processes of the wolf life cycle whose consequences on population dynamics are still poorly understood: the pack dissolution following the loss of a breeder, the adoption of young dispersers by packs, the establishment of new packs through budding, and the different types of breeder replacement. While running different versions of the IBM to explore these processes, we also illustrate the modularity and flexibility of our model, an asset to model wolf populations experiencing different ecological and demographic conditions. The different parameterization of pack dissolution, territory establishment by budding, and breeder replacement processes influence the most the projections of wolf populations. As such, these processes require further field investigation to be better understood. The adoption process has a lesser impact on model predictions. Being coded in R to facilitate its understanding, we expect that our model will be used and further adapted by ecologists for their own specific applications.

Understanding how populations respond to variability in environmental conditions and interspecific interactions is one of the biggest challenges of population ecology, particularly in the context of global change. Although several studies have investigated population responses to climate change, very few have explicitly integrated interspecific relationships when studying these responses. Here, we aim to understand the combined effects of inter- and intraspecific interactions and environmental conditions on the demographic parameters of a prey-predator system of three sympatric seabird populations breeding in Antarctica: the south polar skua (Catharacta maccormicki), and its two main preys during the breeding season, the Adelie penguin (Pygoscelis adeliae) and the emperor penguin (Aptenodytes forsteri). We built a two-species integrated population model (IPM) with 31 years of capture-recapture and count data, and provided a framework that allows estimating demographic parameters and abundance of a predator-prey system in a context where capture-recapture data are not available for one species. Our results showed that predator-prey interactions and local environmental conditions affect differently south polar skuas depending on their breeding state of the previous year. Concerning prey-predator relationships, the number of Adelie penguin breeding pairs showed a positive effect on south polar skua survival and breeding probability, and the number of emperor penguin dead chicks showed a positive effect on the breeding success of south polar skuas. In contrast, there was no evidence for an effect of the number of south polar skuas on the demography of Adelie penguins. We also found an important impact of sea ice conditions on both the dynamics of south polar skuas and Adelie penguins. Our results suggest that this prey-predator system is mostly driven by bottom-up processes and local environmental conditions.

Scatter-hoarding decisions by rodents are key for the long-term maintenance of scattered tree populations. Decisions are determined by seed value, competition and predation risk, so that they can be influenced by the integrity of the biological system composed by trees, rodents, ungulate competitors, and rodent predators. We manipulate and model the oak-mice interaction in a Spanish dehesa, an anthropogenic savanna system suffering chronic tree regeneration failure, and quantify the joint effect of intrinsic and extrinsic factors on acorn dispersal effectiveness. First, we conducted a large-scale cafeteria field experiment, where we modified ungulate presence and predation risk, and followed mouse scatter-hoarding decisions under contrasting levels of moonlight and acorn availability. Then, we estimated the net effects of competition and risk by means of transition probability models that simulated mouse scatter-hoarding decisions according to the environmental context. Our results show that suboptimal conditions for mice balance the interaction towards the mutualism as they force mice to forage less efficiently. Under stressful conditions (predation risks and presence of ungulates), lack of antipredatory cover around dehesa trees limited transportation of acorns, but also precluded mice activities outside tree canopies. As a result, post-dispersal predation rates were reduced and large acorns had a higher probability to survive. Our work shows that inter-specific interactions preventing efficient foraging by scatter-hoarders benefitted seed dispersal. Therefore, the maintenance of the full set of producers, consumers, dispersers and predators in ecosystems is key for promoting seed dispersal effectiveness in conditional mutualisms.