Co‐creation of individual‐based models by practitioners and modellers to inform environmental decision‐making

DEB-IBM for predicting climate change and anthropogenic impacts on population dynamics of hairtail Trichiurus lepturus in the East China Sea

The hairtail Trichiurus lepturus supports the largest fisheries in the East China Sea. The stock has fluctuated in the past few decades and this variation has been attributed to human pressures and climate change. To investigate energetics of individuals and population dynamics of the species in responses to environmental variations and fishing efforts, we have developed a DEB-IBM by coupling a dynamic energy budget (DEB) model to an individual-based model (IBM). The parameter estimation of DEB model shows an acceptable goodness of fit. The DEB-IBM was validated with histological data for a period of 38 years. High fishing pressure was largely responsible for the dramatic decline of the stock in middle 1980s. The stock recovered from early 1990s, which coincided with introduction of fishing moratorium on spawning stocks in inshore waters and substantial decrease of fishing efforts from large fisheries companies. In addition, the population average age showed a trend of slight decrease. The model successfully reproduced these observations of interannual variations in the population dynamics. The model was then implemented to simulate the effect of climate change on the population performance under greenhouse gas emission scenarios projected for 2100. It was also used to explore population responses to changing fishing mortalities. These scenario simulations have shown that the population biomass under SSP1-1.9, SSP2-4.5 and SSP5-8.5 would decline by 7.5%, 16.6% and 30.1%, respectively, in 2100. The model predicts that increasing fishing mortality by 10% will cause 5.3% decline of the population biomass, whereas decrease of fishing mortality by 10% will result in 6.8% increase of the biomass. The development of the DEB-IBM provides a predictive tool to inform management decisions for sustainable exploitation of the hairtail stock in the East China Sea.

No Stakeholder Is an Island: Human Barriers and Enablers in Participatory Environmental Modelling

Sustainability science strives to hone our ability to tackle problems that involve interconnected economic, social, and environmental systems. Addressing the root causes of these problems requires a more nuanced understanding of how human behaviour can undermine stakeholder engagement efforts towards effective conflict management and resolution. Participatory modelling—the co-production of knowledge via facilitated modelling workshops—plays a critical role in this endeavour by enabling participants to co-formulate problems and use modelling practices that aid in the description, solution, and decision-making actions of the group. While the difficulties of modelling with stakeholders are widely acknowledged, there is still a need to more concretely identify and categorize the barriers and opportunities that human behaviour presents to this type of engagement process. This review fills an important gap in participatory modelling practice by presenting five broad categories of barriers, along with strategies that can assist in overcoming them. We conclude with a series of actions and future research directions that the participatory modelling community as a whole can take to create more meaningful and behaviourally-attuned engagements that help stakeholders take concrete steps towards sustainability in natural resource management.

Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement

Well-managed and connected protected area networks are needed to combat the 6th mass extinction, yet the implementation of plans intended to secure landscape connectivity remains insufficient. The failure to translate planning efforts into effective action (i.e., the research-implementation gap) hinders our ability to conserve biodiversity threatened by ongoing climate change and habitat fragmentation. Sustained collaboration between researchers and practitioners to co-produce conservation strategies can bridge this gap by providing end-users with implementation guidance based on legitimate, relevant, and trusted information. However, few case studies capture methods for the co-production and use of climate-wise connectivity knowledge. Here we describe the framework for sustained engagement used by a multi-jurisdictional practitioner network to co-produce climate-wise linkages for the interior coastal ranges in Northern California. We found iterative co-production shaped ecological objectives, input data, analytical methods, and implementation priorities. Stakeholders used both co-produced and local socio-ecological (e.g., development threat, management priorities) knowledge to finalize corridor implementation plans. Priority corridors afforded greater climate benefit and were more likely to connect lands managed by participant organizations. Our results demonstrate how collaborative partnerships can bridge the gap between connectivity research and implementation. Lessons learned, outcomes, and future plans provide insights to advance landscape-scale resilience to climate change.

A concise guide to developing and using quantitative models in conservation management

Quantitative models are powerful tools for informing conservation management and decision-making. As applied modeling is increasingly used to address conservation problems, guidelines are required to clarify the scope of modeling applications and to facilitate the impact and acceptance of models by practitioners. We identify three key roles for quantitative models in conservation management: (a) to assess the extent of a conservation problem; (b) to provide insights into the dynamics of complex social and ecological systems; and, (c) to evaluate the efficacy of proposed conservation interventions. We describe 10 recommendations to facilitate the acceptance of quantitative models in conservation management, providing a basis for good practice to guide their development and evaluation in conservation applications. We structure these recommendations within four established phases of model construction, enabling their integration within existing workflows: (a) design (two recommendations); (b) specification (two); (c) evaluation (one); and (d) inference (five). Quantitative modeling can support effective conservation management provided that both managers and modelers understand and agree on the place for models in conservation. Our concise review and recommendations will assist conservation managers and modelers to collaborate in the development of quantitative models that are fit-for-purpose, and to trust and use these models appropriately while understanding key drivers of uncertainty.

Temporal plasticity in habitat selection criteria explains patterns of animal dispersal

Patterns of dispersal behavior are often driven by the composition and configuration of suitable habitat in a matrix of unsuitable habitat. Interactions between animal behavior and landscapes can therefore influence population dynamics, population and species distributions, population genetic structure, and the evolution of behavior. Spatially explicit individual-based models (IBMs) are ideal tools for exploring the effects of landscape structure on dispersal. We developed an empirically parameterized IBM in the modeling framework SEARCH to simulate dispersal of translocated American martens in Wisconsin. We tested the hypothesis that a time-limited disperser should be willing to settle in lower quality habitat over time. To evaluate model performance, we used a pattern-oriented modeling approach. Our best model matched all empirical dispersal patterns (e.g., dispersal distance) except time to settlement. This model incorporated a required search phase as well as the mechanism for declining habitat selectivity over time, which represents the first demonstration of this hypothesis for a vertebrate species. We suggest that temporal plasticity in habitat selectivity allows individuals to maximize fitness by making a tradeoff between habitat quality and risk of mortality. Our IBM is pragmatic in that it addresses a management need for a species of conservation concern. However, our model is also paradigmatic in that we explicitly tested a theory of dispersal behavior. Linking these 2 approaches to ecological modeling can further the utility of individual-based modeling and provide direction for future theoretical and empirical work on animal behavior.

Understanding the population consequences of disturbance

Managing the nonlethal effects of disturbance on wildlife populations has been a long-term goal for decision makers, managers, and ecologists, and assessment of these effects is currently required by European Union and United States legislation. However, robust assessment of these effects is challenging. The management of human activities that have nonlethal effects on wildlife is a specific example of a fundamental ecological problem: how to understand the population-level consequences of changes in the behavior or physiology of individual animals that are caused by external stressors. In this study, we review recent applications of a conceptual framework for assessing and predicting these consequences for marine mammal populations. We explore the range of models that can be used to formalize the approach and we identify critical research gaps. We also provide a decision tree that can be used to select the most appropriate model structure given the available data. Synthesis and applications: The implementation of this framework has moved the focus of discussion of the management of nonlethal disturbances on marine mammal populations away from a rhetorical debate about defining negligible impact and toward a quantitative understanding of long-term population-level effects. Here we demonstrate the framework's general applicability to other marine and terrestrial systems and show how it can support integrated modeling of the proximate and ultimate mechanisms that regulate trait-mediated, indirect interactions in ecological communities, that is, the nonconsumptive effects of a predator or stressor on a species' behavior, physiology, or life history.

Responses of Aquatic Plants to Eutrophication in Rivers: A Revised Conceptual Model

Compared to research on eutrophication in lakes, there has been significantly less work carried out on rivers despite the importance of the topic. However, over the last decade, there has been a surge of interest in the response of aquatic plants to eutrophication in rivers. This is an area of applied research and the work has been driven by the widespread nature of the impacts and the significant opportunities for system remediation. A conceptual model has been put forward to describe how aquatic plants respond to eutrophication. Since the model was created, there have been substantial increases in our understanding of a number of the underlying processes. For example, we now know the threshold nutrient concentrations at which nutrients no longer limit algal growth. We also now know that the physical habitat template of rivers is a primary selector of aquatic plant communities. As such, nutrient enrichment impacts on aquatic plant communities are strongly influenced, both directly and indirectly, by physical habitat. A new conceptual model is proposed that incorporates these findings. The application of the model to management, system remediation, target setting, and our understanding of multi-stressor systems is discussed. We also look to the future and the potential for new numerical models to guide management.

Individual-based modelling of population growth and diffusion in discrete time

Individual-based models (IBMs) of human populations capture spatio-temporal dynamics using rules that govern the birth, behavior, and death of individuals. We explore a stochastic IBM of logistic growth-diffusion with constant time steps and independent, simultaneous actions of birth, death, and movement that approaches the Fisher-Kolmogorov model in the continuum limit. This model is well-suited to parallelization on high-performance computers. We explore its emergent properties with analytical approximations and numerical simulations in parameter ranges relevant to human population dynamics and ecology, and reproduce continuous-time results in the limit of small transition probabilities. Our model prediction indicates that the population density and dispersal speed are affected by fluctuations in the number of individuals. The discrete-time model displays novel properties owing to the binomial character of the fluctuations: in certain regimes of the growth model, a decrease in time step size drives the system away from the continuum limit. These effects are especially important at local population sizes of <50 individuals, which largely correspond to group sizes of hunter-gatherers. As an application scenario, we model the late Pleistocene dispersal of Homo sapiens into the Americas, and discuss the agreement of model-based estimates of first-arrival dates with archaeological dates in dependence of IBM model parameter settings.

Management and modeling approaches for controlling raccoon rabies: The road to elimination

Rabies is an ancient viral disease that significantly impacts human and animal health throughout the world. In the developing parts of the world, dog bites represent the highest risk of rabies infection to people, livestock, and other animals. However, in North America, where several rabies virus variants currently circulate in wildlife, human contact with the raccoon rabies variant leads to the highest per capita population administration of post-exposure prophylaxis (PEP) annually. Previous rabies variant elimination in raccoons (Canada), foxes (Europe), and dogs and coyotes (United States) demonstrates that elimination of the raccoon variant from the eastern US is feasible, given an understanding of rabies control costs and benefits and the availability of proper tools. Also critical is a cooperatively produced strategic plan that emphasizes collaborative rabies management among agencies and organizations at the landscape scale. Common management strategies, alone or as part of an integrated approach, include the following: oral rabies vaccination (ORV), trap-vaccinate-release (TVR), and local population reduction. As a complement, mathematical and statistical modeling approaches can guide intervention planning, such as through contact networks, circuit theory, individual-based modeling, and others, which can be used to better understand and predict rabies dynamics through simulated interactions among the host, virus, environment, and control strategy. Strategies derived from this ecological lens can then be optimized to produce a management plan that balances the ecological needs and program financial resources. This paper discusses the management and modeling strategies that are currently used, or have been used in the past, and provides a platform of options for consideration while developing raccoon rabies virus elimination strategies in the US.

Plasmodium knowlesi transmission: integrating quantitative approaches from epidemiology and ecology to understand malaria as a zoonosis

The public health threat posed by zoonotic Plasmodium knowlesi appears to be growing: it is increasingly reported across South East Asia, and is the leading cause of malaria in Malaysian Borneo. Plasmodium knowlesi threatens progress towards malaria elimination as aspects of its transmission, such as spillover from wildlife reservoirs and reliance on outdoor-biting vectors, may limit the effectiveness of conventional methods of malaria control. The development of new quantitative approaches that address the ecological complexity of P. knowlesi, particularly through a focus on its primary reservoir hosts, will be required to control it. Here, we review what is known about P. knowlesi transmission, identify key knowledge gaps in the context of current approaches to transmission modelling, and discuss the integration of these approaches with clinical parasitology and geostatistical analysis. We highlight the need to incorporate the influences of fine-scale spatial variation, rapid changes to the landscape, and reservoir population and transmission dynamics. The proposed integrated approach would address the unique challenges posed by malaria as a zoonosis, aid the identification of transmission hotspots, provide insight into the mechanistic links between incidence and land use change and support the design of appropriate interventions.

Wildlife in the cloud: a new approach for engaging stakeholders in wildlife management

Research in wildlife management increasingly relies on quantitative population models. However, a remaining challenge is to have end-users, who are often alienated by mathematics, benefiting from this research. I propose a new approach, 'wildlife in the cloud,' to enable active learning by practitioners from cloud-based ecological models whose complexity remains invisible to the user. I argue that this concept carries the potential to overcome limitations of desktop-based software and allows new understandings of human-wildlife systems. This concept is illustrated by presenting an online decision-support tool for moose management in areas with predators in Sweden. The tool takes the form of a user-friendly cloud-app through which users can compare the effects of alternative management decisions, and may feed into adjustment of their hunting strategy. I explain how the dynamic nature of cloud-apps opens the door to different ways of learning, informed by ecological models that can benefit both users and researchers.