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USGS2011

Biogeochemistry of a temperate forest nitrogen gradient

Wide natural gradients of soil nitrogen (N) can be used to examine fundamental relationships between plant–soil–microbial N cycling and hydrologic N loss, and to test N-saturation theory as a general framework for understanding ecosystem N dynamics. We characterized plant production, N uptake and return in litterfall, soil gross and net N mineralization rates, and hydrologic N losses of nine Douglas-fir ( Pseudotsuga menziesii ) forests across a wide soil N gradient in the Oregon Coast Range (USA). Surface mineral soil N (0–10 cm) ranged nearly three-fold from 0.29% to 0.78% N, and in contrast to predictions of N-saturation theory, was linearly related to 10-fold variation in net N mineralization, from 8 to 82 kg N·ha −1 ·yr −1 . Net N mineralization was unrelated to soil C:N, soil texture, precipitation, and temperature differences among sites. Net nitrification was negatively related to soil pH, and accounted for <20% of net N mineralization at low-N sites, increasing to 85–100% of net N mineralization at intermediate- and high-N sites. The ratio of net : gross N mineralization and nitrification increased along the gradient, indicating progressive saturation of microbial N demands at high soil N. Aboveground N uptake by plants increased asymptotically with net N mineralization to a peak of 35 kg N·ha −1 ·yr −1 . Aboveground net primary production per unit net N mineralization varied inversely with soil N, suggesting progressive saturation of plant N demands at high soil N. Hydrologic N losses were dominated by dissolved organic N at low-N sites, with increased nitrate loss causing a shift to dominance by nitrate at high-N sites, particularly where net nitrification exceeded plant N demands. With the exception of N mineralization patterns, our results broadly support the application of the N-saturation model developed from studies of anthropogenic N deposition to understand N cycling and saturation of plant and microbial sinks along natural soil N gradients. This convergence of behavior in unpolluted and polluted forest N cycles suggests that where future reductions in deposition to polluted sites do occur, symptoms of N saturation are most likely to persist where soil N content remains elevated.

Oregon↗

USGS2007

Preliminary Surficial Geology of the Dove Spring Off-Highway Vehicle Open Area, Mojave Desert, California

Introduction As part of a U.S. Geological Survey (USGS) monitoring plan to evaluate the environmental impact of off-highway vehicle (OHV) use on Bureau of Land Management (BLM) land in California, this report presents results of geologic studies in the Dove Spring OHV Open Area. This study produced baseline data, which when combined with historic and current patterns of land use, forms the basis for vegetation and wildlife monitoring designed to address the following questions: 1. Is the density and length of OHV routes increasing? 2. Are there cumulative effects of past and current OHV use associated with changes in the environmental integrity of soils, plants, and wildlife? 3. Is the spread of invasive species associated with levels of OHV use? 4. Is there a threshold of OHV impact that might be translated to management action by the BLM? The monitoring studies will be used to collect baseline environmental information to determine levels of environmental impact of OHV use. This approach will use a low-impact area as a proxy for pre-impact conditions (substituting space for time) to determine thresholds of OHV impacts beyond which environmental integrity is affected. Indicators of environmental integrity will emphasize factors that are fundamental to ecosystem structure and function and likely to be sensitive to OHV impacts. Surficial geology is studied because material properties such as texture and chemistry strongly control soil moisture and nutrient availability and therefore affect plant growth and distribution. An understanding of surficial geology can be used to predict and extrapolate soil properties and improve understanding of vegetation assemblages and their distribution. In the present study, vegetation associations may be examined as a function of surficial geology as well as other environmental variables such as slope, aspect, NRCS (National Resources Conservation Service) soil classification, elevation, and land-use history. Ground measurements of vegetation, biological soil crusts, compaction, and other information may be correlated with land use to identify possible ecological thresholds in OHV use that require monitoring. Surficial geology is relevant for several other studies of OHV impact, such as soil compaction, dust emissions, and acceleration of erosion. Compaction, reduced infiltration, and accelerated erosion have been documented in Dove Spring Canyon because of OHV use (Snyder and others, 1976) and elsewhere in the Mojave Desert (e.g., Webb, 1983; Langdon, 2000). A surficial geologic map enables the use of geomorphic process models, which when combined with measured soil properties, such as texture, nutrient chemistry, and bulk density, allows spatial extrapolation of the properties. Maps can be produced that predict compaction susceptibility, moisture conditions, dust emissions, flood hazards, and erodibility, among other applications.

Open-File Report↗

USGS2012

Linking river management to species conservation using dynamic landscape scale models

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km 2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.

Georgia↗

USGS2002

The Protected Areas Visitor Impact Management (PAVIM) framework: A simplified process for making management decisions

Ecotourism and protected area visitation in Central and South America have resulted in ecological impacts, which some protected areas managers have addressed by employing visitor impact management frameworks. In this paper, we propose the Protected Area Visitor Impact Management (PAVIM) framework as an alternative to carrying capacity and other frameworks such as Limits of Acceptable Change. We use a set of evaluation criteria to compare the relative positive and negative attributes of carrying capacity, other decision-making frameworks and the new framework, within the context of their actual and potential use in Central and South America. Positive attributes of PAVIM include simplicity, flexibility, cost effectiveness, timeliness and incorporating input from stakeholders and local residents. Negative attributes include diminished objectivity and cultural sensitivity issues. Further research and application of PAVIM are recommended.

Journal of Sustainable Tourism↗

USGS2001

Methods for Evaluating Wetland Condition #12: Using Amphibians in Bioassessments of Wetlands

Because amphibians have both aquatic and terrestrial life stages they can serve in a unique way among vertebrates as sources of information for bioassessments of both wetlands and surrounding habitats. Although there are many data gaps in our knowledge about the habitat requirements and ecology of many amphibian species, it is apparent that community composition, presence and frequency of abnormalities, various mensural characteristics (e.g. snout vent length divided by body weight) and laboratory diagnostics (e.g. cholinesterase activity, blood chemistry) can be used in developing metrics for an index of biotic integrity. In addition, potential metrics can be derived from the various life stages that most amphibians experience such as egg clusters; embryonic development and hatching rates; tadpole growth, development, and survival; progress and success of metamorphosis; and breeding behavior and presence of adults. It is important, however, to focus on regional biodiversity and species assemblages of amphibians in the development of metrics rather than to strive for broadscale application of common metrics. This report discusses the procedures of developing an index of biotic integrity based on amphibians, explains potential pitfalls in using amphibians in bioassessments, and demonstrates where more research is needed to enhance the use of amphibians in evaluating wetland conditions.

Report↗

USGS2026

The application of state-and-transition models to remotely sensed fractional cover datasets

Assessing vegetation conditions in expansive rangeland ecosystems has long posed a persistent challenge. Recent advancements in remote sensing technologies have provided new avenues for improving this assessment process. In this study, conducted at two ranch sites in Nevada, we integrated existing line-point-intercept monitoring data with additional field observations to evaluate the vegetation condition or “State” at various monitoring points. We then employed machine learning techniques to classify gridded raster datasets, aligning them with existing state-and-transition models (STMs) specific to each study area. Leveraging Landsat-derived fractional cover datasets, along with climate and soil predictors, we aimed to predict vegetation State within specific Vegetation Great Groups (VGGs). The resulting vegetation State maps were then combined to generate a cohesive representation of vegetation conditions across the study sites. Our analysis revealed that relative functional group cover emerged as a superior predictor of vegetation state and ecological processes at the site level. However, we encountered variations in state mapping accuracy ranging from approximately 14% to 44% error. These discrepancies were influenced by factors such as study location, landscape heterogeneity, availability of training data, and species-specific challenges, all of which complicate the accurate classification of remote sensing datasets.

Nevada↗

USGS2023

A targeted annual warning system developed for the conservation of a sagebrush indicator species

A fundamental goal of population ecologists is to identify drivers responsible for temporal variation in abundance. Understanding whether variation is associated with environmental stochasticity or anthropogenic disturbances, which are more amenable to management action, is crucial yet difficult to achieve. Here, we present a hierarchical monitoring framework that models rates of change in abundance from spatially structured populations and identifies when local declines fall out of synchrony with trends at larger spatial scales. Importantly, the framework provides signals that alert managers to the categorical significance of observed declines while avoiding signals where declines result from drivers operating at larger spatial scales (e.g., periodic reductions in primary productivity owing to drought). We demonstrate utility through application to a rapidly declining sagebrush ( Artemisia spp.) indicator species (greater sage-grouse; Centrocercus urophasianus ) using 30 years (1990–2019) of count data collected from greater than 4,400 leks (habitual breeding sites) distributed across the western United States. Results revealed population declines, immediately preceding triggers (2–4-year period), ranging between 58 and 68%. Conversely, population trends unassociated with triggers showed little-to-no sign of decline. Retrospective application of the monitoring framework indicated an average annual rate of 1.7% of leks or 1.3% of neighborhood clusters (lek aggregations) would have required management intervention to reverse range-wide declines and stabilize the U.S. population as a whole.

Ecological Indicators↗

USGS2025

Post-fire recovery of sagebrush-steppe communities is better explained by elevation than climate-derived indicators of resistance and resilience

More landscapes require restoration than can feasibly be treated, and so decision-support tools to prioritize areas for treatment are needed. Moreover, restoration is complicated by the threat of biological invasion in disturbed areas, and so indicators of ecosystem resistance to invasion and resilience to disturbance (hereafter R&R) are important candidate criteria for prioritizing sites for restoration. We asked how climate-based R&R indicators that differed in being either categorical or continuous compared in their ability to explain plant-community recovery after six wildfires that collectively encompassed >750,000 ha and 7803 plot-year observations in sagebrush steppe of the western USA. Unique associations of species that most frequently co-occurred were identified using structural topic modelling. Mixed effect random forests were used to identify the relative importance of various R&R indicators in explaining post-fire plant associations compared with weather, landscape characteristics and treatment history. Simple metrics (elevation, latitude, longitude and year of monitoring) were more informative predictors of post-fire recovery than climate-based R&R indicators. However, small differences in the abundances of perennial grass and especially annual grass associations were predicted by the spring modified Thornthwaite Moisture Index (difference between precipitation and potential evapotranspiration). Synthesis and applications : The convenience of categorical resistance and resilience indicators has led to their widespread adoption for large-scale planning of restoration. Our results reveal that none of the resistance and resilience indicators assessed effectively explained post-fire restoration better than elevation, although a simple continuous resistance and resilience indicator describing water balance performed better than categorical indicators for explaining small but critical differences in cheatgrass association abundances.

California, Idaho, Nevada, Oregon↗

USGS2016

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Nature Climate Change↗

USGS2025

Blueprints for riverine cod nest boxes draw from multiple design considerations

Designing aquatic nest boxes is rarely afforded detailed scientific account. Here we provide some historical context for nest boxes used in production of large-bodied fishes of the Australian freshwater cod genus Maccullochella . Our experience with eastern freshwater cod is used as a case study to: (a) convey aspects of the complexity of the nest box design process and to (b) demonstrate the importance of visual literacy in project communication across the variety of contributors to the eco-design process. Specifically, we describe a new, two-variant, triangular nest box design for application in rivers and modifications to a standard stainless steel nest box for hatchery-pond-based spawning of eastern freshwater cod M. ikei . We designed the boxes to test adult preference for single versus double entrance/exits to cavities in hatchery and field environments. An important consideration specific to hatchery production is harvesting demersal, adhesive eggs prior to hatching to minimise fungal infection of eggs and physical loss of larvae, in addition to providing critical first feeding of larvae. In contrast, field nest box design incorporated multiple factors and associated trade-offs related to both internal and external design, ranging from manufacturer capability, material types, cost, transportability, hydrological performance, biodegradability, retrievability, as well as biological and ecological function. Only preliminary findings from field nest box deployments are provided here, and we focus primarily on elements of visual language in the form of conceptual drawings, sketches and final schematics which have been central to our process. We emphasise the benefit of harnessing input from multiple fields of expertise and documenting and testing designs of nest boxes for cavity nesting fishes, under both controlled hatchery and more complex field conditions.

Aquaculture, Fish and Fisheries↗

USGS2019

Fluorescent biomarkers demonstrate prospects for spreadable vaccines to control disease transmission in wild bats

Vaccines that autonomously transfer among individuals have been proposed as a strategy to control infectious diseases within inaccessible wildlife populations. However, rates of vaccine spread and epidemiological efficacy in real-world systems remain elusive. Here, we investigate whether topical vaccines that transfer among individuals through social contacts can control vampire bat rabies—a medically and economically important zoonosis in Latin America. Field experiments in three Peruvian bat colonies, which used fluorescent biomarkers as a proxy for the bat-to-bat transfer and ingestion of an oral vaccine, revealed that vaccine transfer would increase population-level immunity up to 2.6 times beyond the same effort using conventional, non-spreadable vaccines. Mathematical models showed that observed levels of vaccine transfer would reduce the probability, size and duration of rabies outbreaks, even at low but realistically achievable levels of vaccine application. Models further predicted that existing vaccines provide substantial advantages over culling bats—the policy currently implemented in North, Central and South America. Linking field studies with biomarkers to mathematical models can inform how spreadable vaccines may combat pathogens of health and conservation concern before costly investments in vaccine design and testing.

Nature Ecology and Evotution↗

USGS2016

Hydrologic impacts of thawing permafrost—A review

Where present, permafrost exerts a primary control on water fluxes, flowpaths, and distribution. Climate warming and related drivers of soil thermal change are expected to modify the distribution of permafrost, leading to changing hydrologic conditions, including alterations in soil moisture, connectivity of inland waters, streamflow seasonality, and the partitioning of water stored above and below ground. The field of permafrost hydrology is undergoing rapid advancement with respect to multiscale observations, subsurface characterization, modeling, and integration with other disciplines. However, gaining predictive capability of the many interrelated consequences of climate change is a persistent challenge due to several factors. Observations of hydrologic change have been causally linked to permafrost thaw, but applications of process-based models needed to support and enhance the transferability of empirical linkages have often been restricted to generalized representations. Limitations stem from inadequate baseline permafrost and unfrozen hydrogeologic characterization, lack of historical data, and simplifications in structure and process representation needed to counter the high computational demands of cryohydrogeologic simulations. Further, due in part to the large degree of subsurface heterogeneity of permafrost landscapes and the nonuniformity in thaw patterns and rates, associations between various modes of permafrost thaw and hydrologic change are not readily scalable; even trajectories of change can differ. This review highlights promising advances in characterization and modeling of permafrost regions and presents ongoing research challenges toward projecting hydrologic and ecologic consequences of permafrost thaw at time and spatial scales that are useful to managers and researchers.

Vadose Zone Journal↗

USGS2014

Conservation Action Planning: Lessons learned from the St. Marys River watershed biodiversity conservation planning process

Conservation Action Planning (CAP) is an adaptive management planning process refined by The Nature Conservancy (TNC) and embraced worldwide as the Open Standards for the Practice of Conservation. The CAP process facilitates open, multi-institutional collaboration on a common conservation agenda through organized actions and quantified results. While specifically designed for conservation efforts, the framework is adaptable and flexible to multiple scales and can be used for any collaborative planning effort. The CAP framework addresses inception; design and development of goals, measures, and strategies; and plan implementation and evaluation. The specific components of the CAP include defining the project scope and conservation targets; assessing the ecological viability; ascertaining threats and surrounding situation; identifying opportunities and designing strategies for action; and implementing actions and monitoring results. In 2007, TNC and a multidisciplinary graduate student team from the University of Michigan's School of Natural Resources and Environment initiated a CAP for the St. Marys River, the connecting channel between Lake Superior and Lake Huron, and its local watershed. The students not only gained experience in conservation planning, but also learned lessons that notably benefited the CAP process and were valuable for any successful collaborative effort—a dedicated core team improved product quality, accelerated the timeline, and provided necessary support for ongoing efforts; an academic approach in preparation for engagement in the planning process brought applicable scientific research to the forefront, enhanced workshop facilitation, and improved stakeholder participation; and early and continuous interactions with regional stakeholders improved cooperation and built a supportive network for collaboration.

Michigan, Ontario↗

USGS2014

Controls of vegetation structure and net primary production in restored grasslands

1. Vegetation structure and net primary production (NPP) are fundamental properties of ecosystems. Understanding how restoration practices following disturbance interact with environmental factors to control these properties can provide insight on how ecosystems recover and guide management efforts. 2. We assessed the relative contribution of environmental and restoration factors in controlling vegetation structure, above- and below-ground investment in production across a chronosequence of semiarid Conservation Reserve Program (CRP) fields recovering from dryland wheat cropping relative to undisturbed grassland. Importantly, we determined the role of plant diversity and how seeding either native or introduced perennial grasses influenced the recovery of vegetation properties. 3. Plant basal cover increased with field age and was highest in CRP fields seeded with native perennial grasses. In contrast, fields seeded with introduced perennial grasses had tall-growing plants with relatively low basal cover. These vegetation structural characteristics interacted with precipitation, but not soil characteristics, to influence above-ground NPP (ANPP). Fields enrolled in the CRP program for >7 years supported twice as much ANPP as undisturbed shortgrass steppe in the first wet year of the study, but all CRP fields converged on a common low amount of ANPP in the following dry year and invested less than half as much as the shortgrass steppe in below-ground biomass. 4. ANPP in CRP fields seeded with native perennial grasses for more than 7 years was positively related to species richness, whereas ANPP in CRP fields seeded with introduced perennial grasses were controlled more by dominant species. 5. Synthesis and applications. Seeding with introduced, instead of native, perennial grasses had a strong direct influence on vegetation structure, including species richness, which indirectly affected NPP through time. However, the effects of restoring either native or introduced grasses on NPP were secondary to low water availability. Therefore, restoration strategies that maximize basal cover and below-ground biomass, which promote water acquisition, may lead to high resilience in semiarid and arid regions.

Colorado↗

USGS2021

Does restoration of plant diversity trigger concomitant soil microbiome changes in dryland ecosystems?

Drylands are highly vulnerable to land degradation, and despite increasing efforts, restoration success remains low. Although often ignored in the design and deployment of management strategies, soil microbial communities might be critical for dryland restoration due to their central role in promoting soil stability, nutrient cycling and plant establishment. We collected soil samples from eight dryland restoration sites within RestoreNet, a restoration field trial network, and determined their soil microbiome using 16S rRNA (bacteria and archaea) and ITS (fungi) amplicon sequencing. Each previously degraded site was treated with monoculture (single species) and polyculture (multiple species) seedling plantings. Contrary to our initial expectations, we found that these different revegetation interventions did not trigger changes in microbial diversity, composition or relative abundance of functional groups across sites after 1 year of revegetation. Synthesis and applications . Considering the crucial role of soil micro-organisms in dryland ecosystem functions, our results suggest that site-specific targeted microbiome restoration should be considered to accelerate the establishment of desired microbial communities. Plant community-based restoration practices such as revegetation have a limited impact on soil micro-organisms in the short term.

Journal of Applied Ecology↗

USGS2022

The effects of cheatgrass invasion on US Great Basin carbon storage depend on interactions between plant community composition, precipitation seasonality, and soil climate regime

Annual-grass invasions are transforming desert ecosystems in ways that affect ecosystem carbon (C) balance, but previous studies do not agree on the pattern, magnitude and direction of changes. A recent meta-analysis of 41 articles and 386 sites concludes that invasion by annual grasses such as cheatgrass ( Bromus tectorum L) reduces C in biomass across the Great Basin (Nagy et al., 2021). Reanalysis reveals that whether cheatgrass affects biomass C stocks is not generalizable, but rather depends on the considerable variation in climate across the subject sites. Our analysis suggests that accurate Great Basin-scale estimates of cheatgrass effects on C balance are not yet possible. Addition of climate variables to the meta-analysis reveals that cheatgrass invasion (a) reduced C in above-ground biomass in relatively summer-wet sites but not in summer-dry sites, (b) increased surface soil C in sites with intermediate resistance and resilience classifications (R&R) but not in low R&R sites—that is, mesic/aridic soil climates and (c) did not affect deep soil C. Considering that cheatgrass has expanded most in relatively summer-dry sites and mesic/aridic sites, omission of climate factors leads to model overestimates of cheatgrass effects on C when extrapolating to larger areas. Estimates of cheatgrass effects on C would also be improved if the analysis considered that (a) perennial grasslands are a common community state in the Great Basin that have intermediary C relative to annual grasslands and sagebrush stands, that is the omission of perennial grasslands from analysis inflates the baseline C storage of uninvaded Great Basin ecosystems, and( b) cheatgrass does not often exist in stable monocultures and soil carbon can reflect current or recent presence of other species. Synthesis and applications . Invasions often reveal heterogeneity in ecosystem structure and function that is not otherwise evident, and the heterogeneity can influence estimation of the net impacts of the invaders. For cheatgrass and other invaders, we propose that formally accounting for the spatial variability of invasion on ecosystem functions will improve the estimation of their net effect on ecosystem C, and thus improve prospects for adjusting management practices to optimize C sequestration.

western United States↗

USGS2010

Modelling community dynamics based on species-level abundance models from detection/nondetection data

1. In large‐scale field surveys, a binary recording of each species’ detection or nondetection has been increasingly adopted for its simplicity and low cost. Because of the importance of abundance in many studies, it is desirable to obtain inferences about abundance at species‐, functional group‐, and community‐levels from such binary data. 2. We developed a novel hierarchical multi‐species abundance model based on species‐level detection/nondetection data. The model accounts for the existence of undetected species, and variability in abundance and detectability among species. Species‐level detection/nondetection is linked to species‐level abundance via a detection model that accommodates the expectation that probability of detection (at least one individuals is detected) increases with local abundance of the species. We applied this model to a 9‐year dataset composed of the detection/nondetection of forest birds, at a single post‐fire site (from 7 to 15 years after fire) in a montane area of central Japan. The model allocated undetected species into one of the predefined functional groups by assuming a prior distribution on individual group membership. 3. The results suggest that 15–20 species were missed in each year, and that species richness of communities and functional groups did not change with post‐fire forest succession. Overall abundance of birds and abundance of functional groups tended to increase over time, although only in the winter, while decreases in detectabilities were observed in several species. 4. Synthesis and applications . Understanding and prediction of large‐scale biodiversity dynamics partly hinge on how we can use data effectively. Our hierarchical model for detection/nondetection data estimates abundance in space/time at species‐, functional group‐, and community‐levels while accounting for undetected individuals and species. It also permits comparison of multiple communities by many types of abundance‐based diversity and similarity measures under imperfect detection.

Journal of Applied Ecology↗

USGS2019

Spatial capture–recapture for categorically marked populations with an application to genetic capture–recapture

Recently introduced unmarked spatial capture–recapture (SCR), spatial mark–resight (SMR), and 2‐flank spatial partial identity models (SPIMs) extend the domain of SCR to populations or observation systems that do not always allow for individual identity to be determined with certainty. For example, some species do not have natural marks that can reliably produce individual identities from photographs, and some methods of observation produce partial identity samples as is the case with remote cameras that sometimes produce single‐flank photographs. Unmarked SCR, SMR, and SPIM share the feature that they probabilistically resolve the uncertainty in individual identity using the spatial location where samples were collected. Spatial location is informative of individual identity in spatially structured populations because a sample is more likely to have been produced by an individual living near the trap where it was recorded than an individual living further away from the trap. Further, the level of information about individual identity that a spatial location contains is related to two key ecological concepts, population density and home range size, which we quantify using a proposed Identity Diversity Index (IDI). We show that latent and partial identity SCR models produce imprecise and biased density estimates in many high IDI scenarios when data are sparse. We then extend the unmarked SCR model to incorporate categorical, partially identifying covariates, which reduce the level of uncertainty in individual identity, increasing the reliability and precision of density estimates, and allowing reliable density estimation in scenarios with higher IDI values and with more sparse data. We illustrate the performance of this “categorical SPIM” via simulations and by applying it to a black bear data set using microsatellite loci as categorical covariates, where we reproduce the full data set estimates with only slightly less precision using fewer loci than necessary for confident individual identification. We then discuss how the categorical SPIM can be applied to other wildlife sampling scenarios such as remote camera surveys, where natural or researcher‐applied partial marks can be observed in photographs. Finally, we discuss how the categorical SPIM can be added to SMR, 2‐flank SPIM, or other latent identity SCR models.

Ecosphere↗