Amelie Schmolke

Ecological models supporting environmental decision making: a strategy for the future

Ecological models are important for environmental decision support because they allow the consequences of alternative policies and management scenarios to be explored. However, current modeling practice is unsatisfactory. A literature review shows that the elements of good modeling practice have long been identified but are widely ignored. The reasons for this might include lack of involvement of decision makers, lack of incentives for modelers to follow good practice, and the use of inconsistent terminologies. As a strategy for the future, we propose a standard format for documenting models and their analyses: transparent and comprehensive ecological modeling (TRACE) documentation. This standard format will disclose all parts of the modeling process to scrutiny and make modeling itself more efficient and coherent.

Ecological models and pesticide risk assessment: Current modeling practice

Ecological risk assessments of pesticides usually focus on risk at the level of individuals, and are carried out by comparing exposure and toxicological endpoints. However, in most cases the protection goal is populations rather than individuals. On the population level, effects of pesticides depend not only on exposure and toxicity, but also on factors such as life history characteristics, population structure, timing of application, presence of refuges in time and space, and landscape structure. Ecological models can integrate such factors and have the potential to become important tools for the prediction of population-level effects of exposure to pesticides, thus allowing extrapolations, for example, from laboratory to field. Indeed, a broad range of ecological models have been applied to chemical risk assessment in the scientific literature, but so far such models have only rarely been used to support regulatory risk assessments of pesticides. To better understand the reasons for this situation, the current modeling practice in this field was assessed in the present study. The scientific literature was searched for relevant models and assessed according to nine characteristics: model type, model complexity, toxicity measure, exposure pattern, other factors, taxonomic group, risk assessment endpoint, parameterization, and model evaluation. The present study found that, although most models were of a high scientific standard, many of them would need modification before they are suitable for regulatory risk assessments. The main shortcomings of currently available models in the context of regulatory pesticide risk assessments were identified. When ecological models are applied to regulatory risk assessments, we recommend reviewing these models according to the nine characteristics evaluated here.

The role of ecological models in linking ecological risk assessment to ecosystem services in agroecosystems

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.

Benefits of Dispersed Central‐Place Foraging: An Individual‐Based Model of a Polydomous Ant Colony

Colonies of many ant species are not confined to a single nest but inhabit several dispersed nests, a colony organization referred to as polydomy. The benefits of polydomy are not well understood. It has been proposed that increased foraging efficiency promotes polydomy. In a spatially explicit individual‐based model, I compare the foraging success of monodomous and polydomous colonies in environments with varying food distributions. Multiple nests increased the colony’s foraging success if food sources were randomly scattered in the environment. Monodomous and polydomous colonies did not differ in foraging success if food sources were clustered in one or three locations. These results support the hypothesis that foraging success serves as a driver for polydomous colony organization. Because transport may occur between the dispersed nests of a polydomous colony, I tested the efficiency of a simple mechanism of food exchange between nests. This mechanism, as introduced previously in the literature, proves insufficient to equalize the level of food between nests. While the importance of transport between nests remains unclear, the model results indicate that polydomy may increase the foraging success of ant colonies and that this effect may be robust across a range of food distributions.

Persistence of aquatic insects across managed landscapes: effects of landscape permeability on re-colonization and population recovery

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.

Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work

United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:1904-1913.

Developing population models: A systematic approach for pesticide risk assessment using herbaceous plants as an example

Population models are used as tools in species management and conservation and are increasingly recognized as important tools in pesticide risk assessments. A wide variety of population model applications and resources on modeling techniques, evaluation and documentation can be found in the literature. In this paper, we add to these resources by introducing a systematic, transparent approach to developing population models. The decision guide that we propose is intended to help model developers systematically address data availability for their purpose and the steps that need to be taken in any model development. The resulting conceptual model includes the necessary complexity to address the model purpose on the basis of current understanding and available data. We provide specific guidance for the development of population models for herbaceous plant species in pesticide risk assessment and demonstrate the approach with an example of a conceptual model developed following the decision guide for herbicide risk assessment of Meads milkweed (Asclepias meadii), a species listed as threatened under the US Endangered Species Act. The decision guide specific to herbaceous plants demonstrates the details, but the general approach can be adapted for other species groups and management objectives. Population models provide a tool to link population-level dynamics, species and habitat characteristics as well as information about stressors in a single approach. Developing such models in a systematic, transparent way will increase their applicability and credibility, reduce development efforts, and result in models that are readily available for use in species management and risk assessments.

Assessing and mitigating simulated population-level effects of 3 herbicides to a threatened plant: Application of a species-specific population model of Boltonia decurrens

Extrapolating from organism-level endpoints, as generated from standard pesticide toxicity tests, to populations is an important step in threatened and endangered species risk assessments. We apply a population model for a threatened herbaceous plant species, Boltonia decurrens, to estimate the potential population-level impacts of 3 herbicides. We combine conservative exposure scenarios with dose-response relationships for growth and survival of standard test species and apply those in the species-specific model. Exposure profiles applied in the B. decurrens model were estimated using exposure modeling approaches. Spray buffer zones were simulated by using corresponding exposure profiles, and their effectiveness at mitigating simulated effects on the plant populations was assessed with the model. From simulated exposure effects scenarios that affect plant populations, the present results suggest that B. decurrens populations may be more sensitive to exposures from herbicide spray drift affecting vegetative stages than from runoff affecting early seedling survival and growth. Spray application buffer zones were shown to be effective at reducing effects on simulated populations. Our case study demonstrates how species-specific population models can be applied in pesticide risk assessment to bring organism-level endpoints, exposure assumptions, and species characteristics together in an ecologically relevant context. Environ Toxicol Chem 2018;37:1545-1555.

Adapting population models for application in pesticide risk assessment: A case study with Mead's milkweed

Population models can facilitate assessment of potential impacts of pesticides on populations or species rather than individuals and have been identified as important tools for pesticide risk assessment of nontarget species including those listed under the Endangered Species Act. Few examples of population models developed for this specific purpose are available; however, population models are commonly used in conservation science as a tool to project the viability of populations and the long-term outcomes of management actions. We present a population model for Meads milkweed (Asclepias meadii), a species listed as threatened under the Endangered Species Act throughout its range across the Midwestern United States. We adapted a published population model based on demographic field data for application in pesticide risk assessment. Exposure and effects were modeled as reductions of sets of vital rates in the transition matrices, simulating both lethal and sublethal effects of herbicides. Two herbicides, atrazine and mesotrione, were used as case study examples to evaluate a range of assumptions about potential exposure-effects relationships. In addition, we assessed buffers (i.e., setback distances of herbicide spray applications from the simulated habitat) as hypothetical mitigation scenarios and evaluated their influence on population-level effects in the model. The model results suggest that buffers can be effective at reducing risk from herbicide drift to plant populations. These case studies demonstrate that existing population models can be adopted and integrated with exposure and effects information for use in pesticide risk assessment. Environ Toxicol Chem 2018;37:2235-2245.