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Lynn C. Sweet

Publications and source records attributed to Lynn C. Sweet.

4 recordsLinked to original sources
USGS2020

Validating climate‐change refugia: Empirical bottom‐up approaches to support management actions

Efforts to conserve biodiversity increasingly focus on identifying climate‐change refugia – areas relatively buffered from contemporary climate change over time that enable species persistence. Identification of refugia typically includes modeling the distribution of a species’ current habitat and then extrapolating that distribution given projected changes in temperature and precipitation, or by mapping topographic features that buffer species from regional climate extremes. However, the function of those hypothesized refugia must be validated (or challenged) with independent data not used in the initial identification of the refugia. Although doing so would facilitate the incorporation of climate‐change refugia into conservation and management decision making, a synthesis of validation methods is currently lacking. We reviewed the literature and defined four methods to test refugia predictions. We propose that such bottom‐up approaches can lead to improved protected‐area designations and on‐the‐ground management actions to reduce influences from non‐climate stressors within potential refugia.

Idaho, Montana, Wyoming↗
USGS2016

Shrinking windows of opportunity for oak seedling establishment in southern California mountains

Seedling establishment is a critical step that may ultimately govern tree species’ distribution shifts under environmental change. Annual variation in the location of seed rain and microclimates results in transient “windows of opportunity” for tree seedling establishment across the landscape. These establishment windows vary at fine spatiotemporal scales that are not considered in most assessments of climate change impacts on tree species range dynamics and habitat displacement. We integrate field seedling establishment trials conducted in the southern Sierra Nevada and western Tehachapi Mountains of southern California with spatially downscaled grids of modeled water-year climatic water deficit (CWD wy ) and mean August maximum daily temperature ( T max ) to map historical and projected future microclimates suitable for establishment windows of opportunity for Quercus douglasii , a dominant tree species of warm, dry foothill woodlands, and Q. kelloggii , a dominant of cooler, more mesic montane woodlands and forests. Based on quasi-binomial regression models, Q. douglasii seedling establishment is significantly associated with modeled CWD wy and to a lesser degree with modeled T max . Q. kelloggii seedling establishment is most strongly associated with T max and best predicted by a two-factor model including CWD wy and T max . Establishment niche models are applied to explore recruitment window dynamics in the western Tehachapi Mountains, where these species are currently widespread canopy dominants. Establishment windows are projected to decrease by 50–95%, shrinking locally to higher elevations and north-facing slopes by the end of this century depending on the species and climate scenario. These decreases in establishment windows suggest the potential for longer-term regional population declines of the species. While many additional processes regulate seedling establishment and growth, this study highlights the need to account for topoclimatic controls and interannual climatic variation when assessing how seedling establishment and colonization processes could be affected by climate change.

California↗
USGS2013

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

Ecological Processes↗