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USGS2012

Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0

In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center (RMGSC), in collaboration with Colorado State University, developed a geographic information system (GIS) application, Social Values for Ecosystem Services (SolVES). With version 2.0 (SolVES 2.0), RMGSC has improved and extended the functionality of SolVES, which was designed to assess, map, and quantify the perceived social values of ecosystem services. Social values such as aesthetics, biodiversity, and recreation can be evaluated for various stakeholder groups as distinguished by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with the previous version, SolVES 2.0 derives a quantitative, 10-point, social-values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys and calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. Additionally, SolVES 2.0 integrates Maxent maximum entropy modeling software to generate more complete social value maps and to produce robust statistical models describing the relationship between the social values maps and explanatory environmental variables. The performance of these models can be evaluated for a primary study area, as well as for similar areas where primary survey data are not available but where social value mapping could potentially be completed using value-transfer methodology. SolVES 2.0 also introduces the flexibility for users to define their own social values and public uses, model any number and type of environmental variable, and modify the spatial resolution of analysis. With these enhancements, SolVES 2.0 provides an improved public domain tool for decisionmakers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among different ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

Open-File Report↗

USGS2025

Status of water-quality conditions in the United States, 2010–20

Degradation of water quality can make water harmful or unusable for humans and ecosystems. Although many studies have assessed the effect of individual constituents or narrow suites of constituents on freshwater systems, no consistent, comprehensive assessment exists over the wide range of water-quality effects on water availability. Using published studies, data, and models completed at regional or national scales in the United States during 2010–20, this chapter moves towards a comprehensive assessment by summarizing how selected anthropogenic and geogenic water-quality constituents affect national-scale water availability for human and ecosystem needs. Several types of human health, agricultural, ecological, and beneficial-use standards or thresholds were used to provide context for categorizing surface-water and groundwater quality. Water availability for human and ecological use is limited by elevated concentrations of geogenic and anthropogenic constituents in surface and groundwater. Elevated concentrations of five geogenic constituents (arsenic, manganese, strontium, radium, and adjusted gross alpha) are common in groundwater and collectively affect the drinking water supply to over 30 million people. Surface water sourced drinking water supplies are impaired in about a third of assessed stream miles, most commonly because of non-mercury metals and salinity. Health-based violations at community water systems may disproportionately affect socially vulnerable communities. Ecological water uses are predominantly limited by nutrients, sediment, temperature, pathogens, salinity, and pesticides. Water availability for human and ecological use is adversely affected by human activities including human contaminant sources (for example, wastewater, agriculture), processes (for example, dredging, groundwater pumping), or permanent landscape modifications (for example, dams, urbanization). Primary contaminant sources vary spatially and include fertilizer and manure, atmospheric deposition, wastewater treatment plants, urban land, and a range of natural sources. Contaminants of emerging concern, contaminants without regulatory thresholds, and mixtures of geogenic and anthropogenic water contaminants also contribute to ecological degradation and human exposure.

conterminous United States↗

USGS2023

Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast

Context Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands. Objectives We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area. Methods We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington. Results We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t. Conclusions All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.

California, Oregon, Washington↗

USGS2010

On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake

Most models of lower crust/mantle viscosity inferred from postearthquake relaxation assume one or two uniform-viscosity layers. A few existing models possess apparently significant radially variable viscosity structure in the shallow mantle (e.g., the upper 200 km), but the resolution of such variations is not clear. We use a geophysical inverse procedure to address the resolving power of inferred shallow mantle viscosity structure using postearthquake relaxation data. We apply this methodology to 9 years of GPS-constrained crustal motions after the 16 October 1999 M = 7.1 Hector Mine earthquake. After application of a differencing method to isolate the postearthquake signal from the “background” crustal velocity field, we find that surface velocities diminish from ∼20 mm/yr in the first few months to ≲2 mm/yr after 2 years. Viscoelastic relaxation of the mantle, with a time-dependent effective viscosity prescribed by a Burgers body, provides a good explanation for the postseismic crustal deformation, capturing both the spatial and temporal pattern. In the context of the Burgers body model (which involves a transient viscosity and steady state viscosity), a resolution analysis based on the singular value decomposition reveals that at most, two constraints on depth-dependent steady state mantle viscosity are provided by the present data set. Uppermost mantle viscosity (depth ≲ 60 km) is moderately resolved, but deeper viscosity structure is poorly resolved. The simplest model that explains the data better than that of uniform steady state mantle viscosity involves a linear gradient in logarithmic viscosity with depth, with a small increase from the Moho to 220 km depth. However, the viscosity increase is not statistically significant. This suggests that the depth-dependent steady state viscosity is not resolvably different from uniformity in the uppermost mantle.

California↗

USGS2018

Best practices for elevation-based assessments of sea-level rise and coastal flooding exposure

Elevation data are critical for assessments of sea-level rise (SLR) and coastal flooding exposure. Previous research has demonstrated that the quality of data used in elevation-based assessments must be well understood and applied to properly model potential impacts. The cumulative vertical uncertainty of the input elevation data substantially controls the minimum increments of SLR and the minimum planning horizons that can be effectively used in assessments. For regional, continental, or global assessments, several digital elevation models (DEMs) are available for the required topographic information to project potential impacts of increased coastal water levels, whether a simple inundation model is used or a more complex process-based or probabilistic model is employed. When properly characterized, the vertical accuracy of the DEM can be used to report assessment results with the uncertainty stated in terms of a specific confidence level or likelihood category. An accuracy evaluation has been conducted of global DEMs to quantify their inherent vertical uncertainty to demonstrate how accuracy information should be considered when planning and implementing a SLR or coastal flooding assessment. The evaluation approach includes comparison of the DEMs with high-accuracy geodetic control points as the independent reference data over a variety of coastal relief settings. The global DEMs evaluated include SRTM, ASTER GDEM, ALOS World 3D, TanDEM-X, NASADEM, and MERIT. High-resolution, high-accuracy DEM sources, such as airborne lidar and stereo imagery, are also included to give context to the results from the global DEMs. The accuracy characterization results show that current global DEMs are not adequate for high confidence mapping of exposure to fine increments (<1 m) of SLR or with shorter planning horizons (<100 years) and thus they should not be used for such mapping, but they are suitable for general delineation of low elevation coastal zones. In addition to the best practice of rigorous accounting for vertical uncertainty, other recommended procedures are presented for delineation of different types of impact areas (marine and groundwater inundation) and use of regional relative SLR scenarios. The requirement remains for a freely available, high-accuracy, high-resolution global elevation model that supports quantitative SLR and coastal inundation assessments at high confidence levels.

Frontiers in Earth Science↗

USGS2022

Resist, accept, and direct responses to biological invasions: A social–ecological perspective

Biological invasions represent an important and unique case of ecological transformation that can strongly influence species and entire ecosystems. Challenges in managing invasions arise on multiple fronts, ranging from diverse and often divergent values associated with native and introduced species, logistical constraints, and transformation via other change agents (e.g., climate and land-use change). We address biological invasions considering the Resist-Accept-Direct (RAD) framework for addressing ecological transformation. Because RAD is focused on decisions, we address both social and ecological factors that influence preferences for decision alternatives. We address social factors first as these can constrain the range of alternatives considered in an ecological context. Next, we address ecological dynamics by modeling trajectories from RAD alternatives in a two-species scenario involving impacts of introduced brook trout ( Salvelinus fontinalis ) on native bull trout ( S. confluentus ). Results reveal that decision alternatives aligned with each of the major components of RAD can produce positive outcomes. In a management context, these findings highlight the value of investing in early engagement to fully identify decision alternatives, formalizing models of system dynamics to understand ecological trajectories, and applying this knowledge to set the stage for longer term efforts to address biological invasions.

Fisheries Management and Ecology↗

USGS2022

Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development

Context Wildlife avoid human disturbances, including roads and development. Avoidance and displacement of wildlife into less suitable habitat due to human development can affect their energy expenditures and fitness. The heart rate and oxygen uptake of large mammals varies with both natural aspects of their habitat (terrain, climate, predators, etc.) and anthropogenic influence (noise, light, fragmentation, etc.). Although incorporating physiological analyses of energetics can inform the impacts of both development and conservation, management decisions rarely incorporate individuals’ energetic requirements when deciding on locations for potential development. Objectives We aimed to estimate the change in expected energy expenditure, numerically and spatially, for mule deer to traverse a landscape with varying levels of oil and gas development through time. Methods Using calculations of energy expenditure of mule deer ( Odocoileus hemionus ) by weight, in relation to physical terrain components, plus avoidance factors for anthropogenic disturbance, we developed a spatiotemporal model of the minimum energy required for mule deer to traverse a landscape. We compared expected energy expenditure across 12 study sites with increasing levels of oil and gas development and over time in our study area, on the northern Colorado Plateau of Utah. Results We found that energy expenditure can be increased by development, regardless of terrain, through increased travel distance associated with avoidance behavior. Maximum median energy expenditure to traverse a 1400 ha sample area rose from 1135 to 1935 kilocalories, a 70% increase in energy required of a mule deer. There was a significant relationship between energy expenditure and the size of oil and gas development (p < 0.001), its compactness (p < 0.05), and its ‘thinness’ (p < 0.001), but not terrain ruggedness (p = 0.25). Conclusion As the energy costs of movement correlate across multiple species of large mammals, our analysis of the energetic cost, for mule deer, associated with development can serve as a quantitative representative of the impacts of oil and gas development for multiple mammals—including threatened or endangered species. Our bioenergetic cost-distance model provides a means of delineating impediments to efficient movement and can be used to quantify the expected energetic costs of proposed future developments. As wildlife are exposed to increasing anthropogenic stressors which reduce fitness, it is important to make strategic siting decisions to reduce energetic costs imposed by human activities.

Utah↗

USGS2017

Integrating geographically isolated wetlands into land management decisions

Wetlands across the globe provide extensive ecosystem services. However, many wetlands – especially those surrounded by uplands, often referred to as geographically isolated wetlands (GIWs) – remain poorly protected. Protection and restoration of wetlands frequently requires information on their hydrologic connectivity to other surface waters, and their cumulative watershed‐scale effects. The integration of measurements and models can supply this information. However, the types of measurements and models that should be integrated are dependent on management questions and information compatibility. We summarize the importance of GIWs in watersheds and discuss what wetland connectivity means in both science and management contexts. We then describe the latest tools available to quantify GIW connectivity and explore crucial next steps to enhancing and integrating such tools. These advancements will ensure that appropriate tools are used in GIW decision making and maintaining the important ecosystem services that these wetlands support.

Frontiers in Ecology and the Environment↗

USGS2018

Current research in land, water, and agroecosystems: ASABE journals 2017 year in review

This article highlights current research into land and water resources, agroecosystems, and agricultural production systems published by the Natural Resources and Environmental Systems (NRES) community of ASABE journals (Transactions of the ASABE and Applied Engineering in Agriculture) in 2017. This article reviews the context, scope, and key results of the published articles and perhaps more importantly recommends areas for increased research attention. Experimental and modeling advances were described in hydrology, agroecosystems, climate-change effects, soil erosion, irrigation, drainage, forest resources, livestock systems, natural treatment systems, international water issues, and water quality topic areas. Three special collections were published (International Watershed Technology, Crop Modeling to Optimize Water Use, and Advances in Drainage). Other focal areas included 14 articles relating to livestock waste management, 13 concerning irrigated agricultural systems, 8 addressing climate change effects on land and water resources, and 16 on various aspects of soil erosion measurement and modeling. Building on the articles reviewed from 2017 and toward a vision of future agroecosystems research, the NRES community of ASABE journals strives to grow its role in making new knowledge accessible to sustain agricultural and natural systems in a changing world. In this vane, recommendations for future research direction are discussed with an emphasis on increased application of remote sensing data to agroecosystems research, improved assessment of agroecosystem resiliency and vulnerability to land and climate change, development of integrated models of agroecosystem services, meeting stubborn water management challenges in agricultural production systems, and focusing on publishing fully reproducible model results.

Transactions of the ASABE↗

USGS2021

Towards building a sustainable future: Positioning ecological modelling for impact in ecosystems management

As many ecosystems worldwide are in peril, efforts to manage them sustainably require scientific advice. While numerous researchers around the world use a great variety of models to understand ecological dynamics and their responses to disturbances, only a small fraction of these models are ever used to inform ecosystem management. There seems to be a perception that ecological models are not useful for management, even though mathematical models are indispensable in many other fields. We were curious about this mismatch, its roots, and potential ways to overcome it. We searched the literature on recommendations and best practices for how to make ecological models useful to the management of ecosystems and we searched for ‘success stories’ from the past. We selected and examined several cases where models were instrumental in ecosystem management. We documented their success and asked whether and to what extent they followed recommended best practices. We found that there is not a unique way to conduct a research project that is useful in management decisions. While research is more likely to have impact when conducted with many stakeholders involved and specific to a situation for which data are available, there are great examples of small groups or individuals conducting highly influential research even in the absence of detailed data. We put the question of modelling for ecosystem management into a socio-economic and national context and give our perspectives on how the discipline could move forward.

Bulletin of Mathematical Biology↗

USGS2020

Observations of an extreme atmospheric river storm with a diverse sensor network

Observational networks enhance real‐time situational awareness for emergency and water resource management during extreme weather events. We present examples of how a diverse, multitiered observational network in California provided insights into hydrometeorological processes and impacts during a 3‐day atmospheric river storm centered on 14 February 2019. This network, which has been developed over the past two decades, aims to improve understanding and mitigation of effects from extreme storms influencing water resources and natural hazards. We combine atmospheric reanalysis output and additional observations to show how the network allows: (1) the validation of record cool season precipitable water observations over southern California; (2) the identification of phenomena that produce natural hazards and present difficulties for short‐term weather forecast models, such as extreme precipitation amounts and snow level variability; (3) the use of soil moisture data to improve hydrologic model forecast skill in northern California's Russian River basin; and (4) the combination of meteorological data with seismic observations to identify when a large avalanche occurred on Mount Shasta. This case study highlights the value of investments in diverse observational assets and the importance of continued support and synthesis of these networks to characterize climatological context and advance understanding of processes modulating extreme weather.

California↗

USGS2025

High resolution mapping of submerged sediment size and suitable salmon spawning habitat using topo-bathymetric Lidar in the Santiam Basin, Oregon

The distribution of river-bed grain sizes plays a foundational role in river morphology and ecology. River-bed grain size is a key driver of channel form and process, and has first order effects on aquatic macroinvertebrate assemblages, fish nesting, and biogeochemical processes. Despite this importance, tools to spatially quantify grain-size distributions, particularly submerged grain-size distributions, are lacking. Efforts to address this knowledge gap include developing optical and sonographic tools, however, these approaches have limitations, especially in shallow rivers and over large spatial extents. This study quantifies submerged grain size at high resolution (1 m 2 ) across 260 km of geomorphically diverse river corridors in the Santiam River Basin, Oregon, by pairing bathymetric Lidar point clouds with georeferenced pebble counts. Results suggest that derivatives of Lidar point clouds are able to accurately estimate measured median grain size across seven of the eight river reaches investigated, including reaches above and below high-head dams. Spatial analysis of predicted grain-sizes in the context of Chinook salmon spawning habitat suggests that suitable size sediment patches in the upper, unregulated reaches the study basin is typically small and unorganized. In contrast, the larger rivers downstream of high-head dams typically have larger areas of suitable spawning gravels. This method may be useful for quantification of fish and macroinvertebrates habitats, surface grain-size metrics for sediment transport models, and monitoring of natural and anthropogenic changes in river systems.

Oregon↗

USGS2021

Major reorganization of the Snake River modulated by passage of the Yellowstone Hotspot

The details and mechanisms for Neogene river reorganization in the U.S. Pacific Northwest and northern Rocky Mountains have been debated for over a century with key implications for how tectonic and volcanic systems modulate topographic development. To evaluate paleo-drainage networks, we produced an expansive data set and provenance analysis of detrital zircon U-Pb ages from Miocene to Pleistocene fluvial strata along proposed proto-Snake and Columbia River pathways. Statistical comparisons of Miocene-Pliocene detrital zircon spectra do not support previously hypothesized drainage routes of the Snake River. We use detrital zircon unmixing models to test prior Snake River routes against a newly hypothesized route, in which the Snake River circumnavigated the northern Rocky Mountains and entered the Columbia Basin from the northeast prior to incision of Hells Canyon. Our proposed ancestral Snake River route best matches detrital zircon age spectra throughout the region. Furthermore, this northerly Snake River route satisfies and provides context for shifts in the sedimentology and fish faunal assemblages of the western Snake River Plain and Columbia Basin through Miocene−Pliocene time. We posit that eastward migration of the Yellowstone Hotspot and its effect on thermally induced buoyancy and topographic uplift, coupled with volcanic densification of the eastern Snake River Plain lithosphere, are the primary mechanisms for drainage reorganization and that the eastern and western Snake River Plain were isolated from one another until the early Pliocene. Following this basin integration, the substantial increase in drainage area to the western Snake River Plain likely overtopped a bedrock threshold that previously contained Lake Idaho, which led to incision of Hells Canyon and establishment of the modern Snake and Columbia River drainage network.

Alberta, British Columbia, Idaho, Montana, Oregon,↗

USGS2012

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Natural Hazards↗

USGS2019

Effects of landscape characteristics on annual survival of Lesser Prairie-Chickens

Agriculture and development have caused landscape change throughout the southwestern Great Plains in the range of the lesser prairie-chicken ( Tympanuchus pallidicinctus ). Landscape alteration within the lesser prairie-chicken range may contribute to range contraction and population losses through decreases in survival rates. Our objectives were to determine if: (1) landscape configuration ( i.e ., the spatial arrangement of habitat) or composition ( i.e ., the amount of habitat), at the study-site scale, affected annual survival of females, (2) relationships exist between landscape context ( i.e ., landscape configuration and composition) and weekly survival to assess effects of landscape composition and configuration on lesser prairie-chicken populations, and (3) anthropogenic features influenced daily mortality risk. We captured 170 female lesser prairie-chickens and used very-high-frequency and GPS (Global Positioning System) transmitters to track their movement and survival for 2 y. We used known-fate survival models to test if landscape configuration or composition within three sites in Kansas were related to differences in female survival among sites. In addition we tested for relationships between weekly survival and landscape configuration or composition within home ranges. Finally, we used Andersen-Gill models to test the influence of distance to anthropogenic features on daily mortality risk. Differences in survival were evident between sites with differing landscape compositions as annual survival in Northwestern Kansas (Ŝ = 0.27) was half that of Clark County, Kansas (Ŝ = 0.56), which corresponded with 41.9% more grassland on the landscape in Clark County; landscape configuration did not measurably differ among sites. Survival was greater for prairie-chickens with home-ranges that had greater patch richness and in areas with 30% crop and 57% grassland. Female lesser prairie-chickens also experienced greater mortality risk closer to fences at patch edges. Further conversion of grassland landscapes occupied by lesser prairie-chickens should be avoided to reduce habitat loss and fragmentation thresholds that could affect survival. We suggest continued encouragement of Conservation Reserve Program enrollment in western areas of the lesser prairie-chicken range to maintain or increase the amount of grassland to increase annual survival.

Kansas↗

USGS2020

Mapping climate change resistant vernal pools in the northeastern U.S.

Vernal pools are seasonal wetlands that provide important breeding habitat for a variety of amphibian species. As future climate projections indicate warmer growing seasons and earlier seasonal increases in evapotranspiration, some managers of vernal pools have expressed concern that pools may dry earlier in the season, potentially interfering with completion of amphibian life cycles. In this context, a subset of pools might function as hydrologic refugia by providing wetland habitat later into the year under relatively dry conditions, thus supporting species persistence even as summer conditions become warmer and droughts more frequent. This study used approximately 3,000 field observations of inundation from 450 pools in the northeastern United States—located from West Virginia to Maine—to train machine-learning models for predicting the likelihood of pool inundation. Inputs to these models included pool size, day of the year, climate conditions, short-term weather patterns, and attributes of the landscapes in which pools were embedded. Predictions of pool wetness were generated on a daily time step from late April through late July using three short-term weather scenarios (dry, wet, and average) under historical climate conditions and four sets of downscaled climate projections (2050s and 2080s under Representative Concentration Pathways 4.5 and 8.5). The modeling and inundation prediction process was replicated using four inundation thresholds on wetted area and depth. Model outputs can enable users to examine the inundation thresholds, time points, weather scenarios, and future climate projections most relevant to their management needs. Together with long-term monitoring of individual pools at the site scale, this regional-scale study can support amphibian conservation by helping to identify subsets of pools that may be most likely to function as hydrologic refugia from changing climate conditions.

Connecticut, Delaware, Maine, Maryland, Massachuse↗

USGS2017

Geomagnetically induced currents: Science, engineering, and applications readiness

This paper is the primary deliverable of the very first NASA Living With a Star Institute Working Group, Geomagnetically Induced Currents (GIC) Working Group. The paper provides a broad overview of the current status and future challenges pertaining to the science, engineering, and applications of the GIC problem. Science is understood here as the basic space and Earth sciences research that allows improved understanding and physics-based modeling of the physical processes behind GIC. Engineering, in turn, is understood here as the “impact” aspect of GIC. Applications are understood as the models, tools, and activities that can provide actionable information to entities such as power systems operators for mitigating the effects of GIC and government agencies for managing any potential consequences from GIC impact to critical infrastructure. Applications can be considered the ultimate goal of our GIC work. In assessing the status of the field, we quantify the readiness of various applications in the mitigation context. We use the Applications Readiness Level (ARL) concept to carry out the quantification.

Space Weather↗

USGS2022

Models combining multiple scales of inference capture hydrologic and climatic drivers of riparian tree distributions

Predicting species geographic distributions is key to managing invasive species, conserving biodiversity, and understanding species' environmental requirements. Species distribution models (SDMs) commonly focus on climatic predictors, but other environmental factors can also be essential, particularly for species with specialized habitats defined by hydrologic, topographic, or edaphic conditions (e.g., riparian, wetland, alpine, coastal, serpentine). Here, we demonstrate a novel approach for capturing strong effects of both hydrologic and climatic predictors in SDMs for riparian plants, by merging analyses targeted at environmental drivers within riparian ecosystems and across the western USA (3.8 × 10 6 km 2 ). We developed presence-background SDMs from five algorithms for three invasive riparian trees ( Tamarix ramossisima / chinensis [saltcedar], Elaeagnus angustifolia [Russian olive], and Ulmus pumila [Siberian elm]) and three native Populus spp. (cottonwoods). We used separate background datasets to develop models with different spatial scales of inference: (1) spatially filtered random points to represent available habitat across the study area and (2) target-group points from Salix (willow) occurrences to represent available riparian habitat. Random-background models captured hydrologic drivers of riparian tree distributions relative to the largely upland western USA, whereas Salix -background models captured climatic drivers within the context of riparian ecosystems. Combining predictions from the two backgrounds identified hydrologically suitable habitats within climatically suitable regions, resulting in fewer false “absences” than either background alone, improving predictions over previous SDMs, and providing more complete information to guide management decisions. Surprisingly, the predicted habitat for U. pumila , a newly recognized riparian invader, was as or more extensive than Populus deltoides / fremontii , T. ramossisima / chinensis , and E. angustifolia , the most common riparian tree complexes in the western USA. Watersheds constituting 20% of U. pumila predicted habitat contained no occurrence records, indicating high risk of future and unrecognized invasions. Combining models from random and ecosystem-specific target-group backgrounds may improve SDMs for species from many specialized habitats, providing a method to link predicted distributions to localized geographic features while capturing broad-scale climatic requirements.

western United States↗