An evidence assessment tool for ecosystem services and conservation studies

Mupepele, Anne‐Christine; Walsh, Jessica C.; Sutherland, William J.; Dormann, Carsten F.

doi:10.1890/15-0595

Cited by 61 publications

(93 citation statements)

References 57 publications

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“…A systematic review that achieves a high Level-of-Evidence (LoE) includes quantitative measures [34]. Therefore, we used an original statistical analysis, multiple correspondence analysis, displaying potential gaps in the literature.…”

Section: Discussionmentioning

confidence: 99%

Adaptation to Climate Change in Forestry: A Multiple Correspondence Analysis (MCA)

Brunette

Bourke

Hanewinkel

et al. 2018

Forests

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Abstract:We analyze economic perspectives of forest adaptation to risk attributes, caused mostly by climate change. We construct a database with 89 systematically chosen articles, dealing simultaneously with climate, adaptation, risk and economy. We classify the database with regard to 18 variables bearing on the characteristics of the paper, the description of the risk and the adaptation strategy, the topic and the corresponding results. To achieve a "high level-of-evidence", we realize a multiple correspondence analysis (MCA) to identify which variables were found in combination with one other in the literature and make distinct groupings affecting adaptive decisions. We identify three groups: (i) profit and production; (ii) microeconomic risk-handling; and (iii) decision and behavior. The first group includes economic costs and benefits as the driver of adaptation and prioritizes simulation, and a mix of theoretical and empirical economic approach. The second group distinctly involves risk-related issues, in particular its management by adaptation. The third group gathers a large set of social and behavioral variables affecting management decisions collected through questionnaires. Such an approach allows the identification of gaps in the literature, concerning the impact of owners' preferences towards risk and uncertainty regarding adaptation decisions, the fact that adaptation was often reduced in an attempt to adapt to the increasing risk of wildfire, or the existence of a regional bias.

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Section: Discussionmentioning

confidence: 99%

Adaptation to Climate Change in Forestry: A Multiple Correspondence Analysis (MCA)

Brunette

Bourke

Hanewinkel

et al. 2018

Forests

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“…Recently, numerous studies have used an ES conservation-based approach to conservation planning. For example, Bhagabati et al [13] determined conservation scenarios based on ES; Sandifer et al [14] used ES for biodiversity health enhancement and conservation; Rodriguez-Loinaz et al [15] proposed multifunctional landscape conservation using an ES conservation approach; Hansen et al [16] included ES in planning discourses of European and American cities; Mitchell et al [17] considered ES in their landscape management approach under landscape fragmentation; Darvill and Lindo [18] reported on conservation with priorities for cultural ES values; Zheng et al [19] considered ES with respect to water conservation policies and management practices; Snall et al [20] considered ES in green infrastructure design; Mupepele et al [21] included ES in evidence-based environmental management; Jorgensen et al [22] reported on local municipal decision making in South Africa that included ES considerations; Maes et al [4] applied ES conservation concepts in support of the EU Biodiversity Strategy; Verhagen et al [23] reported on spatial priority patterns for ES conservation; and Lin et al [10] incorporated ES in social-ecological conservation. Yet, 'landscape sustainability' itself is an important research priority that is a key in shaping the debate among landscape ecologists about the relationships between landscapes, ES, and human well-being [24].…”

Section: Introductionmentioning

confidence: 99%

Landscape Conservation Planning to Sustain Ecosystem Services under Climate Change

et al. 2019

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Sustainable conservation aims to ensure the sustained conservation of landscape multi-functionality which in turn requires ensuring ecosystem service (ES) and habitat quality (HQ) sustainability with inclusive landscape-scale conservation planning. This study proposes a landscape conservation planning (LCP) framework for landscape-scale ES-HQ conservation and sustainability. Spatially explicit hotspots for five ESs and HQs are identified via InVEST and LISA software. Spatiotemporal changes in ES-HQ hotspots, in terms of stability and resilience, are delineated. The Zonation technique is applied to prioritize areas for conservation based on ES-HQ hotspot stability and resilience maps. High priority conservation areas are identified and are used as reserve area inputs for land use modeling with CLUE-S software to simulate future land use change under climate change scenarios. This study reports that varied rainfall and climate are major driving factors of ES-HQ sustainability disturbance in the study area. Furthermore, our proposed conservation Strategy 2 demonstrates that a larger extent of landscape multi-functionality can be sustained when the existing conservation area includes the total area of identified ES-HQ resilient hotspots. This study effectively identifies the stability and resiliency of ES-HQ hotspot areas affected by disturbances for high priority landscape conservation requirements to ensure ES-HQ sustainability and landscape multi-functionality in the study area.

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“…Alternative approaches of evidence synthesis to tackle poor data reporting, such as non-parametric weighting by sample size, have been encouraged (Gurevitch and Hedges 1999) and proposed (Mayerhofer et al 2013, Adams et al 1997) but these weights fail to consider wider aspects of study quality, including pseudoreplication and study design (Spake and Doncaster 2017). Whilst recent efforts for assessing evidence quantitatively by study design , Mupepele et al 2016, Mupepele & Dormann 2017 are welcomed, their weights are relatively simplistic and discrete (e.g. simple integer scores or categories) and do not seem to have been informed using quantitative evidence.…”

Section: Discussionmentioning

confidence: 99%

“…Although study design and spatial replication only assess part of study quality (Spake and Doncaster 2017), our weights are also versatile and could be modulated using subject-specific quality checklists to help incorporate more context-specific factors of study quality into evidence assessment such as size of sampling unit, temporal replication and internal validity (Spake and Doncaster 2017;Mupepele et al 2016;Bilotta et al 2014). For example, our weights could be multiplied by the percentage of criteria met in quality checklists.…”

Section: Discussionmentioning

confidence: 99%

Simple study designs in ecology produce inaccurate estimates of biodiversity responses

Christie

Amano

Martin

et al. 2019

Preprint

Self Cite

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1. Ecologists use a wide range of study designs to estimate the impact of interventions or threats but there are no quantitative comparisons of their accuracy. For example, while it is accepted that simpler designs, such as After (sampling sites post-impact without a control), Before-After (BA) and Control-Impact (CI), are less robust than Randomised Controlled Trials (RCT) and Before-After Control-Impact (BACI) designs, it is not known how much less accurate they are.2. We simulate a step-change response of a population to an environmental impact using empirically-derived estimates of the major parameters. We use five ecological study designs to estimate the effect of this impact and evaluate each one by determining the percentage of simulations in which they accurately estimate the direction and magnitude of the environmental impact. We also simulate different numbers of replicates and assess several accuracy thresholds.3. We demonstrate that BACI designs could be 1.1-1.5 times more accurate than RCTs, 2.9-4.1 times more accurate than BA, 3.8-5.6 times more accurate than CI, and 6.8-10.8 times more accurate than After designs, when estimating to within ±30% of the true effect (depending on the sample size). We also found that increasing sample size substantially increases the accuracy of BACI designs but only increases the precision of simpler designs around a biased estimate; only by using more robust designs can accuracy increase. Modestly increasing replication of both control and impact sites also increased the accuracy of BACI designs more than substantially increasing replicates in just one of these groups.4. We argue that investment into using more robust designs in ecology, where possible, is extremely worthwhile given the inaccuracy of simpler designs, even when using large sample sizes. Based on our results we propose a weighting system that quantitatively ranks the accuracy of studies based on their study design and the number of replicates used. We hope these 'accuracy weights' enable researchers to better account for study design in evidence synthesis when assessing the reliability of a range of studies using a variety of designs.

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An evidence assessment tool for ecosystem services and conservation studies

Cited by 61 publications

References 57 publications

Adaptation to Climate Change in Forestry: A Multiple Correspondence Analysis (MCA)

Adaptation to Climate Change in Forestry: A Multiple Correspondence Analysis (MCA)

Landscape Conservation Planning to Sustain Ecosystem Services under Climate Change

Simple study designs in ecology produce inaccurate estimates of biodiversity responses

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