Publications by authors named "John D Shaw"

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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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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Estimates of the percentage of species "committed to extinction" by climate change range from 15% to 37%. The question is whether factors other than climate need to be included in models predicting species' range change. We created demographic range models that include climate vs.

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Article Synopsis
  • Trees have a distinctive ability to recall past climate conditions, known as 'climatic memory,' which affects their growth over time, particularly under stress like drought.
  • The study focused on tree species in the southwestern USA, measuring their growth and non-structural carbohydrate (NSC) levels to understand how previous climate impacts their current growth.
  • Findings indicate that different species respond uniquely to climatic memory, with effects on drought recovery and resilience linked to their NSC concentrations, suggesting that these physiological traits play a key role in how trees adapt to changing climates.
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Identifying the signs and symptoms of pathogens, insects, and other biotic and abiotic agents provides valuable information about the absolute and relative impacts of different types of damage across the forest landscape. In the USA, damage collection protocols have been included in various forms since the initiation of state-level forest surveys in the early twentieth century; however, changes in the protocols over time have made it difficult for the data to be used to its full potential. This article outlines differences in protocols across inventory regions, changes in protocols over time, and limitations and utility of the data so that those interested in using the US national forest inventory database will better understand what data are available and how they have been and can be used.

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A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree-ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space-for-time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today.

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Understanding the driving mechanisms behind existing patterns of vegetation hydraulic traits and community trait diversity is critical for advancing predictions of the terrestrial carbon cycle because hydraulic traits affect both ecosystem and Earth system responses to changing water availability. Here, we leverage an extensive trait database and a long-term continental forest plot network to map changes in community trait distributions and quantify "trait velocities" (the rate of change in community-weighted traits) for different regions and different forest types across the United States from 2000 to the present. We show that diversity in hydraulic traits and photosynthetic characteristics is more related to local water availability than overall species diversity.

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Climate-tree growth relationships recorded in annual growth rings have recently been the basis for projecting climate change impacts on forests. However, most trees and sample sites represented in the International Tree-Ring Data Bank (ITRDB) were chosen to maximize climate signal and are characterized by marginal growing conditions not representative of the larger forest ecosystem. We evaluate the magnitude of this potential bias using a spatially unbiased tree-ring network collected by the USFS Forest Inventory and Analysis (FIA) program.

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Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact.

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Climate change is expected to drive increased tree mortality through drought, heat stress, and insect attacks, with manifold impacts on forest ecosystems. Yet, climate-induced tree mortality and biotic disturbance agents are largely absent from process-based ecosystem models. Using data sets from the western USA and associated studies, we present a framework for determining the relative contribution of drought stress, insect attack, and their interactions, which is critical for modeling mortality in future climates.

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We document high rates of triploidy in aspen (Populus tremuloides) across the western USA (up to 69% of genets), and ask whether the incidence of triploidy across the species range corresponds with latitude, glacial history (as has been documented in other species), climate, or regional variance in clone size. Using a combination of microsatellite genotyping, flow cytometry, and cytology, we demonstrate that triploidy is highest in unglaciated, drought-prone regions of North America, where the largest clone sizes have been reported for this species. While we cannot completely rule out a low incidence of undetected aneuploidy, tetraploidy or duplicated loci, our evidence suggests that these phenomena are unlikely to be significant contributors to our observed patterns.

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