Summary
1. Ecologists have long sought to distinguish relationships that are general from those that are idiosyncratic to a narrow range of conditions. Conventional methods of model validation and ...selection assess in‐ or out‐of‐sample prediction accuracy but do not assess model generality or transferability, which can lead to overestimates of performance when predicting in other locations, time periods or data sets.
2. We propose an intuitive method for evaluating transferability based on techniques currently in use in the area of species distribution modelling. The method involves cross‐validation in which data are assigned non‐randomly to groups that are spatially, temporally or otherwise distinct, thus using heterogeneity in the data set as a surrogate for heterogeneity among data sets.
3. We illustrate the method by applying it to distribution modelling of brook trout (Salvelinus fontinalis Mitchill) and brown trout (Salmo trutta Linnaeus) in western United States. We show that machine‐learning techniques such as random forests and artificial neural networks can produce models with excellent in‐sample performance but poor transferability, unless complexity is constrained. In our example, traditional linear models have greater transferability.
4. We recommend the use of a transferability assessment whenever there is interest in making inferences beyond the data set used for model fitting. Such an assessment can be used both for validation and for model selection and provides important information beyond what can be learned from conventional validation and selection techniques.
Landfills provide seasonally reliable food resources to many bird species, including those perceived to be pest or invasive species. However, landfills often contain multiple habitat types that could ...attract diverse species, including those of conservation concern. To date, little is known about the characteristics and composition of bird communities at landfills relative to local and regional pools. Here we used the community science database eBird to extract avian species occurrence data at landfills across the US. We compared species richness and community similarity across space in comparison to similarly-sampled reference sites, and further quantified taxonomic and dietary traits of bird communities at landfills. While landfills harbored marginally lower species richness than reference sites (respective medians of 144 vs 160), landfill community composition, and its turnover across space, were similar to reference sites. Consistent with active waste disposal areas attracting birds, species feeding at higher trophic levels, especially gulls, were more frequently observed at landfills than reference sites. However, habitat specialists including two declining grassland species, Eastern Meadowlark (Sturnella magna) and Savannah Sparrow (Passerculus sandwichensis), as well as migratory waterfowl, were more frequently encountered at landfills than reference sites. Together, these results suggest that landfills harbor comparable avian diversity to neighboring sites, and that habitats contained within landfill sites can support species of conservation concern. As covered landfills are rarely developed or forested, management of wetlands and grasslands at these sites represents an opportunity for conservation.
Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive ...temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency‐specific purposes, collectively these efforts constitute a massive distributed sensing array that generates an untapped wealth of data. Using the framework provided by the National Hydrography Dataset, we organized temperature records from dozens of agencies in the western U.S. to create the NorWeST database that hosts >220,000,000 temperature recordings from >22,700 stream and river sites. Spatial‐stream‐network models were fit to a subset of those data that described mean August water temperatures (AugTw) during 63,641 monitoring site‐years to develop accurate temperature models (r2 = 0.91; RMSPE = 1.10°C; MAPE = 0.72°C), assess covariate effects, and make predictions at 1 km intervals to create summer climate scenarios. AugTw averaged 14.2°C (SD = 4.0°C) during the baseline period of 1993–2011 in 343,000 km of western perennial streams but trend reconstructions also indicated warming had occurred at the rate of 0.17°C/decade (SD = 0.067°C/decade) during the 40 year period of 1976–2015. Future scenarios suggest continued warming, although variation will occur within and among river networks due to differences in local climate forcing and stream responsiveness. NorWeST scenarios and data are available online in user‐friendly digital formats and are widely used to coordinate monitoring efforts among agencies, for new research, and for conservation planning.
Key Points
The NorWeST stream temperature database was developed from data contributed by >100 agencies in the western U.S.
Scenarios created from the database for 343,000 km of streams and rivers indicate a warming trend of 0.17° C/decade occurred during 1976–2015
The geospatial stream analysis tools developed for the NorWeST project have broad utility for many types of stream data throughout the U.S.
The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal ...retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.
Temperature profoundly affects ecology, a fact ever more evident as the ability to measure thermal environments increases and global changes alter these environments. The spatial structure of ...thermalscapes is especially relevant to the distribution and abundance of ectothermic organisms, but the ability to describe biothermal relationships at extents and grains relevant to conservation planning has been limited by small or sparse data sets. Here, we combine a large occurrence database of >23000 aquatic species surveys with stream microclimate scenarios supported by an equally large temperature database for a 149000-km mountain stream network to describe thermal relationships for 14 fish and amphibian species. Species occurrence probabilities peaked across a wide range of temperatures (7.0–18.8°C) but distinct warm- or cold-edge distribution boundaries were apparent for all species and represented environments where populations may be most sensitive to thermal changes. Warm-edge boundary temperatures for a native species of conservation concern were used with geospatial data sets and a habitat occupancy model to highlight subsets of the network where conservation measures could benefit local populations by maintaining cool temperatures. Linking that strategic approach to local estimates of habitat impairment remains a key challenge but is also an opportunity to build relationships and develop synergies between the research, management, and regulatory communities. As with any data mining or species distribution modeling exercise, care is required in analysis and interpretation of results, but the use of large biological data sets with accurate microclimate scenarios can provide valuable information about the thermal ecology of many ectotherms and a spatially explicit way of guiding conservation investments.
Broad-scale studies of climate change effects on freshwater species have focused mainly on temperature, ignoring critical drivers such as flow regime and biotic interactions. We use downscaled ...outputs from general circulation models coupled with a hydrologic model to forecast the effects of altered flows and increased temperatures on four interacting species of trout across the interior western United States (1.01 million km2), based on empirical statistical models built from fish surveys at 9,890 sites. Projections under the 2080s A1B emissions scenario forecast a mean 47% decline in total suitable habitat for all trout, a group of fishes of major socioeconomic and ecological significance. We project that native cutthroat trout Oncorhynchus clarkii, already excluded from much of its potential range by nonnative species, will lose a further 58% of habitat due to an increase in temperatures beyond the species’ physiological optima and continued negative biotic interactions. Habitat for nonnative brook trout Salvelinus fontinalis and brown trout Salmo trutta is predicted to decline by 77% and 48%, respectively, driven by increases in temperature and winter flood frequency caused by warmer, rainier winters. Habitat for rainbow trout, Oncorhynchus mykiss, is projected to decline the least (35%) because negative temperature effects are partly offset by flow regime shifts that benefit the species. These results illustrate how drivers other than temperature influence species response to climate change. Despite some uncertainty, large declines in trout habitat are likely, but our findings point to opportunities for strategic targeting of mitigation efforts to appropriate stressors and locations.
In recognition of the influence of flow on riverine habitats and organisms, stream ecologists have devoted considerable effort to the development of quantitative predictive relationships describing ...ecological responses to flow variability, i.e. flow‐ecology relationships.
Methods used to generate flow‐ecology relationships can be thought of as a continuum bookended by pure states approaches on one end and by rates approaches on the other. In pure states approaches, the ecological response is a snapshot of a condition or property (i.e. a state) derived from a single measurement in time. In contrast, ecological responses in rates approaches reflect temporal change (i.e. a rate) and are thus reliant on repeated measurements made over time.
Here, we elaborate on the fundamental characteristics of different approaches (pure states, rates and an intermediate approach we call repeated states) for generating flow‐ecology relationships, examine how commonly the different approaches are used in the flow‐ecology literature, conduct an independent analysis to illustrate the different outcomes achieved by applying repeated‐states and rates approaches using a dataset for stream fish diversity in relation to flow magnitude, and identify some of the different ways ecologists are applying rates approaches in flow ecology.
Our literature review revealed that repeated‐states approaches (53% of reviewed studies) were used far more commonly than either pure states (19%) or rates (12%) approaches to generate flow‐ecology relationships. The remaining hybrid studies (17%) used both state and rate responses, and thus also relied on repeated measurements over time.
Despite frequent collection of data suitable for rates approaches, flow‐ecology relationships have generally been developed using states approaches that relate changes in ecological states to different long‐term average flow conditions, rather than to specific flow sequences over much shorter time intervals. Such flow‐ecology relationships cannot generate temporally specific predictions of ecological responses to changing flow conditions (i.e. the expected change in state following a specific flow sequence), nor can they describe demographic processes underlying observed changes. While there are different scenarios in which a pure or repeated‐states approach would be useful, more frequent use of rates approaches would increase our ability to test flow‐ecology hypotheses and our mechanistic understanding of flow‐ecology relationships.
Researchers have developed methods to account for imperfect detection of species with either occupancy (presence—absence) or count data using replicated sampling. We show how these approaches can be ...combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.
Reconciling the degree to which ecological processes are generalizable among taxa and ecosystems, or contingent on the identity of interacting species, remains a critical challenge in ecology. ...Ecological stoichiometry (EST) and metabolic theory of ecology (MTE) are theoretical approaches used to evaluate how consumers mediate nutrient dynamics and energy flow through ecosystems. Recent theoretical work has explored the utility of these theories, but empirical tests in species-rich ecological communities remain scarce. Here we use an unprecedented dataset collected from fishes and dominant invertebrates ( n = 900) in a diverse subtropical coastal marine community (50 families, 72 genera, 102 species; body mass range: 0.04–2,597 g) to test the utility of EST and MTE in predicting excretion rates of nitrogen (E N), phosphorus (E P), and their ratio (E NP). Body mass explained a large amount of the variation in E N and E P but not E NP. Strong evidence in support of the MTE 3/4 allometric scaling coefficient was found for E P, and for E N only after accounting for variation in excretion rates among taxa. In all cases, including taxonomy in models substantially improved model performance, highlighting the importance of species identity for this ecosystem function. Body nutrient content and trophic position explained little of the variation in E N, E P, or E NP, indicating limited applicability of basic predictors of EST. These results highlight the overriding importance of MTE for predicting nutrient flow through organisms, but emphasize that these relationships still fall short of explaining the unique effects certain species can have on ecological processes.
Significance A fundamental dilemma in ecology is to reconcile the degree to which ecological processes are generalizable among taxa and ecosystems or determined primarily by taxonomic identity. We apply a unique dataset of organisms from a diverse marine community to test the applicability of two theories, metabolic theory of ecology (MTE) and ecological stoichiometry (EST), and the role of taxonomic identity for predicting nutrient excretion rates by fishes and macroinvertebrates. Excretion rates were principally explained by body mass and taxonomic identity, providing strong support for MTE, but also highlighting the intrinsic importance of taxonomic identity. Little support for basic predictions of EST was found. This research reveals animal-mediated nutrient cycling is largely generalizable by metabolic processes, but refined predictions require taxa-specific understanding.
Path analyses of historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the ...air temperature‐affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and temperature changes have important implications for adaptation planning because global circulation models produce relatively robust estimates of air temperature changes but have large uncertainties in projected precipitation amounts in the Pacific Northwest U.S. Quantile regression analyses indicate that low streamflow extremes from the majority of catchments in this study have declined from 1948 to 2013, which may significantly affect terrestrial and aquatic ecosystems, and water resource management. Trends in the 25th percentile of mean annual streamflow have declined and the center of timing has occurred earlier. We quantify the relative influences of total precipitation and air temperature on the annual low streamflow extremes from 42 stream gauges using mean annual streamflow as a proxy for precipitation amount effects and streamflow center of timing as a proxy for temperature effects on low flow metrics, including 7q10 summer (the minimum 7 day flow during summer with a 10 year return period), mean August, mean September, mean summer, 7q10 winter, and mean winter flow metrics. These methods have the benefit of using only readily available streamflow data, which makes our results robust against systematic errors in high elevation distributed precipitation data. Winter low flow metrics are weakly tied to both mean annual streamflow and center of timing.
Key Points
Hydrologic drought is more sensitive to precipitation amount than air temperature in the Pacific Northwest
Hydrologic drought has generally intensified from 1948 to 2013 in the Pacific Northwest
Mean annual streamflow has declined and the streamflow center of timing has occurred earlier
PDF
