Representing human decisions is of fundamental importance in agent-based models. However, the rationale for choosing a particular human decision model is often not sufficiently empirically or ...theoretically substantiated in the model documentation. Furthermore, it is difficult to compare models because the model descriptions are often incomplete, not transparent and difficult to understand. Therefore, we expand and refine the ‘ODD’ (Overview, Design Concepts and Details) protocol to establish a standard for describing ABMs that includes human decision-making (ODD + D). Because the ODD protocol originates mainly from an ecological perspective, some adaptations are necessary to better capture human decision-making. We extended and rearranged the design concepts and related guiding questions to differentiate and describe decision-making, adaptation and learning of the agents in a comprehensive and clearly structured way. The ODD + D protocol also incorporates a section on ‘Theoretical and Empirical Background’ to encourage model designs and model assumptions that are more closely related to theory. The application of the ODD + D protocol is illustrated with a description of a social–ecological ABM on water use. Although the ODD + D protocol was developed on the basis of example implementations within the socio-ecological scientific community, we believe that the ODD + D protocol may prove helpful for describing ABMs in general when human decisions are included.
•We expand the ODD protocol to describe human decisions in ABMs.•We exemplify the new ODD + D (ODD + Decision) with a social–ecological ABM on water use.•ODD + D facilitates communication and comparison of models.
Animal migration is a global phenomenon, but few studies have examined the substantial within‐ and between‐species variation in migration distances. We built a global database of 94 land migrations ...of large mammalian herbivore populations ranging from 10 to 1638 km. We examined how resource availability, spatial scale of resource variability and body size affect migration distance among populations. Resource availability measured as normalised difference vegetation index had a strong negative effect, predicting a tenfold difference in migration distances between low‐ and high‐resource areas and explaining 23% of the variation in migration distances. We found a weak, positive effect of the spatial scale of resource variability but no effect of body size. Resource‐poor environments are known to increase the size of mammalian home ranges and territories. Here, we demonstrate that for migratory populations as well, animals living in resource‐poor environments travel farther to fulfil their resource needs.
Researchers and development organizations regularly grapple with competing ecological and financial strategies for building climate resilience in smallholder agricultural systems, but rarely are such ...approaches considered in tandem. Using a social-ecological simulation model, we explored how different combinations of legume cover cropping, an ecological insurance, and index-based crop insurance, a financial insurance, affect the climate resilience of mixed crop-livestock smallholder farmers over time. The model simulates interactions between soil nutrient dynamics, crop yields, and household wealth, which is carried solely in the form of livestock. We assume legume cover cropping provides biological nitrogen fixation, thereby increasing soil fertility and productivity over time, whereas microinsurance gives payouts in drought years that provide ex-post coping benefits. Our model results indicate that the benefits of cover cropping to mean household income strongly complement the shock-absorbing benefits of microinsurance. Specifically, we found: (1) insurance always provides larger benefits during and in the wake of a drought, while cover cropping progressively reduces poverty in the medium- to long-term; (2) the use of crop insurance solely as an ex-post coping strategy may not reduce the incidence of poverty; and (3) legume cover cropping offers larger relative benefits in more degraded environments and for poor farmers. These results underscore the complementary roles that ecological and financial strategies could play in building resilience in smallholder agricultural systems. The stylized model constitutes an important social-ecological foundation for future empirical research to inform agricultural innovation and sustainable development priorities.
Despite the increasing use of standards for documenting and testing agent-based models (ABMs) and sharing of open access code, most ABMs are still developed from scratch. This is not only ...inefficient, but also leads to ad hoc and often inconsistent implementations of the same theories in computational code and delays progress in the exploration of the functioning of complex social-ecological systems (SES). We argue that reusable building blocks (RBBs) known from professional software development can mitigate these issues. An RBB is a submodel that represents a particular mechanism or process that is relevant across many ABMs in an application domain, such as plant competition in vegetation models, or reinforcement learning in a behavioural model. RBBs need to be distinguished from modules, which represent entire subsystems and include more than one mechanism and process. While linking modules faces the same challenges as integrating different models in general, RBBs are “atomic” enough to be more easily re-used in different contexts. We describe and provide examples from different domains for how and why building blocks are used in software development, and the benefits of doing so for the ABM community and to individual modellers. We propose a template to guide the development and publication of RBBs and provide example RBBs that use this template. Most importantly, we propose and initiate a strategy for community-based development, sharing and use of RBBs. Individual modellers can have a much greater impact in their field with an RBB than with a single paper, while the community will benefit from increased coherence, facilitating the development of theory for both the behaviour of agents and the systems they form. We invite peers to upload and share their RBBs via our website - preferably referenced by a DOI (digital object identifier obtained e.g. via Zenodo). After a critical mass of candidate RBBs has accumulated, feedback and discussion can take place and both the template and the scope of the envisioned platform can be improved.
•Reusable Building Blocks (RBBs) are effective in software development but are underrepresented in agent-based modelling.•RBBs describe individual mechanisms or processes, distinguishing them from modules that represent entire subsystems.•We present a first website that demonstrates how a RBB template and repository can be organized.•Examples of RBBs are provided to illustrate the concept, fostering discussion and encouraging further refinement.
ABSTRACT
Aim To demonstrate how the interrelations of individual movements form large‐scale population‐level movement patterns and how these patterns are associated with the underlying landscape ...dynamics by comparing ungulate movements across species.
Locations Arctic tundra in Alaska and Canada, temperate forests in Massachusetts, Patagonian Steppes in Argentina, Eastern Steppes in Mongolia.
Methods We used relocation data from four ungulate species (barren‐ground caribou, Mongolian gazelle, guanaco and moose) to examine individual movements and the interrelation of movements among individuals. We applied and developed a suite of spatial metrics that measure variation in movement among individuals as population dispersion, movement coordination and realized mobility. Taken together, these metrics allowed us to quantify and distinguish among different large‐scale population‐level movement patterns such as migration, range residency and nomadism. We then related the population‐level movement patterns to the underlying landscape vegetation dynamics via long‐term remote sensing measurements of the temporal variability, spatial variability and unpredictability of vegetation productivity.
Results Moose, which remained in sedentary home ranges, and guanacos, which were partially migratory, exhibited relatively short annual movements associated with landscapes having very little broad‐scale variability in vegetation. Caribou and gazelle performed extreme long‐distance movements that were associated with broad‐scale variability in vegetation productivity during the peak of the growing season. Caribou exhibited regular seasonal migration in which individuals were clustered for most of the year and exhibited coordinated movements. In contrast, gazelle were nomadic, as individuals were independently distributed and moved in an uncoordinated manner that relates to the comparatively unpredictable (yet broad‐scale) vegetation dynamics of their landscape.
Main conclusions We show how broad‐scale landscape unpredictability may lead to nomadism, an understudied type of long‐distance movement. In contrast to classical migration where landscapes may vary at broad scales but in a predictable manner, long‐distance movements of nomadic individuals are uncoordinated and independent from other such individuals. Landscapes with little broad‐scale variability in vegetation productivity feature smaller‐scale movements and allow for range residency. Nomadism requires distinct integrative conservation strategies that facilitate long‐distance movements across the entire landscape and are not limited to certain migration corridors.
Long-term trends in photosynthetic capacity measured with the satellite-derived Normalized Difference Vegetation Index (NDVI) are usually associated with climate change. Human impacts on the global ...land surface are typically not accounted for. Here, we provide the first global analysis quantifying the effect of the earth's human footprint on NDVI trends. Globally, more than 20% of the variability in NDVI trends was explained by anthropogenic factors such as land use, nitrogen fertilization, and irrigation. Intensely used land classes, such as villages, showed the greatest rates of increase in NDVI, more than twice than those of forests. These findings reveal that factors beyond climate influence global long-term trends in NDVI and suggest that global climate change models and analyses of primary productivity should incorporate land use effects.
Dynamic process‐based modelling is often proposed as a powerful tool to understand complex socio‐environmental problems and to provide sustainable solutions as it allows disentangling cause and ...effect of human behaviour and environmental dynamics. However, the impact of such models in decision‐making and to support policy‐making has so far been very limited.
In this paper, we want to take a critical look at the reasons behind this situation and propose steps that need to be taken to change it. We investigate a number of good practice examples from fields where models have influenced policy‐making and management to identify the main aspects that promote or impede the application of these models.
Specifically, we compare examples that differ in their extent to how explicitly they represent human behaviour as part of the model, ranging from purely environmental systems (including models for river management, honeybee colonies and animal diseases), where modelling techniques have long been established, to coupled socio‐environmental systems (including models for land use, fishery management and sustainable water use).
We use these examples to synthesise four key factors for successful modelling for policy and management support in socio‐environmental systems. They cover (a) the specific requirements caused by modelling the human dimension, (b) the importance of data availability and accessibility, (c) essential elements of the partnership between modellers and decision‐makers and (d) insights related to characteristics of the decision process.
For each of these aspects, we give recommendations specifically to modellers, decision‐makers or both to make the use of models for practice more effective. We argue that if all parties involved in the modelling and decision‐making process take into account these suggestions during their collaboration, the full potential that socio‐environmental modelling bears can increasingly unfold.
A free Plain Language Summary can be found within the Supporting Information of this article.
A free Plain Language Summary can be found within the Supporting Information of this article.
Half of the European Union (EU) land and the livelihood of 10 million farmers is threatened by unsustainable land-use intensification, land abandonment and climate change. Policy instruments, ...including the EU Common Agricultural Policy (CAP) have so far failed to stop this environmental degradation. BESTMAP will: 1) Develop a behavioural theoretical modelling framework to take into account complexity of farmers’ decision-making; 2) Develop, adapt and customize a suite of opensource, flexible, interoperable and customisable computer models linked to existing data e.g. LPIS/IACS and remote sensing e.g. Sentinel-2; 3) Link economic, individual-farm agent-based, biophysical ecosystem services and biodiversity and geostatistical socio-economic models; 4) Produce a simple-to-use dashboard to compare scenarios of Agri-Environmental Schemes adoption; 5) Improve the effectiveness of future EU rural policies’ design, monitoring and implementation.
Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented ...by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) - to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social-ecological systems.
Representing human decisions is of fundamental importance in agent-based models. However, the rationale for choosing a particular human decision model is often not sufficiently empirically or ...theoretically substantiated in the model documentation. Furthermore, it is difficult to compare models because the model descriptions are often incomplete, not transparent and difficult to understand. Therefore, we expand and refine the 'ODD' (Overview, Design Concepts and Details) protocol to establish a standard for describing ABMs that includes human decision-making (ODD + D). Because the ODD protocol originates mainly from an ecological perspective, some adaptations are necessary to better capture human decision-making. We extended and rearranged the design concepts and related guiding questions to differentiate and describe decision-making, adaptation and learning of the agents in a comprehensive and clearly structured way. The ODD + D protocol also incorporates a section on 'Theoretical and Empirical Background' to encourage model designs and model assumptions that are more closely related to theory. The application of the ODD + D protocol is illustrated with a description of a social ecological ABM on water use. Although the ODD + D protocol was developed on the basis of example implementations within the socio-ecological scientific community, we believe that the ODD + D protocol may prove helpful for describing ABMs in general when human decisions are included.
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