Climate change simulations predict altered biotic response in a thermally heterogeneous stream system

The context dependency of fish-habitat associations in separated karst ecoregions

Fish populations may be isolated via natural conditions in geographically separated ecoregions. Although reconnecting these populations is not a management goal, we need to understand how these populations persist across landscapes to develop meaningful conservation actions, particularly for species occupying sensitive karst ecosystems. Our study objective was to determine the physicochemical factors related to the occurrence of four spring-associated fishes. Arbuckle Uplift and Ozark Highlands ecoregions, USA. We used a hierarchical approach to identify habitat relationships at multiple spatial scales. We collected detection data using snorkeling and seining. We examined the physicochemical relationships related to the detection and occurrence of four spring-associated fishes using occupancy modeling in a Bayesian framework. We found physicochemical relationships that differed and were similar between ecoregions for several fishes. For three species, we found different water temperature relationships between ecoregions. Smallmouth bass were ubiquitous in their use of drainage areas in the Ozark Highlands but only associated with the lower network of the Arbuckle Uplift. There were several mirrored relationships between ecoregions, including an interaction between residual pool depth and water temperature, where sites with deeper pools were more likely to be occupied during warmer water temperatures. There were single-species occurrence relationships with percent vegetation and percent agriculture. Lastly, snorkeling was a more efficient sampling method compared to seining for all fishes. Our results indicate stream temperature mitigation may be possible via the maintenance of key channel morphologies, and we identify shared stressors between ecoregions. Channel mitigation to maintain reaches with deeper pools may be an important strategy for maintaining thermal refugia, particularly when considering climate change. Identifying the mechanistic underpinning of other multiscale ecological relationships would be helpful to discern if some of the different ecoregion relationships represent warning signals or interactions with unmeasured biotic or abiotic factors.

Physiological impacts of temperature variability and climate warming in hellbenders (Cryptobranchus alleganiensis)

Cold-adapted hellbender salamanders that inhabit cool mountain streams are expected to fare poorly under warmer projected climate scenarios. This study investigated the physiological consequences of long-term, naturalistic temperature variation on juvenile hellbenders under simulated current and warmer (+1.6 C) climates vs. controlled steady temperatures. Mean temperature and temperature variability were both important predictors of growth as indicated by monthly body mass change (%), stress as indicated by neutrophil:lymphocyte (N:L) ratio and bacteria-killing ability of blood. Cold exposure in hellbenders was associated with weight loss, increased N:L ratios and reduced Escherichia coli killing ability of blood, and these effects were less pronounced under a warmer climate scenario. These observations suggest that cold periods may be more stressful for hellbenders than previously understood. Growth rates peaked in late spring and late fall around 14-17°C. Hellbenders experiencing warmer simulated climates retained body condition better in winter, but this was counter-balanced by a prolonged lack of growth in the 3-month summer period leading up to the fall breeding season where warmer simulated conditions resulted in an average loss of -0.6% body mass/month, compared to a gain +1.5% body mass/month under current climate scenario. Hellbenders can physiologically tolerate projected warmer temperatures and temperature fluctuations, but warmer summers may cause animals to enter the fall breeding season with a caloric deficit that may have population-level consequences.

Linking multiple aspects of thermal performance to explore the potential for thermal resource partitioning between a native and an invasive crayfish

Ecologists require standardized, ecologically relevant information on the thermal ecology of aquatic ectotherms to address growing concerns related to changing climates, altered habitats, and introduced species. We measured multiple thermal endpoints to investigate potential for establishment of the invasive Ringed Crayfish (Faxonius neglectus) in thermally heterogeneous habitat of the narrowly distributed endemic Coldwater Crayfish (Faxonius eupunctus). For each species, we examined the relationships between thermal endpoints at the cellular and organismal levels. We then compared results between the two species to gain insight as to the generality of linkages between cellular and organismal-level endpoints, as well as the potential for thermal niche separation between the native and potential invader. At the cellular level, we found no differences in the temperature for maximum activity of electron transport system enzymes (ETS_max) between species. At the organismal level, F. neglectus preferred significantly warmer temperatures than F. eupunctus, but this difference was small (1.3 °C) and likely to have only limited biological significance. The critical thermal maximum (CTM) did not differ between species. For both species, the thermal performance curve for ETS enzyme activity served as a useful framework to link thermal endpoints and estimate the transition from optimal to stressful temperatures - organismal thermal preference and optimal temperature estimates consistently fell below ETS_max whereas CTM estimates fell above ETS_max. Taken together, the strong similarities in thermal endpoint patterns between the two species suggest habitats thermally suitable for the native F. eupunctus will also be thermally available to expanding populations of F. neglectus, thereby increasing the opportunity for negative interactions and population effects if F. neglectus invades one of the few remaining, uninvaded, critical habitats of F. eupunctus.

Use of Multiple Temperature Logger Models Can Alter Conclusions

Remote temperature loggers are often used to measure water temperatures for ecological studies and by regulatory agencies to determine whether water quality standards are being maintained. Equipment specifications are often given a cursory review in the methods; however, the effect of temperature logger model is rarely addressed in the discussion. In a laboratory environment, we compared measurements from three models of temperature loggers at 5 to 40 °C to better understand the utility of these devices. Mean water temperatures recorded by logger models differed statistically even for those with similar accuracy specifications, but were still within manufacturer accuracy specifications. Maximum mean temperature difference between models was 0.4 °C which could have regulatory and ecological implications, such as when a 0.3 °C temperature change triggers a water quality violation or increases species mortality rates. Additionally, precision should be reported as the overall precision (including a consideration of significant digits) for combined model types which in our experiment was 0.7 °C, not the ≤0.4 °C for individual models. Our results affirm that analyzing data collected by different logger models can result in potentially erroneous conclusions when <1 °C difference has regulatory compliance or ecological implications and that combining data from multiple logger models can reduce the overall precision of results.

Relationship between Water Temperature of Polish Rivers and Large-Scale Atmospheric Circulation

The objective of the paper consisted in determining the effect of macroscale types of NAO, AO, EA, EAWR, SCAND, and AMO atmospheric circulation on changes in water temperature in Polish rivers. The study has made use of a broad body of hydrometeorological materials covering daily water temperature values for 96 water gauge stations located on 53 rivers and air temperature values for 43 meteorological stations. Percentage shares of positive and negative coefficients of correlation of annual, seasonal, and monthly circulation type indices with air and river water temperature were determined, demonstrating the character of teleconnection. Determinations were made of water temperature deviations in positive and negative phases of the analyzed indices from average values from the years 1971–2015, and their statistical significance ascertained. Research has shown that relations between the temperature of river waters in Poland and macroscale circulation types are not strong, however they are noticeable, sometimes even statistically significant, and both temporally and spatially diverse. NAO, AO, EA, and AMO indices are characterized by a generally positive correlation with temperature, whereas SCAND and EWAR indices are characterized by a negative correlation. Research showed a varying impact of types of atmospheric circulation, with their effectiveness increasing in the winter season. The strongest impact on temperature was observed for the positive and negative NAO and AO phases, when deviations of water temperature from average values are correspondingly higher (up to 1.0 °C) and lower (by a maximum of 1.5 °C), and also for the positive and negative SCAND phases, when water temperature are correspondingly lower (by a maximum of 0.8 °C) and higher (by 1.2 °C) than average values. The strongest impact on water temperature in summer, mainly in July, was observed for AMO. The results point to the complexity of processes determining the thermal regime of rivers and to the possibility of additional factors—both regional and local—exerting an influence on their temporal and spatial variability.

A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade(-1)) and a widening of the synchronized period (29 d decade(-1)). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.