Conservation planning at the intersection of landscape and climate change: brook trout in the Chesapeake Bay watershed

Landscape transcriptomic analysis detects thermal stress responses and potential adaptive variation in wild brook trout (Salvelinus fontinalis) during successive heatwaves

Extreme weather events, such as heatwaves, are becoming more frequent and intense as a result of climate change. Critically, such extreme weather events can be more important drivers of extirpation and selection than changes in annual or seasonal averages and they pose a particularly large threat to poikilothermic organisms. In this study, we evaluated the transcriptomic response of a coldwater adapted fish species, the eastern brook trout (Salvelinus fontinalis), to two successive heatwaves during July and August 2022. We sampled brook trout at eight time points from four streams (N = 116 fish), sequenced mRNA from gill samples using TagSeq, and quantified expression levels of 32,670 unique transcripts. Multivariate analyses found that overall expression patterns in response to water temperature change were similar among streams. These analyses further detected groups of genes involved in immune response and oxygen carrier activity that were upregulated and downregulated respectively at higher water temperatures. We also detected 43 genes that were differentially expressed at different time points and followed the same expression pattern during the two heatwaves. Of these genes, 42 covaried with water temperature and most (27, 62.8 %) exhibited responses that varied by stream. Some of the differentially expressed genes, including heat shock proteins and cold-inducible RNA binding proteins, have been widely linked to temperature responses in experimental studies, whereas other genes we identified have functions that have not been well-studied in relationship to temperature or have unknown functions. This study shows the utility of landscape transcriptomic approaches to identify important biological processes governing wild organismal responses to short-term stressors. The results of this study can guide future investigations to identify phenotypic and genetic diversity that contribute to adaptive responses to heatwaves and improve predictions of how populations will respond to future climate change.

Estimates of Effective Number of Breeders Identify Drivers of Decline in Mid-Atlantic Brook Trout Populations

Brook Trout (Salvelinus fontinalis) populations have experienced marked declines throughout their native range and are presently threatened due to isolation in small habitat fragments, land use changes, and climate change. The existence of numerous, spatially distinct populations poses substantial challenges for monitoring population status (e.g., abundance, recruitment, or occupancy). Genetic monitoring with estimates of effective number of breeders (N b) provides a potentially powerful metric to complement existing population monitoring, assessment, and prioritization. We estimated N b for 71 Brook Trout habitat units in mid-Atlantic region of the United States and obtained a mean N b of 73.2 (range 6.90-493). Our modeling approach tested whether N b estimates were sensitive to differences in habitat size, presence of non-native salmonids, base flow index, temperature, acidic precipitation, and indices of anthropogenic disturbance. We found significant support for three of our hypotheses including the positive influences of available habitat and base flow index and negative effect of temperature. Our results are consistent with presently observed and predicted future impacts of climate change on populations of this cold-water fish. Importantly, these findings support the use of N b in population assessments as an index of relative population status.

A novel quantitative framework for riverscape genetics

Riverscape genetics, which applies concepts in landscape genetics to riverine ecosystems, lack appropriate quantitative methods that address the spatial autocorrelation structure of linear stream networks and account for bidirectional geneflow. To address these challenges, we present a general framework for the design and analysis of riverscape genetic studies. Our framework starts with the estimation of pairwise genetic distance at sample sites and the development of a spatially structured ecological network (SSEN) on which riverscape covariates are measured. We then introduce the novel bidirectional geneflow in riverscapes (BGR) model that uses principles of isolation-by-resistance to quantify the effects of environmental covariates on genetic connectivity, with spatial covariance defined using simultaneous autoregressive models on the SSEN and the generalized Wishart distribution to model pairwise distance matrices arising through a random walk model of geneflow. We highlight the utility of this framework in an analysis of riverscape genetics for brook trout (Salvelinus fontinalis) in north central Pennsylvania, USA. Using the fixation index (F_ST ) as the measure of genetic distance, we estimated the effects of 12 riverscape covariates on geneflow by evaluating the relative support of eight competing BGR models. We then compared the performance of the top-ranked BGR model to results obtained from comparable analyses using multiple regression on distance matrices (MRM) and the program STRUCTURE. We found that the BGR model had more power to detect covariate effects, particularly for variables that were only partial barriers to geneflow and/or uncommon in the riverscape, making it more informative for assessing patterns of population connectivity and identifying threats to species conservation. This case study highlights the utility of our modeling framework over other quantitative methods in riverscape genetics, particularly the ability to rigorously test hypotheses about factors that influence geneflow and probabilistically estimate the effect of riverscape covariates, including stream flow direction. This framework is flexible across taxa and riverine networks, is easily executable, and provides intuitive results that can be used to investigate the likely outcomes of current and future management scenarios.

Disentangling the potential effects of land-use and climate change on stream conditions

Land-use and climate change are significantly affecting stream ecosystems, yet understanding of their long-term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land-use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin-wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land-use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project - Phase 5 (CMIP5) and a watershed-wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land-use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed-wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land-use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed-wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%-26.2% of stream kilometers, dependent on land-use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land-use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions.

Flow-Mediated Vulnerability of Source Waters to Elevated TDS in an Appalachian River Basin

Widespread salinization—and, in a broader sense, an increase in all total dissolved solids (TDS)—is threatening freshwater ecosystems and the services they provide (e.g., drinking water provision). We used a mixed modeling approach to characterize long-term (2010–2018) spatio-temporal variability in TDS within the Monongahela River basin and used this information to assess the extent and drivers of vulnerability. The West Fork River was predicted to exceed 500 mg/L a total of 133 days. Occurrence and duration (maximum = 28 days) of—and thus vulnerability to—exceedances within the West Fork River were driven by low flows. Projected decreases in mean daily discharge by ≤10 cfs resulted in an additional 34 days exceeding 500 mg/L. Consistently low TDS within the Tygart Valley and Cheat Rivers reduced vulnerability of the receiving Monongahela River to elevated TDS which was neither observed (maximum = 419 mg/L) nor predicted (341 mg/L) to exceed the secondary drinking water standard of 500 mg/L. Potential changes in future land use and/or severity of low-flow conditions could increase vulnerability of the Monongahela River to elevated TDS. Management should include efforts to increase assimilative capacity by identifying and decreasing sources of TDS. Upstream reservoirs could be managed toward low-flow thresholds; however, further study is needed to ensure all authorized reservoir purposes could be maintained.