Eliciting expert knowledge to inform landscape modeling of conservation scenarios

Price, Jessica; Silbernagel, Janet; Miller, Nicholas; Swaty, Randy; White, Mark A.; Nixon, Kristina

doi:10.1016/j.ecolmodel.2011.09.010

Cited by 25 publications

(15 citation statements)

References 29 publications

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“…Including such groups in the scenario-building process will further improve not only the quality, but also the acceptance and relevance of scenario-based studies of ES development (Silbernagel et al 2011;Price et al 2012).…”

Section: Interdisciplinary Dialoguementioning

confidence: 99%

“…For example, in modeling forest scenarios, Nixon et al (2014) evaluated the effectiveness of different conservation strategies to meet target species needs, while also sustaining timber harvests (Price et al 2012). The scenarios evaluate the premise that blending resource extraction, such as sustainable timber harvest, and biodiversity conservation should yield greater socio-economic benefits without significantly compromising the conservation of biodiversity or the sustainable provisioning of ecosystem services.…”

Section: Scenario Studiesmentioning

confidence: 99%

“…This did not, however, hinder the spread of the concept into management and policy because the concept helps address several core difficulties that these fields face, ranging from monitoring and valuing ecosystem processes and assets of a country or a region (Wallace 2007) to assessing the diversity of environmental effects of a policy or a project. Exploring future effects of zoning regulations (Geneletti 2013), conservation strategies (Price et al 2012) and climate change (Forsius et al 2013) on ES is now an important topic in ES research, which can have implications for adaptation and mitigation strategies relevant to policy making.…”

Section: Introductionmentioning

confidence: 99%

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Linking ecosystem services with landscape history

Bürgi

Silbernagel

et al. 2014

Landscape Ecol

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The concept of ecosystem services (ES) has become widely used because it bridges ecology and economics and links nature to society. ES may evolve over time in dynamic landscapes driven by myriad processes. However, the consequences of changes in key ES has not been considered adequately in current ES research. Here we propose a framework for linking ES with landscape history, which can help us better understand the evolution of ES over time. We illustrate the framework by a case study from Switzerland. Both the capacity of landscapes to supply ES and the realization and recognition of key ES are likely to change over time. This insight should have important implications for landscape sustainability and related scenario studies.

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Section: Interdisciplinary Dialoguementioning

confidence: 99%

Section: Scenario Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Linking ecosystem services with landscape history

Bürgi

Silbernagel

et al. 2014

Landscape Ecol

Self Cite

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“…Others have addressed the difficulties of integrating expert knowledge in modeling processes (Krueger et al, 2012;Martin et al, 2012;O'Hagan, 2012;Price et al, 2012;Voinov and Bousquet, 2010;). For example, Krueger et al (2012) provided a typology of expert-based models used in environmental modeling, and suggested objective ways to integrate expert opinion throughout multiple phases of modeling.…”

Section: Stakeholder Involvement In Decision Support For Land Use Plamentioning

confidence: 99%

Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA

Meyer

Johnson

Lilieholm

et al. 2014

Ecological Modelling

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Land use change results from frequent, independent actions by decision-makers working in isolation, often with a focus on a single land use. In order to develop integrated land use policies that encourage sustainable outcomes, scientists and practitioners must understand the specific drivers of land use change across mixed land use types and ownerships, and must consider the combined influences of biophysical, economic, and social factors that affect land use decisions. In this analysis of two large watersheds covering a total of 1.9 million hectares in Maine, U.S.A., we co-developed with groups of stakeholders land use suitability models that integrated four land uses: economic development, ecosystem protection, forestry, and agriculture. We elicited stakeholder knowledge to: (1) identify generalized drivers of land use change; (2) construct Bayesian network models of suitability for each of the four land uses based on site-level factors that affect land use decisions; and (3) identify thresholds of suitability for each factor and give relative weights to each factor. We then applied 12 distinct Bayesian models using 99 spatially explicit, empirical socioeconomic and biophysical datasets to predict spatially the suitability for each of our four land uses on a 30 x 30 m pixel basis across 1.9 million hectares. We evaluated both the stakeholder engagement process and the land use suitability maps. Results demonstrated the potential efficacy of these models for strategic land use planning, but also revealed that trade-offs occur when stakeholder knowledge is used to augment limited empirical data. First, stakeholder-derived Bayesian land use models can provide decision-makers with relevant insights about the factors affecting land use change. Unfortunately, these models are not easily validated for predictive purposes. Second, integrating stakeholders throughout different phases of the modeling process provides a flexible framework for developing localized or generalizable land use models depending on the scope of stakeholder knowledge and available empirical data. The potential downside is that this can lead to more complex models than anticipated. The trade-offs between model rigor and relevance suggest an adaptive management approach to modeling is needed to improve the integration of stakeholder knowledge into robust land use models.

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“…In many instances, scenario creation is expert-and/or model-driven, and researchers make the case for their utility to end users [9][10][11][12]. This is problematic in a case with high stakes and high uncertainty, as with land use.…”

Section: Introductionmentioning

confidence: 99%

Development of Future Land Cover Change Scenarios in the Metropolitan Fringe, Oregon, U.S., with Stakeholder Involvement

Hoyer

Chang

2014

Land

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Abstract:We describe a future land cover scenario construction process developed under consultation with a group of stakeholders from our study area. We developed a simple geographic information system (GIS) method to modify a land cover dataset and then used qualitative data extracted from the stakeholder storyline to modify it. These identified variables related to our study area's land use regulation system as the major driver in the placement of new urban growth on the landscape; and the accommodation of new population as the determinant of its growth rate. The outcome was a series of three scenario maps depicting a gradient of increased urbanization. The effort attempted to create a simple and transparent modeling framework that is easy to communicate. The incorporation of the regulatory context and rules and place-specific modeling for denser urban and sparse rural areas provide new insights of future land conversions. This relatively rapid mapping process provides useful information for spatial planning and projects for where and how much urban land will be present by the year 2050.

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Eliciting expert knowledge to inform landscape modeling of conservation scenarios

Cited by 25 publications

References 29 publications

Linking ecosystem services with landscape history

Linking ecosystem services with landscape history

Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA

Development of Future Land Cover Change Scenarios in the Metropolitan Fringe, Oregon, U.S., with Stakeholder Involvement

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