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The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams, and both terminology and content vary widely. Here we argue that greater consistency in conceptual model diagram development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ecological risk assessments.

The acceptance and usefulness of simulation models are often limited by the efficiency, transparency, reproducibility, and reliability of the modelling process. We address these issues by suggesting that modellers (1) “trace” the iterative modelling process by keeping a modelling notebook corresponding to the laboratory notebooks used by empirical researchers, (2) use a standardized notebook structure and terminology based on the existing TRACE documentation framework, and (3) use their notebooks to compile TRACE documents that supplement publications and reports. These practices have benefits for model developers, users, and stakeholders: improved and efficient model design, analysis, testing, and application; increased model acceptance and reuse; and replicability and reproducibility of the model and the simulation experiments. Using TRACE terminology and structure in modelling notebooks facilitates production of TRACE documents. We explain the rationale of TRACE, provide example TRACE documents, and suggest strategies for keeping “TRACE Modelling Notebooks.”

Ecosystems are exposed to multiple stressors which can compromise functioning and service delivery. These stressors often co-occur and interact in different ways which are not yet fully understood. Here, we applied a population model representing a freshwater amphipod feeding on leaf litter in forested streams. We simulated impacts of hypothetical stressors, individually and in pairwise combinations that target the individuals’ feeding, maintenance, growth and reproduction. Impacts were quantified by examining responses at three levels of biological organisation: individual-level body sizes and cumulative reproduction, population-level abundance and biomass and ecosystem-level leaf litter decomposition. Interactive effects of multiple stressors at the individual level were mostly antagonistic, that is, less negative than expected. Most population- and ecosystem-level responses to multiple stressors were stronger than expected from an additive model, that is, synergistic. Our results suggest that across levels of biological organisation responses to multiple stressors are rarely only additive. We suggest methods for efficiently quantifying impacts of multiple stressors at different levels of biological organisation.

Website: https://www6.inra.fr/wheatamix The present document details how the Wheatamix consortium, inspired by ecological experiments exploring relationships between plant biodiversity and ecosystem functioning (e.g. the Jena experiment Weisser et al. 2017), selected bread wheat (Triticum aestivum L.) lines, phenotyped them across a range of functional traits and used this information to set up an experimental design able to unravel the effects of variety number and of the functional diversity and identity within variety mixtures for evaluating the impact of intraspecific crop diversity on a range of ecosystem services. Wheat line selection The Wheatamix project investigates the potential benefits of variety mixtures in the Paris basin wheat supply chain, and therefore focuses on varieties and lines adapted to the local climate. A consensus list of 57 wheat lines (Table 1) was thus settled on these grounds and to meet the expectations of agronomists, geneticists, phytopathologists and ecophysiologists of the group. This list is composed of i) 32 elite bread wheat varieties registered in the French catalogue, selected for their high yields under conventional farming, ii) 5 modern varieties bred for organic farming (OF), iii) 10 landraces resulting from farmers' mass-selection, cultivated in France in the early 1900es, and iv) 11 lines from an INRA-MAGIC multiparental and highly recombinant population (Thepot et al., 2015), adapted to Northern France. Due to the heterogeneity of information available for each variety and line, various criteria were used for this selection. The 32 elite bread wheat varieties were chosen on the basis of their wide use in the Paris Basin, and to ensure representativeness of the diversity for earliness, disease resistance or bread-making quality, using the available information in the variety

Human practices in managed landscapes may often adversely affect aquatic biota, such as aquatic insects. Dispersal is often the limiting factor for successful re-colonization and recovery of stressed habitats. Therefore, in this study, we evaluated the effects of landscape permeability, assuming a combination of riparian vegetation (edge permeability) and other vegetation (landscape matrix permeability), and distance between waterbodies on the colonization and recovery potential of weakly flying insects. For this purpose, we developed two models, a movement and a population model of the non-biting midge, Chironomus riparius, an aquatic insect with weak flying abilities. With the movement model we predicted the outcome of dispersal in a landscape with several linear water bodies (ditches) under different assumptions regarding landscape-dependent movement. Output from the movement model constituted the probabilities of encountering another ditch and of staying in the natal ditch or perishing in the landscape matrix, and was used in the second model. With this individual-based model of midge populations, we assessed the implications for population persistence and for recovery potential after an extreme stress event. We showed that a combination of landscape attributes from the movement model determines the fate of dispersing individuals and, once extrapolated to the population level, has a big impact on the persistence and recovery of populations. Population persistence benefited from low edge permeability as it reduced the dispersal mortality which was the main factor determining population persistence and viability. However, population recovery benefited from higher edge permeability, but this was conditional on the low effective distance that ensured fewer losses in the landscape matrix. We discuss these findings with respect to possible landscape management scenarios., Human practices in managed landscapes may often adversely affect aquatic biota, such as aquatic insects. Dispersal is often the limiting factor for successful re-colonization and recovery of stressed habitats. Therefore, in this study, we evaluated the effects of landscape permeability, assuming a combination of riparian vegetation (edge permeability) and other vegetation (landscape matrix permeability), and distance between waterbodies on the colonization and recovery potential of weakly flying insects. For this purpose, we developed two models, a movement and a population model of the non-biting midge, Chironomus riparius, an aquatic insect with weak flying abilities. With the movement model we predicted the outcome of dispersal in a landscape with several linear water bodies (ditches) under different assumptions regarding landscape-dependent movement. Output from the movement model constituted the probabilities of encountering another ditch and of staying in the natal ditch or perishing in the landscape matrix, and was used in the second model. With this individual-based model of midge populations, we assessed the implications for population persistence and for recovery potential after an extreme stress event. We showed that a combination of landscape attributes from the movement model determines the fate of dispersing individuals and, once extrapolated to the population level, has a big impact on the persistence and recovery of populations. Population persistence benefited from low edge permeability as it reduced the dispersal mortality which was the main factor determining population persistence and viability. However, population recovery benefited from higher edge permeability, but this was conditional on the low effective distance that ensured fewer losses in the landscape matrix. We discuss these findings with respect to possible landscape management scenarios.

Nile perch (Lates niloticus) suddenly invaded Lake Victoria between 1979 and 1987, 25 years after its introduction in the Ugandan side of the lake. Nile perch then replaced the native fish diversity and irreversibly altered the ecosystem and its role to lakeshore societies: it is now a prised export product that supports millions of livelihoods. The delay in the Nile perch boom led to a hunt for triggers of the sudden boom and generated several hypotheses regarding its growth at low abundances – all hypotheses having important implications for the management of Nile perch stocks. We use logistic growth as a parsimonious null model to predict when the Nile perch invasion should have been expected, given its growth rate, initial stock size and introduction year. We find the first exponential growth phase can explain the timing of the perch boom at the scale of Lake Victoria, suggesting that complex mechanisms are not necessary to explain the Nile perch invasion or its timing. However, the boom started in Kenya before Uganda, indicating perhaps that Allee effects act at smaller scales than that of the whole Lake. The Nile perch invasion of other lakes indicates that habitat differences may also have an effect on invasion success. Our results suggest there is probably no single management strategy applicable to the whole lake that would lead to both efficient and sustainable exploitation of its resources., Nile perch (Lates niloticus) suddenly invaded Lake Victoria between 1979 and 1987, 25 years after its introduction in the Ugandan side of the lake. Nile perch then replaced the native fish diversity and irreversibly altered the ecosystem and its role to lakeshore societies: it is now a prised export product that supports millions of livelihoods. The delay in the Nile perch boom led to a hunt for triggers of the sudden boom and generated several hypotheses regarding its growth at low abundances – all hypotheses having important implications for the management of Nile perch stocks. We use logistic growth as a parsimonious null model to predict when the Nile perch invasion should have been expected, given its growth rate, initial stock size and introduction year. We find the first exponential growth phase can explain the timing of the perch boom at the scale of Lake Victoria, suggesting that complex mechanisms are not necessary to explain the Nile perch invasion or its timing. However, the boom started in Kenya before Uganda, indicating perhaps that Allee effects act at smaller scales than that of the whole Lake. The Nile perch invasion of other lakes indicates that habitat differences may also have an effect on invasion success. Our results suggest there is probably no single management strategy applicable to the whole lake that would lead to both efficient and sustainable exploitation of its resources.

In agroecosystems, organisms may regularly be exposed to anthropogenic stressors, e.g. pesticides. Species' sensitivity to stress depends on toxicity, life-history, and landscape structure. We developed an individual-based model of an isopod, Asellus aquaticus, to explore how timing of stress events affects population dynamics in a seasonal environment. Furthermore, we tested the relevance of habitat connectivity and spatial distribution of stress for the recovery of a local and total population. The simulation results indicated that population recovery is mainly driven by reproductive periods. Furthermore, high habitat connectivity led to faster recovery both for local and total populations. However, effects of landscape structure disappeared for homogeneously stressed populations, where local survivors increased recovery rate. Finally, local populations recovered faster, implying that assessing recovery in the field needs careful consideration of spatial scale for sampling. We emphasize the need for a coherent definition of recovery for more relevant ecosystem risk assessment and management., In agroecosystems, organisms may regularly be exposed to anthropogenic stressors, e.g. pesticides. Species' sensitivity to stress depends on toxicity, life-history, and landscape structure. We developed an individual-based model of an isopod, Asellus aquaticus, to explore how timing of stress events affects population dynamics in a seasonal environment. Furthermore, we tested the relevance of habitat connectivity and spatial distribution of stress for the recovery of a local and total population. The simulation results indicated that population recovery is mainly driven by reproductive periods. Furthermore, high habitat connectivity led to faster recovery both for local and total populations. However, effects of landscape structure disappeared for homogeneously stressed populations, where local survivors increased recovery rate. Finally, local populations recovered faster, implying that assessing recovery in the field needs careful consideration of spatial scale for sampling. We emphasize the need for a coherent definition of recovery for more relevant ecosystem risk assessment and management.

Agricultural practices are essential for sustaining the human population, but at the same time they can directly disrupt ecosystem functioning. Ecological risk assessment (ERA) aims to estimate possible adverse effects of human activities on ecosystems and their parts. Current ERA practices, however, incorporate very little ecology and base the risk estimates on the results of standard tests with several standard species. The main obstacles for a more ecologically relevant ERA are the lack of clear protection goals and the inherent complexity of ecosystems that is hard to approach empirically. In this paper, we argue that the ecosystem services framework offers an opportunity to define clear and ecologically relevant protection goals. At the same time, ecological models provide the tools to address ecological complexity to the degree needed to link measurement endpoints and ecosystem services, and to quantify service provision and possible adverse effects from human activities. We focus on the ecosystem services relevant for agroecosystem functioning, including pollination, biocontrol and eutrophication effects and present modeling studies relevant for quantification of each of the services. The challenges of the ecosystem services approach are discussed as well as the limitations of ecological models in the context of ERA. A broad, multi-stakeholder dialog is necessary to aid the definition of protection goals in terms of services delivered by ecosystems and their parts. The need to capture spatio-temporal dynamics and possible interactions among service providers pose challenges for ecological models as a basis for decision making. However, we argue that both fields are advancing quickly and can prove very valuable in achieving more ecologically relevant ERA.

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