Skip to main content

Person

James Thorne

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 target emissions (RCP4.5). This comparison allows us to assess the ecosystem value of reaching targets to keep global temperature warming under 2°C. Using 350,719 km2 of natural lands in California, USA, and the mapped...
Abstract (from Ecological Society of America): Large, severe fires are becoming more frequent in many forest types across the western United States and have resulted in tree mortality across tens of thousands of hectares. Conifer regeneration in these areas is limited because seeds must travel long distances to reach the interior of large burned patches and establishment is jeopardized by increasingly hot and dry conditions. To better inform postfire management in low elevation forests of California, USA, we collected 5‐year postfire recovery data from 1,234 study plots in 19 wildfires that burned from 2004–2012 and 18 years of seed production data from 216 seed fall traps (1999–2017). We used this data in conjunction...
Categories: Publication; Types: Citation
Postfire Spatial Conifer Restoration Planning Tool (POSCRPT) R package (and web version) predicts the probability of post-fire conifer regeneration for fire data supplied by the user. The predictive model was fit using presence/absence data collected five years after wildfire, from 1,234 4.4m radius plots (60m2), spanning 19 wildfires in California. Please refer to Stewart et al. (2020) for more details. The poscrptR tool is designed to simplify the process of predicting post-fire conifer regeneration under different precipitation and seed production scenarios. The app was designed to use Rapid Assessment of Vegetative Condition (RAVG) data inputs. The RAVG website has both RdNBR and fire perimeter data sets...
Large, severe fires are becoming more frequent in many forest types across the western United States and have resulted in tree mortality across tens of thousands of hectares. Conifer regeneration in these areas is limited because seeds must travel long distances to reach the interior of large burned patches and establishment is jeopardized by increasingly hot and dry conditions. To better inform postfire management in low elevation forests of California, USA, we collected 5‐yr postfire recovery data from 1,234 study plots in 19 wildfires that burned from 2004–2012 and 18 yrs of seed production data from 216 seed fall traps (1999–2017). We used these data in conjunction with spatially extensive climate, topography,...
Categories: Publication; Types: Citation
thumbnail
Post-Fire Conifer Regeneration Under a Warming Climate: Will Severe Fire Be a Catalyst for Forest Loss?
The Southwest U.S. is experiencing hotter droughts, which are contributing to more frequent, severe wildfires. These droughts also stress vegetation, which can make it more difficult for forests to recover after fire. Forest regeneration in burned areas may be limited because seeds have to travel long distances to recolonize, and when they do arrive, conditions are often unfavorably hot and dry. Conifer forests in the region have demonstrated particular difficulty in recovering after fires, and in some cases have transformed into other ecosystem types, such as deciduous-dominated forests or grasslands. Such ecological transformations have implications not only for the plants and animals that depend on conifer forests...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.