Publications by authors named "R DeRose"

Given the importance of climate in shaping species' geographic distributions, climate change poses an existential threat to biodiversity. Climate envelope modeling, the predominant approach used to quantify this threat, presumes that individuals in populations respond to climate variability and change according to species-level responses inferred from spatial occurrence data-such that individuals at the cool edge of a species' distribution should benefit from warming (the "leading edge"), whereas individuals at the warm edge should suffer (the "trailing edge"). Using 1,558 tree-ring time series of an aridland pine () collected at 977 locations across the species' distribution, we found that trees everywhere grow less in warmer-than-average and drier-than-average years.

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Climate change-triggered forest die-off is an increasing threat to global forests and carbon sequestration but remains extremely challenging to predict. Tree growth resilience metrics have been proposed as measurable proxies of tree susceptibility to mortality. However, it remains unclear whether tree growth resilience can improve predictions of stand-level mortality.

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Polyploidy, the expression of more than two sets of chromosomes, is common in plants, and is thought to influence plant trait expression and drive plant species evolution. The degree to which polyploidy influences interactions among physiological processes such as growth and defense in natural populations through its effect on phenotypic variability is poorly understood. We link broad plant genotypic features (including polyploidy) to phenotypic expression of growth and chemical defense in natural populations of quaking aspen (Populus tremuloides) to examine patterns in resource allocation that might drive growth-defense tradeoffs.

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Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and-ultimately-the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality).

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Robust ecological forecasting of tree growth under future climate conditions is critical to anticipate future forest carbon storage and flux. Here, we apply three ingredients of ecological forecasting that are key to improving forecast skill: data fusion, confronting model predictions with new data, and partitioning forecast uncertainty. Specifically, we present the first fusion of tree-ring and forest inventory data within a Bayesian state-space model at a multi-site, regional scale, focusing on Pinus ponderosa var.

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