bioRxiv Science⌕ Search

Biology subjects

Shriver, R. K.

Publications and source records attributed to Shriver, R. K..

2 recordsLinked to original sources

The rate of ecological acclimation is the dominant uncertainty in long-term projections of a key ecosystem service

Rapid climate change may exceed ecosystems capacity to respond through processes including phenotypic plasticity, compositional turnover and evolutionary adaption. However, research predicting impacts of climate change on ecosystem services rarely consider this rate of "ecosystem acclimation." Combining statistical models fit to historical climate data and remotely-sensed estimates of herbaceous productivity with an ensemble of climate models, we demonstrate that assumptions concerning acclimation rates are a dominant source of uncertainty: models assuming minimal acclimation project widespread decreases in forage production in the western US by 2100, while models assuming that acclimation keeps pace with climate change project widespread forage increases. Uncertainty related to ecosystem acclimation is larger than uncertainties from variation among climate models or emissions pathways. A better understanding of ecosystem acclimation is essential to improve long-term forecasts of ecosystem services, and shows that management to facilitate ecosystem acclimation may be necessary to maintain ecosystem services at historical baselines.

ecology↗

Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using range-wide monitoring data

Climate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species (Pinus edulis and Juniperus osteosperma), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that warming and drying conditions generally lead to declines in recruitment and survival, but there were some idiosyncrasy in the strength of responses across species. Climate conditions lead to vulnerable regions, such as Pinus edulis in N. Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.

ecology↗