Emerging Opportunities for Landscape Ecological Modelling

Synes, Nicholas W.; Brown, Calum; Watts, Kevin; White, Steven M.; Gilbert, Mark; Travis, Justin

doi:10.1007/s40823-016-0016-7

Cited by 31 publications

(22 citation statements)

References 281 publications

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“…SES models contain ecological, social and management (governance) components, which are linked by behavioural feedbacks (Ostrom 2010). Both terrestrial and aquatic SESs can be spatially-structured and spatially-managed (Synes et al 2016). Hence, any SES model must D r a f t explicitly capture the key processes that regulate these feedbacks and, as in any spatially complex system, also make credible predictions across space and time (Carpenter and Brock 2004;Sanchirico and Wilen 2005;Synes et al 2016).…”

mentioning

confidence: 99%

Landscape-scale social and ecological outcomes of dynamic angler and fish behaviours: processes, data, and patterns

Carruthers

Dabrowska

Haider

et al. 2019

Can. J. Fish. Aquat. Sci.

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The first relatively complete landscape-scale social–ecological system (SES) model of a recreational fishery was developed and ground-truthed with independent angling effort data. Based on the British Columbia multistock recreational fishery for rainbow trout (Oncorynchus mykiss), the model includes hundreds of individual lake fisheries, hundreds of thousands of anglers, originating from tens of communities, connected by complex road and trail networks, all distributed over a landscape of approximately half a million square kilometres. The approach is unique in that it incorporates realistic and empirically derived behavioural interactions within and among the three key components of the SES: angler communities, fish populations, and management policies. Current management policies were characterized and alternate policies assessed by simulation. We examined spatial patterns in ecological and social properties of the SES and used simulations to investigate the impacts of alternate management policies on these patterns. Simulation outcomes strongly depended on the spatial redistribution of anglers across the landscape, existing road networks, heterogeneity in angler behaviours, and the spatial pattern of fish population productivity.

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mentioning

confidence: 99%

Landscape-scale social and ecological outcomes of dynamic angler and fish behaviours: processes, data, and patterns

Carruthers

Dabrowska

Haider

et al. 2019

Can. J. Fish. Aquat. Sci.

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“…In any case, future research is increasingly likely to involve the coupling of models to study interacting systems (Synes et al 2016), and realistic couplings require that feedback mechanisms are implemented between the study systems. A model of animal movement and population dynamics will often therefore require a model of the changing landscape or environment in which the species lives.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, individual-or agent-based modelling (hereafter ABM) has become a common method of studying underlying interactions in complex social and ecological systems on the basis of individual-level characteristics and behaviours within varied environmental, social and economic contexts (Matthews et al 2007, Grimm and Railsback 2013, Synes et al 2016. In particular, process-based modelling approaches that have become widespread in recent years share key characteristics in focusing on fundamental system behaviours via 'bottom-up' model architectures, in principle allowing for the coupling of models of different sub-systems.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, process-based modelling approaches that have become widespread in recent years share key characteristics in focusing on fundamental system behaviours via 'bottom-up' model architectures, in principle allowing for the coupling of models of different sub-systems. For instance, individual-or agent-based modelling (hereafter ABM) has become a common method of studying underlying interactions in complex social and ecological systems on the basis of individual-level characteristics and behaviours within varied environmental, social and economic contexts (Matthews et al 2007, Grimm and Railsback 2013, Synes et al 2016. In ecology, ABMs are increasingly used to study animal movements (Tang andBennett 2010, Watkins et al 2015), help identify threats to populations (Wiegand et al 2004), test the efficacy of conservation strategies (Synes et al 2015, Aben et al 2016) and predict the impacts of land-use scenarios (Gimona et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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Coupled land use and ecological models reveal emergence and feedbacks in socio‐ecological systems

et al. 2018

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Understanding the dynamics of socio-ecological systems is crucial to the development of environmentally sustainable practices. Models of social or ecological sub-systems have greatly enhanced such understanding, but at the risk of obscuring important feedbacks and emergent effects. Integrated modelling approaches have the potential to address this shortcoming by explicitly representing linked socio-ecological dynamics. We developed a socio-ecological system model by coupling an existing agentbased model of land-use dynamics and an individual-based model of demography and dispersal. A hypothetical case-study was established to simulate the interaction of crops and their pollinators in a changing agricultural landscape, initialised from a spatially random distribution of natural assets. The bi-directional coupled model predicted larger changes in crop yield and pollinator populations than a unidirectional uncoupled version. The spatial properties of the system also differed, the coupled version revealing the emergence of spatial land-use clusters that neither supported nor required pollinators. These findings suggest that important dynamics may be missed by uncoupled modelling approaches, but that these can be captured through the combination of currently-available, compatible model frameworks. Such model integrations are required to further fundamental understanding of socio-ecological dynamics and thus improve management of socio-ecological systems.

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“…For example, there can be considerable benefits of jointly developing a stochastic IBM and a typically deterministic integrodifference model to estimate rates of spread (e.g., Travis et al, 2011;Santini et al, 2016). Notably, while until recently integrodifference models have almost exclusively been used to project spread rates across homogenous landscapes, recent developments are enabling rapid simulation of integrodifference equations across spatially complex landscapes (e.g., Synes et al, 2016;Gilbert et al, 2017). One major potential advantage of the integrodifference approach is that the much faster speed of individual simulations will make inverse fitting of parameters through Bayesian approaches including approximate Bayesian computation much more readily achievable.…”

Section: Future Modeling Perspectivesmentioning

confidence: 99%

Early Engagement of Stakeholders with Individual-Based Modeling Can Inform Research for Improving Invasive Species Management: The Round Goby as a Case Study

et al. 2017

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Individual-based models (IBMs) incorporating realistic representations of key range-front processes such as dispersal can be used as tools to investigate the dynamics of invasive species. Managers can apply insights from these models to take effective action to prevent further spread and prioritize measures preventing establishment of invasive species. We highlight here how early-stage IBMs (constructed under constraints of time and data availability) can also play an important role in defining key research priorities for providing key information on the biology of an invasive species in order that subsequent models can provide robust insight into potential management interventions. The round goby, Neogobius melanostomus, is currently spreading through the Baltic Sea, with major negative effects being reported in the wake of its invasion. Together with stakeholders, we parameterize an IBM to investigate the goby's potential spread pattern throughout the Gulf of Gdansk and the Baltic Sea. Model parameters were assigned by integrating information obtained through stakeholder interaction, from scientific literature, or estimated using an inverse modeling approach when not available. IBMs can provide valuable direction to research on invasive species even when there is limited data and/or time available to parameterize/fit them to the degree to which we might aspire in an ideal world. Co-development of models with stakeholders can be used to recognize important invasion patterns, in addition to identifying and estimating unknown environmental parameters, thereby guiding the direction of future research. Well-parameterized and validated models are not required in the earlier stages of the modeling cycle where their main utility is as a tool for thought.

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Emerging Opportunities for Landscape Ecological Modelling

Cited by 31 publications

References 281 publications

Landscape-scale social and ecological outcomes of dynamic angler and fish behaviours: processes, data, and patterns

Landscape-scale social and ecological outcomes of dynamic angler and fish behaviours: processes, data, and patterns

Coupled land use and ecological models reveal emergence and feedbacks in socio‐ecological systems

Early Engagement of Stakeholders with Individual-Based Modeling Can Inform Research for Improving Invasive Species Management: The Round Goby as a Case Study

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