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Abundance estimates inform ungulate management and recovery efforts. Yet effective and affordable estimation techniques remain absent for most ungulates lacking identifiable marks and inhabiting rugged or highly vegetated terrain. Methods using N-mixture models with camera trap imagery form an appealing solution but remain unvalidated. We assess this method using populations of desert bighorn sheep (DBS; Ovis canadensis) in New Mexico, USA, plus bison (Bison bison bison) and Texas longhorn cattle (Bos taurus taurus) in Oklahoma, USA, by calculating and comparing abundance estimates to censused values. We parsed data by 3 and 7-day intervals, using images filtered or unfiltered, and collected with motion detection or timed camera settings. We employed priors informed by subject matter experts (SME) and calculated using detection-nondetection methods. Abundance estimates from filtered images captured by motion detection in 3-day intervals included the censused value across all seasons for adult DBS, rams and ewes, indicating "best practices". This "best practices" method also captured censused values for population estimates of bison (detection-nondetection) and cattle with both priors. Our assessment validates the use of N-mixture with camera trap imagery, while presenting sampling approaches, data handling procedures and model calibration to estimate wildlife population sizes more appropriately and accurately. [ABSTRACT FROM AUTHOR]

Climate change shifts ecosystems, altering their compositions and instigating transitions, making climate change the predominant driver of ecosystem instability. Land management agencies experience these climatic effects on ecosystems they administer yet lack applied information to inform mitigation. We address this gap, explaining ecosystem shifts by building relationships between the historical locations of 22 ecosystems (c. 2000) and abiotic data (1970–2000; bioclimate, terrain) within the southwestern United States using 'ensemble' machine learning models. These relationships identify the conditions required for establishing and maintaining southwestern ecosystems (i.e., ecosystem suitability). We projected these historical relationships to mid (2041–2060) and end-of-century (2081–2100) periods using CMIP6 generation BCC-CSM2-MR and GFDL-ESM4 climate models with SSP3-7.0 and SSP5-8.5 emission scenarios. This procedure reveals how ecosystems shift, as suitability typically increases in area (~ 50% (~ 40% SD)), elevation (12–15%) and northing (4–6%) by mid-century. We illustrate where and when ecosystems shift, by mapping suitability predictions temporally and within 52,565 properties (e.g., Federal, State, Tribal). All properties had ≥ 50% changes in suitability for ≥ 1 ecosystem within them, irrespective of size (≥ 16.7 km2). We integrated 9 climate models to quantify predictive uncertainty and exemplify its relevance. Agencies must manage ecosystem shifts transcending jurisdictions. Effective mitigation requires collective action heretofore rarely instituted. Our procedure supplies the climatic context to inform their decisions. [ABSTRACT FROM AUTHOR]

Stable or growing populations may go extinct when their sizes cannot withstand large swings in temporal variation and stochastic forces. Hence, the minimum abundance threshold defining when populations can persist without human intervention forms a key conservation parameter. We identify this threshold for many populations of Caprinae, typically threatened species lacking demographic data. Doing so helps triage conservation and management actions for threatened or harvested populations. Methodologically, we used population projection matrices and simulations, with starting abundance, recruitment, and adult female survival predicting future abundance, growth rate (λ), and population trend. We incorporated mean demographic rates representative of Caprinae populations and corresponding variances from desert bighorn sheep (Ovis canadensis nelsoni), as a proxy for Caprinae sharing similar life histories. We found a population's minimum abundance resulting in ≤ 0.01 chance of quasi-extinction (QE; population ≤ 5 adult females) in 10 years and ≤ 0.10 QE in 30 years as 50 adult females, or 70 were translocation (removals) pursued. Discovering the threshold required 3 demographic parameters. We show, however, that monitoring populations' relationships to this threshold requires only abundance and recruitment data. This applied approach avoids the logistical and cost hurdles in measuring female survival, making assays of population persistence more practical. [ABSTRACT FROM AUTHOR]

With most of the world's Caprinae taxa threatened with extinction, the IUCN appeals to the development of simple and affordable sampling methods that will produce credible abundance and distribution data for helping conserve these species inhabiting remote areas. Traditional sampling approaches, like aerial sampling or mark-capture-recapture, can generate bias by failing to meet sampling assumptions, or by incurring too much cost and logistical burden for most projects to address them. Therefore, we met the IUCN's challenge by testing a sampling technique that leverages imagery from camera traps with conventional distance sampling, validating its operability in mountainous topography by comparing results to known abundances. Our project occurred within a captive facility housing a wild population of desert bighorn sheep (Ovis canadensis) in the Chihuahuan desert of New Mexico, which is censused yearly. True abundance was always within our 90% confidence bounds, and the mean abundance estimates were within 4.9 individuals (average) of the census values. By demonstrating the veracity of this straightforward and inexpensive sampling method, we provide confidence in its operability, urging its use to fill conservation voids for Caprinae and other data-deficient species inhabiting rugged or heavily vegetated terrain. [ABSTRACT FROM AUTHOR]

In the original publication, the Electronic Supplementary Material (ESM) was published incorrectly. The correct version of ESM is given in the link below. [ABSTRACT FROM AUTHOR]