2017
DOI: 10.1002/ecs2.2021
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The impact of climate change uncertainty on California's vegetation and adaptation management

Abstract: Abstract. The impacts of different emission levels and climate change conditions to landscape-scale natural vegetation could have large repercussions for ecosystem services and environmental health. We forecast the risk-reduction benefits to natural landscapes of lowering business-as-usual greenhouse gas emissions by comparing the extent and spatial patterns of climate exposure to dominant vegetation under current emissions trajectories (Representative Concentration Pathway, RCP8.5) and envisioned Paris Accord… Show more

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Cited by 51 publications
(63 citation statements)
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References 49 publications
(75 reference statements)
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“…Previous studies have indicated a high level of climate change exposure in the foothills of CA (Thorne et al, 2017(Thorne et al, , 2018 2015). Other dynamic vegetation model simulations indicate contracting needle leaf evergreen forest cover in some areas we identify as having low drought vulnerability (Jiang et al, 2013).…”
Section: Discussionmentioning
confidence: 97%
“…Previous studies have indicated a high level of climate change exposure in the foothills of CA (Thorne et al, 2017(Thorne et al, , 2018 2015). Other dynamic vegetation model simulations indicate contracting needle leaf evergreen forest cover in some areas we identify as having low drought vulnerability (Jiang et al, 2013).…”
Section: Discussionmentioning
confidence: 97%
“…Climate change is expected to negatively impact southwestern US rangeland production (Reeves, Bagne, & Tanaka, 2017;Reeves, Moreno, Bagne, & Running, 2014), including most of California (Shaw et al, 2011). Forecasting climate change impacts on California rangelands is inherently difficult given the uncertainty of the global emissions trajectory and the possibility for species distribution shifts (Thorne et al, 2017). Forecasting climate change impacts on California rangelands is inherently difficult given the uncertainty of the global emissions trajectory and the possibility for species distribution shifts (Thorne et al, 2017).…”
mentioning
confidence: 99%
“…For example, Thorne et al. () used PCA in a study that determined the sensitivity of vegetation groups to future climate distributions across California, Thorne et al. () selected the first two PCs, which explained approximately 80% of the variance, for their climate exposure analysis.…”
Section: Methodsmentioning
confidence: 99%
“…A common approach is to simply select the first two PCs for further analysis. For example, Thorne et al (2017) used PCA in a study that determined the sensitivity of vegetation groups to future climate distributions across California, Thorne et al (2017) selected the first two PCs, which We selected PCs to retain for the cluster analysis and SMRU classification using a break in slope screetest criterion (Cattell 1966), which is a common empirical method that defines a suite of PCs with the largest explanatory power. Larger eigenvalues represent greater explanatory power and the eigenvalues decrease sequentially for each additional PC, while asymptotically approaching zero.…”
Section: Multivariate Analysis Geographic Information System-workflowmentioning
confidence: 99%