Downstream Warming and Headwater Acidity May Diminish Coldwater Habitat in Southern Appalachian Mountain Streams

Stream-dwelling species in the U.S. southern Appalachian Mountains region are particularly vulnerable to climate change and acidification. The objectives of this study were to quantify the spatial extent of contemporary suitable habitat for acid- and thermally sensitive aquatic species and to forecast future habitat loss resulting from expected temperature increases on national forest lands in the southern Appalachian Mountain region. The goal of this study was to help watershed managers identify and assess stream reaches that are potentially vulnerable to warming, acidification, or both. To our knowledge, these results represent the first regional assessment of aquatic habitat suitability with respect to the combined effects of stream water temperature and acid-base status in the United States. Statistical models were developed to predict July mean daily maximum water temperatures and air-water temperature relations to determine potential changes in future stream water temperatures. The length of stream considered suitable habitat for acid- and thermally sensitive species, based on temperature and acid neutralizing capacity thresholds of 20°C and 50 μeq/L, was variable throughout the national forests considered. Stream length displaying temperature above 20°C was generally more than five times greater than the length predicted to have acid neutralizing capacity below 50 μeq/L. It was uncommon for these two stressors to occur within the same stream segment. Results suggested that species’ distributional shifts to colder, higher elevation habitats under a warming climate can be constrained by acidification of headwater streams. The approach used in this study can be applied to evaluate climate change impacts to stream water resources in other regions

Reduced fire severity offers near-term buffer to climate-driven declines in conifer resilience across the western United States

Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration. © 2023 the Author(s)

Fuel Treatment Effectiveness In The Context of Landform, Vegetation, and Large, Wind-Driven Wildfires

Large wildfires (\u3e50,000 ha) are becoming increasingly common in semi-arid landscapes of the western United States. Although fuel reduction treatments are used to mitigate potential wildfire effects, they can be overwhelmed in wind-driven wildfire events with extreme fire behavior. We evaluated drivers of fire severity and fuel treatment effectiveness in the 2014 Carlton Complex, a record-setting complex of wildfires in north-central Washington State. Across varied topography, vegetation and distinct fire progressions, we used a combination of simultaneous autoregression (SAR) and random forest (RF) approaches to model drivers of fire severity and evaluated how fuel treatments mitigated fire severity. Predictor variables included fuel treatment type, time since treatment, topographic indices, vegetation and fuels, and weather summarized by progression interval. We found that the two spatial regression methods are generally complementary and are instructive as a combined approach for landscape analyses of fire severity. SAR improves upon traditional linear models by incorporating information about neighboring pixel burn severity, which avoids type I errors in coefficient estimates and incorrect inferences. RF modeling provides a flexible modeling environment capable of capturing complex interactions and non-linearities while still accounting for spatial autocorrelation through the use of spatially explicit predictor variables. All treatment areas burned with higher proportions of moderate and high severity fire during early fire progressions, but thin and underburn, underburn only, and past wildfires were more effective than thin-only and thin and pile burn treatments. Treatment units had much greater percentages of unburned and low severity area in later progressions that burned under milder fire weather conditions, and differences between treatments were less pronounced. Our results provide evidence that strategic placement of fuels reduction treatments can effectively reduce localized fire spread and severity even under severe fire weather. During wind-driven fire spread progressions, fuel treatments that were located on leeward slopes tended to have lower fire severity than treatments located on windward slopes. As fire and fuels managers evaluate options for increasing landscape resilience to future climate change and wildfires, strategic placement of fuel treatments may be guided by retrospective studies of past large wildfire events

Assessing impacts of sulfur deposition on aquatic ecosystems: A decision support system for the Southern Appalachians

Abstract With climate change and ongoing impacts from human development and resource extraction, US federal land management agencies are acutely concerned with managing for healthy aquatic ecosystems in the Southern Appalachian Mountain (SAM) Region. Here, we describe development of a spatial decision support application to assess the biological and ecological impacts of atmospheric S and N deposition on aquatic ecosystems of the region. We first summarize foundational published work to predict continuous maps of surface water acid neutralizing capacity (ANC) and soil base cation weathering (BCw). We use the predicted ANC and BCw maps to estimate steady‐state critical loads (CLs) of atmospheric S and N deposition. We included estimated CLs of atmospheric N to get a complete picture of CLs and potential exceedances. We then present a logic‐based decision support model for assessing effects of S and N deposition based on statistically modeled stream ANC and CL exceedance. The model is easily modified for continuous monitoring of CL exceedance patterns as new S and N deposition and ANC data become available. We present mapped model results for the SAM study area and an important subset of the region, the Great Smoky Mountains National Park. ANC modeling results revealed that predicted acid sensitivity was spatially variable, with areas of relatively low stream ANC (<50 μeq · L−1) and soil BCw (<50 meq · m−2 · year−1) predominantly found in certain critical areas. Within the Great Smoky Mountains National Park, evidence for S CL exceedance based on an ANC criterion of 50 μeq · L−1 was strong at locations where ambient S deposition was at least two times the CL. We also predicted likely impacts of CL exceedances on aquatic insect species richness and native fish abundance. Responses for insect species richness and fish impact showed variability similar to CL exceedance, with increasing impact positively correlated with elevation. Finally, we discuss ways that the decision support system can be used to prioritize management across the region

ANC and Stream Temperature Predictions

<p>This dataset contains stream water acid neutralizing capacity (ANC) and temperature predictions for southern Appalachian Mountain streams.</p

Downstream Warming and Headwater Acidity May Diminish Coldwater Habitat in Southern Appalachian Mountain Streams

<div><p>Stream-dwelling species in the U.S. southern Appalachian Mountains region are particularly vulnerable to climate change and acidification. The objectives of this study were to quantify the spatial extent of contemporary suitable habitat for acid- and thermally sensitive aquatic species and to forecast future habitat loss resulting from expected temperature increases on national forest lands in the southern Appalachian Mountain region. The goal of this study was to help watershed managers identify and assess stream reaches that are potentially vulnerable to warming, acidification, or both. To our knowledge, these results represent the first regional assessment of aquatic habitat suitability with respect to the combined effects of stream water temperature and acid-base status in the United States. Statistical models were developed to predict July mean daily maximum water temperatures and air-water temperature relations to determine potential changes in future stream water temperatures. The length of stream considered suitable habitat for acid- and thermally sensitive species, based on temperature and acid neutralizing capacity thresholds of 20°C and 50 μeq/L, was variable throughout the national forests considered. Stream length displaying temperature above 20°C was generally more than five times greater than the length predicted to have acid neutralizing capacity below 50 μeq/L. It was uncommon for these two stressors to occur within the same stream segment. Results suggested that species’ distributional shifts to colder, higher elevation habitats under a warming climate can be constrained by acidification of headwater streams. The approach used in this study can be applied to evaluate climate change impacts to stream water resources in other regions.</p></div

Streams located in the Pisgah Ranger District of the Pisgah National Forest, which comprises 2.8% of the stream length in the study region, having predicted ANC < 50 μeq/L (red), temperature > 20°C (orange), or suitable habitat with respect to both ANC and temperature (blue).

<p>Modeled habitat suitability results are shown for a) ambient July mean maximum daily air temperature (MDAT), and future increases in July mean MDAT of b) 2°C, and c) 4°C. The suitable stream habitat under contemporary July MDAT that is located in the west-central portion of the ranger district is predominantly located in the Shining Rock Wilderness.</p

Coefficients and descriptive statistics associated with the logistic regression model for predicting maximum daily stream water temperature (MDST) sensitivity (high/low) to changes in maximum daily air temperature (MDAT).

<p>Coefficients and descriptive statistics associated with the logistic regression model for predicting maximum daily stream water temperature (MDST) sensitivity (high/low) to changes in maximum daily air temperature (MDAT).</p

Coefficients and descriptive statistics associated with the multiple linear regression model¹ for continuous estimates of the strength of maximum daily stream temperature (MDST) and maximum daily air temperature (MDAT) correlations.

<p>¹ This model was only applied to reaches for which MDST was considered to have high sensitivity to increases in MDAT based on the logistic regression model (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134757#pone.0134757.t003" target="_blank">Table 3</a>).</p><p>Coefficients and descriptive statistics associated with the multiple linear regression model<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134757#t004fn001" target="_blank">¹</a> for continuous estimates of the strength of maximum daily stream temperature (MDST) and maximum daily air temperature (MDAT) correlations.</p