The impact of climate change uncertainty on California's vegetation and adaptation management

Thorne, James H.; Choe, Hyeyeong; Boynton, Ryan; Bjorkman, Jacquelyn; Albright, Whitney; Nydick, Koren R.; Flint, Alan L.; Flint, Lorraine E.; Schwartz, Mark W.

doi:10.1002/ecs2.2021

Cited by 52 publications

(63 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

Near‐future forest vulnerability to drought and fire varies across the western United States

Buotte

Levis²,

Law

et al. 2018

Global Change Biology

View full text Add to dashboard Cite

Recent prolonged droughts and catastrophic wildfires in the western United States have raised concerns about the potential for forest mortality to impact forest structure, forest ecosystem services, and the economic vitality of communities in the coming decades. We used the Community Land Model (CLM) to determine forest vulnerability to mortality from drought and fire by the year 2049. We modified CLM to represent 13 major forest types in the western United States and ran simulations at a 4‐km grid resolution, driven with climate projections from two general circulation models under one emissions scenario (RCP 8.5). We developed metrics of vulnerability to short‐term extreme and prolonged drought based on annual allocation to stem growth and net primary productivity. We calculated fire vulnerability based on changes in simulated future area burned relative to historical area burned. Simulated historical drought vulnerability was medium to high in areas with observations of recent drought‐related mortality. Comparisons of observed and simulated historical area burned indicate simulated future fire vulnerability could be underestimated by 3% in the Sierra Nevada and overestimated by 3% in the Rocky Mountains. Projections show that water‐limited forests in the Rocky Mountains, Southwest, and Great Basin regions will be the most vulnerable to future drought‐related mortality, and vulnerability to future fire will be highest in the Sierra Nevada and portions of the Rocky Mountains. High carbon‐density forests in the Pacific coast and western Cascades regions are projected to be the least vulnerable to either drought or fire. Importantly, differences in climate projections lead to only 1% of the domain with conflicting low and high vulnerability to fire and no area with conflicting drought vulnerability. Our drought vulnerability metrics could be incorporated as probabilistic mortality rates in earth system models, enabling more robust estimates of the feedbacks between the land and atmosphere over the 21st century.

show abstract

Section: Discussionmentioning

confidence: 97%

Near‐future forest vulnerability to drought and fire varies across the western United States

Buotte

Levis²,

Law

et al. 2018

Global Change Biology

View full text Add to dashboard Cite

show abstract

“…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%

Microclimate–forage growth linkages across two strongly contrasting precipitation years in a Mediterranean catchment

O’Geen

Larsen²,

Dahlke

et al. 2019

Ecohydrology

View full text Add to dashboard Cite

Given the complex topography of California rangelands, contrasting microclimates affect forage growth at catchment scales. However, documentation of microclimate-forage growth associations is limited, especially in Mediterranean regions experiencing pronounced climate change impacts. To better understand microclimate-forage growth linkages, we monitored forage productivity and rootzone soil temperature and moisture (0-15 and 15-30 cm) in 16 topographic positions in a 10-ha annual grassland catchment in California's Central Coast Range. Data were collected through two strongly contrasting growing seasons, a wet year (2016-17) with 287-mm precipitation and a dry year (2017-18) with 123-mm precipitation.Plant-available soil water storage (0-30 cm) was more than half full for most of the wet year; mean peak standing forage was 2790 kg ha −1 (range: 1597-4570 kg ha −1 ).The dry year had restricted plant-available water and mean peak standing forage was reduced to 970 kg ha −1 (range: 462-1496 kg ha −1 ). In the wet year, forage growth appeared energy limited (light and temperature): warmer sites produced more forage across a 3-4°C soil temperature gradient but late season growth was associated with moister sites spanning this energy gradient. In the dry year, the warmest topographic positions produced limited forage across a 10°C soil temperature gradient until late season rainfall in March. Linear models accounting for interactions between soil moisture and temperature explained about half of rapid, springtime forage growth variance. These findings reveal dynamic but clear microclimate-forage growth linkages in complex terrain, and thus, have implications for rangeland drought monitoring and dryland ecosystems modeling under climate change.

show abstract

“…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%

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

Curtis

Flint

Stern

2019

J American Water Resour Assoc

Self Cite

View full text Add to dashboard Cite

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.

show abstract

The impact of climate change uncertainty on California's vegetation and adaptation management

Cited by 52 publications

References 49 publications

Near‐future forest vulnerability to drought and fire varies across the western United States

Near‐future forest vulnerability to drought and fire varies across the western United States

Microclimate–forage growth linkages across two strongly contrasting precipitation years in a Mediterranean catchment

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

Contact Info

Product

Resources

About