Biology subjects

Abatzoglou, J. T.

Publications and source records attributed to Abatzoglou, J. T..

3 recordsLinked to original sources

bioRxiv2026

Summertime Fog and Dew Impacts on Vegetation Depend on Aridity

Rainfall and vapor pressure deficit (VPD) are well-studied hydrological variables that largely determine aboveground net primary production (ANPP) in most ecosystems. Meanwhile, the impacts of another important part of the hydrologic cycle, non-rainfall water from fog and dew, remain poorly understood at the ecosystem level. To fill this gap, we used meteorological variables measured at weather stations along with satellite-derived vegetation greenness data from surrounding areas to examine how fog and dew frequency affect summer plant growth across the contiguous United States. Our analysis shows that, even after accounting for precipitation, VPD, and land-cover type, fog and, more so, dew enhanced vegetation productivity in water-limited regions. In contrast, non-rainfall water had a neutral or negative impact on plant growth in humid regions, with fog showing the strongest and most widespread negative effects. Taken together, our findings reveal that summertime non-rainfall water has differential effects on vegetation that are largely determined by ecosystem-level water availability. These aridity-dependent effects of fog and dew should be considered in future ecological and agricultural studies and in assessments of projected climate impacts on vegetation.

ecology↗

bioRxiv2021

Climate risks to carbon sequestration in US forests

Forests are currently a substantial carbon sink globally. Many climate change mitigation strategies rely on forest preservation and expansion, but the effectiveness of these approaches hinges on forests sequestering carbon for centuries despite anthropogenic climate change. Yet climate-driven disturbances pose critical risks to the long-term stability of forest carbon. We quantify the key climate drivers that fuel wildfire, drought, and insects, for the United States over 1984-2018 and project future disturbance risks over the 21st century. We find that current risks are widespread and projected to increase across different emission scenarios by a factor of 4-14 for fire and 1.3-1.8 for drought and insects. Our results provide insights for carbon cycle modeling, conservation, and climate policy, underscoring the escalating climate risks facing forests and the need for emissions reductions to mitigate climate change.

ecology↗

bioRxiv2018

Understanding and predicting extreme wildfires in the contiguous United States

Wildfires are becoming more frequent in parts of the globe, but predicting where and when wildfires occur remains difficult. To predict wildfire extremes across the contiguous United States, we integrate a 30 year wildfire record with meteorological and housing data in spatiotemporal Bayesian statistical models with spatially varying nonlinear effects. We compared different distributions for the number and sizes of large fires to generate a posterior predictive distribution based on finite sample maxima for extreme events (the largest fires over bounded spatiotemporal domains). A zero-inflated negative binomial model for fire counts and a lognormal model for burned areas provided the best performance. This model attains 99% interval coverage for the number of fires and 93% coverage for fire sizes over a six year withheld data set. Dryness and air temperature strongly predict extreme wildfire probabilities. Housing density has a hump-shaped relationship with fire occurrence, with more fires occurring at intermediate housing densities. Statistically, these drivers affect the chance of an extreme wildfire in two ways: by altering fire size distributions, and by altering fire frequency, which influences sampling from the tails of fire size distributions. We conclude that recent extremes should not be surprising, and that the contiguous United States may be on the verge of even larger wildfire extremes.

ecology↗