Geology topics

Jonathon Joseph Valente

Publications and source records attributed to Jonathon Joseph Valente.

8 recordsLinked to original sources

USGS2026

Survey protocols drive heterogeneity in occupancy estimates that cannot be standardized using post hoc analyses

Site occupancy models are widely used to estimate species distributions from presence–nondetection data, yet for mobile animals, the true proportion of sites occupied varies in time. Thus, true occupancy and estimates generated from different protocols are affected by temporal characteristics of survey design. Here we tested whether we could standardize occupancy estimates across different sampling protocols with a post hoc statistical test. Using an individual-based movement model of Wood Thrush ( Hylocichla mustelina ), we simulated point count surveys across 3000 populations under 90 spatially and temporally variable sampling protocols. For each simulation, we fit a standard occupancy model, then used minute-level detections to truncate surveys and generate occupancy estimates across increasing survey lengths. We fit asymptotic models to these series to estimate intercepts (instantaneous occupancy) and asymptotes (longer-term occupancy) and evaluated how well they approximated true instantaneous, daily and seasonal occupancy. We were unable to recover instantaneous or seasonal occupancy from any approach. Both standard occupancy models and asymptotic regression (the top-performing asymptotic model) most closely approximated daily occupancy; although asymptotic regression produced slightly less biased estimates, it showed substantially greater variability, resulting in greater overall error. Our results show that post hoc analytical approaches cannot, at present, reliably standardize occupancy estimates across heterogeneous survey designs. Instead, ensuring biologically informative and comparable estimates will depend on standardized survey protocols. Practical implication : Monitoring programs using presence–nondetection data should prioritize consistent survey protocols when estimating occupancy for mobile species, with a focus on daily occupancy as the most attainable and useful metric. Although the highest accuracy and precision were achieved under the most intensive survey protocols, for point counts of Wood Thrush and similar species, four consecutive 15–20 min surveys provide near-optimal precision and can be completed in a single visit, making them well suited for estimating relative occupancy under logistical constraints. Three 20-min surveys spaced ~24 h apart closely approximate daily occupancy while maintaining reasonable precision. Developing similar protocols for other species and survey methods will be critical to ensuring comparable occupancy estimates across space and time.

Ecological Solutions and Evidence↗

USGS2026

Spatial behavior of socially isolated wild pigs (Sus scrofa) following sounder removal via trapping

BACKGROUND The rapid expansion of wild pig ( Sus scrofa ) populations across North America, coupled with increased concern over disease transmission, has intensified the need for effective management strategies. Trapping is widely regarded as the most effective control method; however, trapping events often fail to capture entire sounders. The behavioral responses of untrapped individuals following partial sounder removal remain poorly understood, potentially undermining management efficiency. We evaluated the spatiotemporal movement responses of wild pigs that became socially isolated following trapping events. RESULTS We deployed GPS collars on 18 female wild pigs from multiple sounders and quantified post-trapping movement patterns using distance from trap site, step length, persistence velocity, space covered and overlap area over a 30-day period. Movement responses were highly variable among individuals, but wild pigs travelled an average of 1.2 km from the trap, with a maximum observed distance of 6.37 km. Space-use overlap was limited, and range sizes remained relatively stable. Individuals originating from sounders with a greater proportion of females moved farther from the trap, whereas wild pigs in better body condition exhibited lower movement velocities. CONCLUSION Socially isolated wild pigs generally remained close to trap sites following partial sounder removal and rarely dispersed from the area. This behavioral pattern suggests a predictable post-trapping window during which untrapped individuals remain spatially accessible. These findings provide critical empirical support for adaptive trapping strategies, indicating that follow-up removal efforts can be effectively concentrated near original trap locations to improve management efficiency and reduce the risk of population persistence or disease spread. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Alabama↗

USGS2026

Spatially concentrating logging could mitigate climate-magnified fragmentation risks to a globally endangered bird

1. Rising timber demand is transforming forest structure globally, profoundly affecting biodiversity and climate resilience. Logging-driven fragmentation is potentially a major driver of biodiversity loss in production landscapes, yet its interactions with escalating climate stressors remain poorly understood. 2. We combine two decades of Landsat-derived habitat metrics with 29,000 surveys of the marbled murrelet ( Brachyramphus marmoratus )—an iconic Pacific Northwest old-forest specialist seabird affecting management of >10 million hectares. Controlling for habitat amount and detection probability, increasing landscape-scale forest edge amount sharply reduces murrelet occupancy, with impacts worsening under unfavourable climate-driven ocean conditions. 3. Comparing alternative landscape-scale timber harvest strategies, spatially concentrated logging consistently supports higher murrelet populations than fragmented approaches producing equivalent wood volumes, with benefits amplified under adverse ocean conditions. However, historical harvesting policies in the Pacific Northwest have instead driven severe habitat fragmentation, which we show is eroding the value of core set-aside forests on federal and conservation lands and ultimately rendering murrelets more vulnerable to climate change. 4. Synthesis and applications : We map key opportunities to boost populations by reducing edginess around remaining nesting habitat and investigate these opportunities' spatial distribution across land ownership and timber productivity gradients. Concentrating logging could be critical for mitigating fragmentation and climate threats for murrelets and potentially other forest-dependent species amid rising timber demand.

California, Oregon, Washington↗

USGS2024

Thinking beyond the closure assumption: Designing surveys for estimating biological truth with occupancy models

Occupancy models estimate distributions of imperfectly detected species, but violations of the closure assumption can bias results. However, researchers working with mobile animals may find it impossible to eliminate such violations. Here, we tested the hypothesis that occupancy models fit to realistic sampling data can generate unbiased occupancy estimates for an itinerant Wood Thrush ( Hylocichla mustelina ) population. In 2013 and 2014, we tracked movements of 41 breeding Wood Thrush males. We modelled territory shift probabilities using logistic exposure models and within-territory movements using continuous-time stochastic process models. We then constructed an individual-based model, simulated (1000 iterations) spatiotemporal locations for individuals and simulated sampling these populations using 162 different point count protocols with variable spatial (sampling radius and point placement method), and temporal (survey length, between-survey intervals and number of surveys) characteristics. We compared occupancy estimates with true values of instantaneous, daily and seasonal occupancy from the simulations. We parameterized continuous time stochastic process models based on movements within 34 unique territories and estimated a daily territory shift probability of 0.0099 (95% CI: 0.0060, 0.0152). Simulated data indicated that estimates of occupancy ranged from 0.18 (0.06, 1.00) to 0.80 (0.71, 0.89) depending on protocol characteristics. Occupancy estimates increased with increasing survey radius, survey length and between-survey interval. Protocols using shorter surveys and between-survey intervals were good estimators for instantaneous occupancy (low bias and mean-squared error) but poor estimators for daily and seasonal occupancy; longer surveys and intervals generated unbiased estimators of daily occupancy but underestimated seasonal occupancy. Logistic regression models that ignored imperfect detection outperformed occupancy models for estimating instantaneous occupancy but not daily or seasonal occupancy. For mobile animals, occupancy of sampling sites changes in space and time. Consequently, the spatial and temporal aspects of a sampling protocol have strong, but predictable, effects on occupancy model parameter estimates. Our results demonstrate that how these factors interact is critical for designing surveys that produce occupancy estimates representative of the biological process of interest to a researcher.

Methods in Ecology and Evolution↗

USGS2024

Designing count-based studies in a world of hierarchical models

Advances in hierarchical modeling have improved estimation of ecological parameters from count data, especially those quantifying population abundance, distribution, and dynamics by explicitly accounting for observation processes, particularly incomplete detection. Even hierarchical models that account for incomplete detection, however, cannot compensate for data limitations stemming from poorly planned sampling. Ecologists therefore need guidance for planning count-based studies that follow established sampling theory, collect appropriate data, and apply current modeling approaches to answer their research questions. We synthesize available literature relevant to guiding count-based studies. Considering the central historical and ongoing contributions of avian studies to ecological knowledge, we focus on birds as a case study for this review, but the basic principles apply to all populations whose members are sufficiently observable to be counted. The sequence of our review represents the thought process in which we encourage ecologists to engage 1) the research question(s) and population parameters to measure, 2) sampling design, 3) analytical framework, 4) temporal design, and 5) survey protocol. We also provide 2 hypothetical demonstrations of these study plan components representing different research questions and study systems. Mirroring the structure of hierarchical models, we suggest researchers primarily focus on the ecological processes of interest when designing their approach to sampling, and wait to consider logistical constraints of data collection and observation processes when developing the survey protocol. We offer a broad framework for researchers planning count-based studies, while pointing to relevant literature elaborating on particular tools and concepts.

Journal of Wildlife Management↗

USGS2024

Passive acoustic monitoring and convolutional neural networks facilitate high-resolution and broadscale monitoring of a threatened species

Population monitoring is an essential component of biodiversity conservation and management, but low detection probabilities for rare and/or cryptic species makes estimating abundance and occupancy challenging. Passive acoustic monitoring combined with machine learning algorithms represents a potential path forward to effectively and efficiently monitor the occurrence of rare vocalizing species across entire forest landscapes. Our objectives were to develop and implement a convolutional neural network (PNW-Cnet) to identify vocalizations of a rare and threatened forest nesting bird species – the marbled murrelet ( Brachyramphus marmoratus ) – in the Pacific Northwest, U.S.A., 2018–2021. We used PNW-Cnet predictions from broadscale passive acoustic monitoring data to examine spatiotemporal patterns in the distribution of murrelets. PNW-Cnet showed sufficiently high prediction accuracy (overall precision > 0.9) to enable broadscale population monitoring. Spatiotemporal analysis showed that annual peak murrelet call abundance occurs in ordinal weeks 28–32 (late July–Mid August) but this varied by study area. The greatest number of detections typically occurred in the Olympic Peninsula and Oregon Coast Range where late-successional forest dominates and nearer to ocean habitats. We demonstrate that passive acoustic monitoring can be used to understand intensity of use across broad scales for a rare and cryptic species in addition to the typical detection/non-detection data that are often collected. Passive acoustic monitoring combined with PNW-Cnet offers considerable promise for species distribution modeling and long-term population monitoring for rare species.

Oregon, Washington↗

USGS2023

Toward conciliation in the habitat fragmentation and biodiversity debate

Landscape-scale conservation planning is urgent given the extent of anthropogenic land-use change and its pervasive impacts on Earth’s biodiversity. However, such efforts are hindered by disagreements over the effects of habitat fragmentation on biodiversity that have persisted since the mid-1970s. We contend that nearly 50 years later, these disagreements have become a locked-in debate characterized by polarized, unproductive discourse and a lack of consistent guidance for landscape managers and policy makers. Here, we highlight the need for a unified set of principles regarding conservation in fragmented landscapes, identify potential reasons for disparate conclusions in fragmentation research, and suggest ways for the ecological community to advance research that leads to consensus rather than the perpetuation of disagreement. Explicit efforts to develop and test multiple competing hypotheses, inter-laboratory collaborations, and acknowledgement of multiple interacting effects will be vital for moving the fragmentation debate forward. We argue that we in the ecology community should be responsible for helping to reconcile different views across scales, systems, and methodological approaches to advance conservation planning within a landscape ecology framework.

Landscape Ecology↗

USGS2023

Both Landsat- and LiDAR-derived measures predict forest bee response to large-scale wildfire

Large-scale disturbances such as wildfire can have profound impacts on the composition, structure, and functioning of ecosystems. Bees are critical pollinators in natural settings and often respond positively to wildfires, particularly in forests where wildfire leads to more open conditions and increased floral resources. The use of Light Detection and Ranging (LiDAR) provides opportunities for quantifying habitat features across large spatial scales and is increasingly available to scientists and land managers for post-fire habitat assessment. We evaluated the extent to which LiDAR-derived forest structure measurements can predict forest bee communities after a large, mixed-severity fire. We hypothesized that LiDAR measurements linked to post-fire forest structure would improve our ability to predict bee abundance and species richness when compared to satellite-based maps of burn severity. To test this hypothesis, we sampled wild bee communities within the Douglas Fire Complex in southwestern Oregon, USA. We then used LiDAR and Landsat data to quantify forest structure and burn severity, respectively, across bee sampling locations. We found that the LiDAR forest structure model was the best predictor of abundance, whereas the Landsat burn severity model had better predictive ability for species richness. Furthermore, the Landsat burn severity model was better at predicting the presence and species richness of bumble bees (Bombus spp.), an ecologically distinct and economically important group within the Pacific Northwest. We posit that the divergent responses of the two modeling approaches are due to distinct responses by bee taxa to variation in forest structure as mediated by wildfire, with bumble bees in particular depending on closed-canopy forest for some portions of their life cycle. Our study demonstrates that LiDAR data can provide information regarding the drivers of bee abundance in post-wildfire conifer forest, and that both remote sensing approaches are useful for predicting components of wild bee diversity after large-scale wildfire.

Oregon↗