Eurasian otters (Lutra lutra) occur across Asia, Europe, and northern Africa, yet many populations are declining or endangered. Otter populations in northeast China have decreased substantially over the past 70 years, which is generally attributed to land use change, though this hypothesis remains untested. We examined the relationship between land use and otter occurrence in Jilin Province by characterizing land use in 100-m river buffers extending 7.5 km upstream and downstream from each of the 58 known otter occurrences compared to 100 randomly selected pseudo-absence points across the same landscape. Logistic regression revealed that otters were less likely to occur as agricultural land increased (p = 0.00347). We also observed negative but nonsignificant trends between otter presence and average cropland patch size, percentage of built-up land, and average built-up patch size. A principal component analysis explained 48.7% of total landscape variation and indicated that locations where otters were known to be present were less variable in landscape conditions (i.e. amount and size of agricultural and urbanized patches) compared to random locations. Overall, this ensemble approach suggests that otters are affected by land use at least at a localized scale, complementing other studies within its range. (c) 2025 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA). Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

Aim Phylogenetic niche conservatism, the tendency of closely related species to retain ancestral ecological traits, has gained considerable interest, yet the lack of integration across independent evaluation methods has hindered our understanding of whether niches are conserved or dynamic. Such an understanding is especially relevant for taxa of conservation concern, such as crocodylians (order Crocodylia). This study assessed niche conservatism among New World crocodylians by combining ensemble species distribution models, phylogenetics, and standard metrics of geographic and environmental niche overlap.Location America.Major Taxa Order Crocodylia.Methods We estimated species' climatic niches in geographic and environmental dimensions to assess overlap patterns and quantified associations between niche overlap and phylogenetic patristic distance using the Mantel test and phylogenetic independent contrast (PIC).Results Overlap analyses in geographic and environmental spaces revealed climatic niche differentiation across the clade, suggesting divergent environmental preferences among species. The relationship between phylogenetic patristic distance and climatic niche overlap assessed via Mantel tests revealed a significant negative correlation with geographic niche overlap (rho = -0.361, p = 0.005), but no evidence for associations with environmental niche overlap (Schoener's D: rho = -0.079, p = 0.184; Hellinger's I: rho = -0.063, p = 0.250), suggesting that more distantly related species overlap less geographically. In contrast, the relationship assessed using PIC revealed no evidence for associations between phylogenetic distance and either geographic (rho = -0.200, p = 0.579) or environmental niche overlap (D: rho = -0.294, p = 0.41; I: rho = -0.319, p = 0.369).Conclusions We found no strong or consistent evidence for phylogenetic conservatism in climatic niches across both geographic (inverse relationship) and environmental (no relationship) dimensions in New World crocodylians. This study enhances our understanding of niche dynamics and highlights the value of integrating niche modelling with phylogenetic analyses to detect biogeographic and evolutionary patterns.

The Yazoo–Mississippi Delta is an agricultural production zone and flyway for migratory birds. During winter, agricultural field-flooding practices are routinely used to support bird conservation and local recreational hunting opportunities. In response to the 2010 Deepwater Horizon oil spill, federal agencies incentivized flooding in summer and fall to mitigate the risks to migratory bird populations. This funding ceased in 2017, yet the United States Department of Agriculture Natural Resources Conservation Service Environmental Quality Incentives Program Practice 644 and a local non-profit continue to incentivize flooding during fall. Ensuring that contractual water levels are met is challenging to determine. To that end, we developed the Field Inundation Tool/Survey, an integrated remote sensing approach using PlanetScope imagery (Planet Labs, San Francisco, CA, USA) to quantify associated hydrology patterns. We used the Normalized Difference Water Index and an Iso Cluster Unsupervised Classification to estimate field inundation and associated habitat types over a three-year period. The results indicate dynamic field inundation can be estimated via PlanetScope imagery. Derived inundation metrics were comparable with in situ sensor and digital elevation models among some treatment types. We documented future refinements for image quality and soil patterns. Our work can improve conservation incentivization by tracking spatial and temporal patterns in adoption and has applicability to other agroecosystems.

The house sparrow (Passer domesticus) is one of the most widespread invasive bird species, with numerous and dense populations established across urban-agricultural landscapes of North America. Although this species has been widely studied to identify the traits that explain its global ubiquity, descriptions of house sparrow acoustic features across its native and introduced range are limited in the literature. We recorded male house sparrow vocalizations from 13 cities across Europe and North America to quantify the structural features of its common “chirrup” vocalization. Although the basic structure and duration were consistent across the two geographic regions, the vocalizations differed in their minimum frequencies and bandwidth. In a post hoc analysis of 140 museum specimens, we found that European house sparrows had larger bills and bodies than those in North America. Thus, we propose that these frequency shifts could be a result of synergistic interactions between morphological differences, potential differences in ambient noise, acoustic overlap with other species within the soundscape, or other acoustic features of European and North American cities. House sparrows seem to be a good model for future bioacoustics studies, given their worldwide distribution and acoustic plasticity, to test hypotheses related to urbanization traits and invasion potential.

Curtailing encroachment is dependent on effectively identifying where problematic species occur. However, traditional classification methods struggle to distinguish spectrally similar species. New techniques that incorporate environmental variables (edaphic, climatic, and topographic characteristics) into classification can refine predictions and help identify important factors associated with species occurrence. We developed a workflow to improve classification of honey mesquite (Neltuma [=Prosopis] glandulosa) in the Southern Great Plains (USA), examining 70 environmental variables to determine which were most associated with mesquite presence. We used Google Earth Engine to run X-means clustering on high-resolution aerial imagery from 50 replicate 78-km2 areas in New Mexico and Texas. We then refined our classification using XGBoost to generate accuracy assessment points for each area to confirm locations of mesquite clusters. Our method improved classification accuracy from 36 % to 83 %. We performed an ex-situ ground-truthed validation study and achieved 74 % accuracy. Inclusion of environmental data increased the accuracy of mesquite classification and allowed us to estimate the influence of each variable in determining whether a given point was classified as mesquite. Shallow, alkaline soils with low water-storage capacity, high electrical conductance, and low cation exchange capacity were associated with mesquite presence; these areas tended to be associated with flat, low-elevation drainages in regions that experience wide annual temperature ranges. These methods provide an easily reproducible and scalable way to assist with image classification of rangeland shrubs from remotely sensed imagery, which may prove useful in managing the further encroachment of problematic species like honey mesquite.

The lesser prairie-chicken (Tympanuchus pallidicinctus) lek network represents a prime testing ground for examining how analyses of connectivity may help inform why and where population declines occur. We compared how patterns of decline and inactivity were associated with lek structural connectivity. We used lek locations and years of recorded activity from the southern population of lesser prairie-chickens to construct networks at a range of distances representing biological processes. We calculated Kleinberg’s hub score and betweenness score to quantify each lek’s contribution to facilitating connectivity at each distance. We used these scores to predict lek activity based on centrality at multiple scales. The number of years in which a lek was active was positively associated with betweenness score and, to a lesser extent, hub score. Associations varied across spatial scales, with high-persistence leks being more central in smaller-scale clusters (maximum nesting distance), and leks known to have failed being less central at broader scales (average and maximum dispersal distances). Connectivity scores predicted whether a lek was active or not with 80

Understanding how past and current environmental conditions shape the demographic and genetic distributions of organisms facilitates our predictions of how future environmental patterns may affect populations. The Canyon Rubyspot damselfly (Odonata: Zygoptera: Hetaerina vulnerata) is an insect with a range distribution from Colombia to the arid southwestern United States, where it inhabits shaded mountain streams in the arid southwestern United States. Past spatial fragmentation of habitat and limited dispersal capacity of H. vulnerata may cause population isolation and genetic differentiation, and projected climate change may exacerbate isolation by further restricting the species' distribution. We constructed species distribution models (SDMs) based on occurrences of H. vulnerata and environmental variables characterizing the species' niche. We inferred seven current potential population clusters isolated by unsuitable habitat. Paleoclimate models indicated habitat contiguity in past conditions; projected models indicated some habitat fragmentation in future scenarios. Seventy-eight H. vulnerata individuals from six of the current clusters were sequenced via ddRADseq and processed with Stacks. Principal components and phylogeographic analyses resolved three subpopulations; Structure resolved four subpopulations. FST values were low (<0.05) for nearby populations and >0.15 for populations separated by expanses of unsuitable habitat. Isolation by distance was an existing but weak factor in determining genomic structure; isolation by environment and the intervening landscape explained a significant proportion of genetic distance. Hetaerina vulnerata populations were shown to be isolated by a lack of tree canopy coverage, an important habitat predictor for oviposition and territoriality. Thus, H. vulnerata populations are likely separated and are genetically isolated. Integrating SDMs with landscape genetics allowed us to identify populations separated by distance and unsuitable habitat, explaining population genetic patterns and probable fates for populations under future climate scenarios.

Context Cultivation and crop rotation, influenced by federal policy, prices, and precipitation, are significant sources of land-cover heterogeneity. Characterization of heterogeneity is required to identify areas and trends of stability or change. Objectives We analyzed a land-cover time series within a prominent agroecosystem in the US, the Yazoo-Mississippi Delta (the Delta), as a case study of which metrics capture dynamics of landscape composition, configuration, connectivity, and context. Methods An assessment of land cover- from 2008 to 2021- was conducted and analyzed for potential differences among three Farm Bill eras. Twelve out of 23 metrics (including three new ones presented herein) examined were useful in characterizing land-cover heterogeneity. Results Although there was no increase in cultivated land, > 72% of the Delta experienced changes in land-cover type, and ~ 3% of the Delta was stable monoculture. Configurational metrics varied across years for soybeans, cotton, and rice, indicating prevalence of field-level changes in composition; connectivity metrics revealed isolation of upland forest and rice. The amount of corn was positively associated with the previous year’s commodity prices and negatively with precipitation whereas soybean acreage was lower in high-precipitation years and more dependent on commodity prices. Farm Bill effects were mixed among categories, whereas CRP generally declined. Conclusions The Delta experienced land-cover change with no net loss or gain of cultivated lands. Using 12 metrics that captured temporal shifts in spatial patterns, we characterized this agroecosystem as a shifting mosaic. Our approach may be useful for identifying areas of spatio-temporal heterogeneity or stability, with implications on resource management.

In a two-year field study across 58 isolated wetlands in Texas (USA), we examined whether odonate (Insecta: Odonata) assemblages were structured by local environmental filters or instead simply reflected the use of any available water in this semi-arid region. Cluster analysis resolved three wetland groupings based on environmental characteristics (hydroperiod, water chemistry, vegetation); 37 odonate species were detected at these wetlands. The most speciose assemblages occurred at wetlands with longer hydroperiods; these sites also had the most species found at no other wetland type. Ordination plots indicated some filtering with respect to the hydroperiod, but there was only mixed or weak support with respect to other local factors. Because water persistence was the strongest driver maintaining odonate diversity in this region, regardless of water quality or vegetation, beggars cannot be choosers in this system and conservation efforts can focus on water maintenance or supplementation.

In the United States, several land use and land cover (LULC) data sets are available based on satellite data, but these data sets often fail to accurately represent features on the ground. Alternatively, detailed mapping of heterogeneous landscapes for informed decision-making is possible using high spatial resolution orthoimagery from the National Agricultural Imagery Program (NAIP). However, large-area mapping at this resolution remains challenging due to radiometric differences among scenes, landscape heterogeneity, and computational limitations. Various machine learning (ML) techniques have shown promise in improving LULC maps. The primary purposes of this study were to evaluate bagging (Random Forest, RF), boosting (Gradient Boosting Machines [GBM] and extreme gradient boosting [XGB]), and stacking ensemble ML models. We used these techniques on a time series of Sentinel 2A data and NAIP orthoimagery to create a LULC map of a portion of Irion and Tom Green counties in Texas (USA). We created several spectral indices, structural variables, and geometry-based variables, reducing the dimensionality of features generated on Sentinel and NAIP data. We then compared accuracy based on random cross-validation without accounting for spatial autocorrelation and target-oriented cross-validation accounting for spatial structures of the training data set. Comparison of random and target-oriented cross-validation results showed that autocorrelation in the training data offered overestimation ranging from 2% to 3.5%. The XGB-boosted stacking ensemble on-base learners (RF, XGB, and GBM) improved model performance over individual base learners. We show that meta-learners are just as sensitive to overfitting as base models, as these algorithms are not designed to account for spatial information. Finally, we show that the fusion of Sentinel 2A data with NAIP data improves land use/land cover classification using geographic object-based image analysis.

BACKGROUND:Anthropogenic activities occurring throughout the Sonoran Desert are replacing and fragmenting habitat and reducing landscape connectivity for the Sonoran desert tortoise (Gopherus morafkai). Understanding how the structure of the landscape influences tortoise habitat use and movement can help develop strategies for mitigating the impacts of these landscape alterations, which are conservation actions needed to support the species' long-term persistence. However, how natural and anthropogenic features influence fine-scale habitat use and movement of Sonoran desert tortoises remains unclear. METHODS:The goals of this study were to (1) understand how characteristics of the landscape shape tortoise habitat use and movement in order to (2) identify factors that may reduce habitat use or threaten landscape connectivity for the species by discouraging or restricting movement. We collected GPS telemetry data from 17 adult tortoises tracked for two summer monsoon seasons, when tortoises are most active, in a U.S. National Monument along the international border between Arizona, USA and Sonora, Mexico. We used Hidden Markov Models (HMMs) to assign GPS locations to an encamped or a moving state. We used the moving state data in integrated Step Selection Analyses (iSSA) to examine how range-resident Sonoran desert tortoises select habitat and respond to landscape features while moving. RESULTS:Tortoises selected to move through areas of intermediate vegetation cover and terrain ruggedness and avoided areas far from desert washes and close to low-traffic roads. Tortoises increased their speed when approaching or crossing low-traffic roads but showed no detectable response to a highway. CONCLUSION:Bare earth or high vegetation cover, flat or extremely rugged terrain, areas far from desert washes, and low-traffic roads may discourage or restrict tortoise movement. Therefore, preventing the development of roads, activities that degrade washes, and activities that thin, remove, or greatly increase vegetation cover may encourage tortoise habitat use and movement within those habitats.

Globally, freshwater ecosystems and the organisms that depend on them are at risk. Dragonflies and damselflies (collectively, “odonates”) have a history of being used as bioindicators of freshwater habitat quality due to their wide range in environmental sensitivities across species and because they are relatively accessible. However, the nymphal stage is severely understudied compared to the adult stage, which inhibits conservation efforts. Somatochlora calverti is a rare species of dragonfly in the family Corduliidae; members of the genus Somatochlora are notoriously difficult to find and collect in the field as nymphs and adults. Somatochlora calverti is known primarily from the Florida panhandle but has been documented in Alabama, Georgia, and South Carolina. The nymph of this species is speculated to use seepage streams analogous to sympatric congeners; however, the nymph has never been collected in the field and, therefore, its specific microhabitat is unknown. We conducted a review from a suite of informational sources to generate a holistic consensus on what is defined to be suitable reproductive habitat for S. calverti. Sources identified eight major environmental characteristics that are likely to harbor S. calverti: shallow seepage streams, including steephead ravines, with undercut banks and mats of Sphagnum moss adjacent to intact sandhill forest. These ecosystems are being lost and degraded by anthropogenic activity, which has considerable impacts on the persistence of habitat specialists, including S. calverti, and managers’ ability to conserve them.

AimDeforestation of the Atlantic Forest of eastern Paraguay has been recent but extensive, resulting in a fragmented landscape highly influenced by forest edges. We examined edge effects on multiple dimensions of small mammalian diversity.LocationForest fragments of eastern Paraguayan Atlantic Forest.MethodsWe trapped small mammal species at different distances from the forest edge (DTE) in reserves and estimated multiple dimensions of diversity per site. Similarity analysis identified species clusters that best described the patterns of diversity across reserves. Multivariate ordination and linear mixed models were used to determine the influence of DTE on various dimensions of small mammal diversity.ResultsThere was an increase in richness and abundance along a DTE gradient, and remnants with higher edge:area ratios showed higher richness and abundance, independent of remnant size. Species at edges were generalists, open-habitat species or exotic species (spillover effect). We found higher phylogenetic diversity and functional richness and divergence towards forest edges. Spillover of non-forest and invasive species best explained richness, generalist forest species best explained total abundance, abundance of Hylaeamys megacephalus best explained diversity and evenness metrics and the presence of Marmosa paraguayana best explained various phylogenetic diversity models. None of the models that included megafauna or social factors were shown to be important in explaining patterns as a function of DTE.Main ConclusionsWe found strong support for a spillover effect and mixed support for complementary resource use and enhanced habitat resources associated with ecotones. Generalists characterized edge assemblages but not all generalists were equivalent. Edges showed more phylogenetically and functionally distinct assemblages than the interior of remnants. There was a conservation of functional diversity; however, open-habitat species, habitat generalists and exotic species boosted diversity near forest edges. Mechanisms governing diversity along forest edges are complex; disentangling those mechanisms necessitates the use of multiple dimensions of diversity.

Linear anthropogenic barriers may reduce structural landscape connectivity for wildlife. Using graph-based connectivity indices, we modeled the potential impacts of linear barriers on structural connectivity and on individual patch importance at different biologically justified dispersal distance thresholds for the Sonoran desert tortoise, a wide-ranging species for which anthropogenic barriers may be reducing structural landscape connectivity. To characterize the potential impacts of barriers on structural connectivity for the Sonoran desert tortoise, we compared network compartmentalization, individual habitat patch importance, and the spatial distribution of important habitat patches for models of structural connectivity reflecting the landscape prior to the development of linear barriers to models depicting current linear barriers in the landscape at different distance thresholds. Linear barriers fragmented the habitat patch network into a minimum of 239 patch components. Compartmentalization increased little as dispersal distance thresholds exceeded 10 km. In barrier simulations, patch importance mostly decreased and the spatial distribution of important patches shifted south. Barriers are limiting structural connectivity for Sonoran desert tortoises and may prevent dispersal events, rescue effects in the event of localized extinctions, and successful range shift in response to climate change. Management efforts targeted at enhancing connectivity for ecological processes or movements occurring at 5–10 km may enhance the potential for longer-distance movements or generational dispersal occurring at a greater extent. Our methods provide an efficient framework for assessing changes in structural connectivity on a landscape extent that may be applied to addressing different problems or questions related to landscape connectivity.

Large-area land use land cover (LULC) mapping using high-resolution imagery remains challenging due to radiometric differences between scenes, the low spectral depth of the imagery, landscape heterogeneity, and computational limitations. Using a random forest (RF)- supervised machine-learning algorithm, we present a geographic object-based image analysis approach to classifying a large mosaic of 220 National Agriculture Imagery Program orthoimagery into lulc categories. The approach was applied in central Texas, USA, covering over 6000 km2. We generated 36 variables for each object and accounted for spatial structures of sample data to determine the distance at which samples were spatially independent. The final rf model produced 94.8% accuracy on independent stratified random samples. In addition, vegetation and water indices, the mean and standard deviation of principal components, and texture features improved classification accuracy. This study demonstrates a cost-effective way of producing an accurate multi-class land use/land cover map using high-spatial/low-spectral resolution orthoimagery.

Anthropogenic land-cover change is modifying ecosystems at an accelerating rate. Changes to ecomorphologically variable taxa within those ecosystems serve as early-warning signs that resources on which humans and other animals depend are being altered. One known ecomorphologically variable taxon is Hylogomphus geminatus, a species of dragonfly in the southeastern United States that shows pronounced variation in total body length across its limited geographic range. We measured total length of live as well as preserved museum specimens of H. geminatus and the sympatric species Progomphus obscurus (as a means for comparison). Both species showed significant size differences linked to HUC-8 watersheds in which they occur. H. geminatus showed additional significant differences on either side of the Apalachicola River, Florida, for all comparisons by sex. In overlapping watersheds, the species tended to show the same trends in length relative to their respective averages. Smaller body length was associated with more urban and agricultural land cover. These findings indicate that ecomorphological variation is tied to the watershed scale and point to significant variations on either side of the Apalachicola River. More thorough future analyses would be needed to verify trends in body length and identify the drivers behind them.

We compared the prevalence and intensity of Arrenurus sensu stricto water mite parasites on Enallagma civile Hagen in Selys, 1853 (Zygoptera: Coenagrionidae) from 10 freshwater wetlands (playas) in two different land-cover contexts in western Texas from 2006-2007. Vulnerability to parasitism may be a consequence of disturbance, so we predicted that the more natural form of regional land cover (grasslands) surrounding playas should be associated with a lower water mite load than more disturbed land cover (tilled croplands). Additionally, we examined Arrenurus occurrence and intensity of infection by host sex. Overall prevalence was 38.46% of 130 damselflies sampled having mites; this varied by land-cover type but with opposite trends between years. Overall average parasite load was ~11 water mites per infected host (range: 1-40 mites); intensity was significantly higher in hosts from cropland playas in 2006, but there was no difference by surrounding land cover in 2007. Although there were consistent trends in both years of more males being parasitized than females, the highly uneven distribution of parasites on hosts and differences in average mite load between years generated variability that obscured any statistically significant patterns. Thus, land-cover context surrounding playas, but not host sex, had an impact on parasite load in one of the two years of our study. Future work is needed to identify the mechanisms by which land cover may affect water mite-odonate host-parasite relationships as well as the role of the odonate assemblage as a whole in dispersal of parasites in a temporally dynamic wetland network.

known as a marine biologist, Darnell encouraged research in the emerging science of ecology.This was a trait that Gary later carried on with his own mentees, who were given the freedom to work on various taxa and topics.Gary's M.S. research focused on the effects of pesticides on small mammals, and much of the research for the rest of his career was related to the effects of stresses and spatial heterogeneity on small mammals and ecosystem processes.After his M.

Conservation efforts often focus on a single species, but this approach is inefficient for agencies dealing with many declining species at risk of extinction. Leveraging already-funded management for additional species can help stretch limited resources to conserve more biodiversity. However, evaluation of the efficacy of such an umbrella approach is typically lacking, does not explicitly consider outcomes of management treatments, or only evaluates one or a few species. We developed a method to evaluate the ability of management for the lesser prairie-chicken (Tympanuchus pallidicinctus) to offer an umbrella of protection for non-target species at risk of decline. To accomplish this, we predicted the conservation outcomes of lesser prairie-chicken management for overlapping at-risk species and created an index of conservation benefit to evaluate the effectiveness of the lesser prairie-chicken as an umbrella species for conservation. We conducted a literature review for 77 at-risk species that overlap in range with the lesser prairie-chicken to determine the effects (benefit, cost, or neutral) of the primary conservation actions taken to manage lesser prairie-chicken habitat. We determined that 84 % of the species were expected to receive a net conservation benefit from management for lesser prairie-chicken, 8 % would incur a net cost, and 8 % would have a net balance of costs and benefits. These results suggest that the lesser prairie-chicken functions as an umbrella of protection for other grassland species, providing a net conservation benefit. Our index-based approach serves as a model for evaluating the efficacy of proposed surrogate species on a community of organisms.