Habitat Covariates Research Articles

Large-scale overlap and fine-scale avoidance: assessing interactions between coyotes, bobcats, and cougars at multiple scales

Abstract In multi-carnivore systems individuals must forage and reproduce while also competing with other carnivores and avoiding intraguild predation. These interactions may vary by strength and scales across different ecosystems. We used occupancy analyses and attraction–avoidance indices to assess large- and fine-scale interactions, respectively, between Cougars (Puma concolor), Bobcats (Lynx rufus), and Coyotes (Canis latrans) in northeast Oregon based on data from camera traps set during the summer and fall of 2016 and 2017. To determine the importance of habitat preferences and spatial overlap, we compared occupancy (probability of use) models that included habitat covariates with and without species co-occurrence terms. Detection was different for all species and was influenced by roads, game trails, and canopy cover. Terrain ruggedness was important for all species; Bobcats showed the strongest preference for ruggedness, Cougars showed a weak preference, and Coyotes significantly but weakly avoided rugged areas. The top probability of use model showed that Bobcats and Coyotes were 1.88 times more likely to spatially overlap on roads. We also found evidence that interactions among carnivores were scale-dependent. At larger scales, habitat preference was more important than interactions with other carnivores, whereas at finer scales, most carnivores avoided each other. At fine spatiotemporal scales, our attraction–avoidance analyses showed that Bobcats avoided Coyotes and Coyotes avoided both Bobcats and Cougars. These findings suggest that carnivores in our study system were adept at minimizing conflict through fine-scale avoidance in space and time, that the human footprint can influence carnivore interactions, and that studying carnivore interactions at multiple scales is important for understanding the effects of spatial overlap and potential competition.

Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing

The Arctic-Boreal zone (ABZ) covers over 26 million km2 and is home to numerous duck species; however, understanding the spatiotemporal distribution of their populations across this vast landscape is challenging, in part due to extent and data scarcity. Species abundance models for ducks in the ABZ commonly use static (time invariant) habitat covariates to inform predictions, such as wetland type and extent maps. For the first time in this region, we developed species abundance models using high-resolution, time-varying wetland inundation data produced using satellite remote sensing methods. This data captured metrics of surface water extent and inundated vegetation in the Peace Athabasca Delta, Canada, which is within the NASA Arctic Boreal Vulnerability Experiment core domain. We used generalized additive mixed models to demonstrate the improved predictive value of this novel data set over time-invariant data. Our findings highlight both the potential complementarity and efficacy of dynamic wetland inundation information for improving estimation of duck abundance and distribution at high latitudes. Further, these data can be an asset to spatial targeting of biodiversity conservation efforts and developing model-based metrics of their success under rapidly changing climatic conditions.

A two-step species distribution modeling to disentangle the effect of habitat and bioclimatic covariates on Psacothea hilaris, a potentially invasive species

Integrating host plants in distribution modeling of phytophagous species and disentangling the effect of habitat and bioclimatic variables are key aspects to produce reliable predictions when the aim is to identify suitable areas outside species’ native range. To this aim, we implemented a framework of Species Distribution Model aimed at predicting potential suitable areas of establishment for the beetle Psacothea hilaris across the world. Since habitat (including host plants) and bioclimatic variables affect species distribution according to processes acting at different geographical scales, we modeled these variables separately. For the species native range, we fitted a habitat (HSM) and a bioclimatic (BSM) suitability model calibrated on a local and a large scale, respectively; the overall suitability map was obtained as the spatial product of HSM and BSM projection maps. ROC, TSS and Cohen’s Kappa obtained in validation confirmed a good predictive performance of modeling framework. Within HSM, host plants played a substantial effect on species presence probability, while among bioclimatic variables, precipitation of the warmer quarter and isothermality were the most important. Native HSM and BSM models were used to realize an overall suitability map at world scale. At global scale, many areas resulted suitable for habitat, some for bioclimate, and few for both conditions; indeed, if the species would not be able to modify its bioclimatic niche, it might not be considered a major invasive species. However, the high rate of range expansion documented for P. hilaris in Northern Italy, a poorly suitable bioclimatic area, suggests a plasticity of the species that requires increasing the level of attention to its invasive potential.

Long‐term occupancy monitoring reveals value of moderate disturbance for an open‐habitat specialist, the Stephens' kangaroo rat (Dipodomys stephensi)

AbstractFor species of conservation concern, long‐term monitoring is vital to properly characterize changes in population distribution and abundance over time. In addition, long‐term monitoring guides management decisions by informing and evaluating the efficacy of management actions. A long‐term monitoring initiative for the federally threatened Stephens' Kangaroo rat (Dipodomys stephensi, SKR) was established in 2005, across 628 hectares within Marine Corps Base Camp Pendleton (MCBCP), San Diego, California, USA. From 2005 to 2018, we tracked trends in area occupied by SKR, trends in relative SKR densities within occupied habitat, and modeled probabilities of SKR occupancy, colonization, extinction, with habitat, climate, and disturbance covariates. Area occupied by SKR increased almost 2‐fold from 2005 to 2018 on MCBCP, while density in occupied habitat increased almost 3‐fold. Increased area occupied was correlated with increases in estimated density among years, indicating SKR population growth occurs by expansion into suitable habitat patches, as well as increases in numbers within occupied habitat. SKR occupancy was positively associated with gentle slopes (<10%) and moderate open ground (40–80%) and forb cover (>40%). They were more likely to colonize previously unoccupied habitat when there were moderate levels of open ground (40–80%) and low shrub cover (<20%), while more likely to go locally extinct in areas with high slopes (>10%), less open ground (<20%), and increased non‐native grass cover (>40%). Additionally, probabilities of SKR occupancy and colonization were higher in areas with moderate levels of disturbance, which was positively associated with open ground and forb cover. We conclude that long‐term occupancy and density monitoring is effective in informing status and trends of spatially dynamic species and that moderate habitat‐based disturbance is compatible with the management of SKR.

Limited spatiotemporal niche partitioning among mesocarnivores in Gorongosa National Park, Mozambique.

Competition drives community composition and structure in many ecosystems. Spatial and temporal niche partitioning, in which competing species divide the environment in space or time, are mechanisms that may allow for coexistence among ecologically similar species. Such division of resources may be especially important for carnivores in African savannas, which support diverse carnivore assemblages. We used camera traps to explore patterns of spatial and temporal niche partitioning among four mesocarnivore species in Mozambique's Gorongosa National Park: large-spotted genet (Genetta maculata), African civet (Civettictis civetta), honey badger (Mellivora capensis) and marsh mongoose (Atilax paludinosus). We applied a multispecies occupancy model to evaluate spatial partitioning among mesocarnivores and to quantify the environmental factors that affect species-specific habitat use, including relative lion (Panthera leo) activity. We also analyzed the temporal activity overlap of the four focal species. We identified species-specific habitat covariates that influenced detection probabilities but found no evidence of spatial or temporal partitioning among mesocarnivores in the study system. Indeed, we found some evidence for spatial co-occurrence between two of our focal species: African civet and marsh mongoose. There may be limited competition among mesocarnivores in this system, perhaps due to niche and diet differentiation among these species and an abundance of resources. While we found limited evidence that lion activity impacts mesocarnivores, ongoing monitoring of intraguild interactions is vital as apex predator populations recover in the system. This study adds to a growing understanding of African mesocarnivore ecology and highlights the importance of understanding these dynamics for effective multispecies conservation and restoration.

Chronobiological perspectives: Association between meal timing and sleep quality.

Meal timing has been associated with metabolism and cardiovascular diseases; however, the relationship between meal timing and sleep quality remains inconclusive. This study aims to investigate the relationship between meal timing and sleep quality from a chronobiological perspective. This study utilized data from the NHANES for the years 2005-2008, including a cohort of 7,023 participants after applying exclusion criteria. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Meal timing was analyzed based on two 24-hour dietary recalls from each individual, considering the timing of the initial and final meals, meal duration, and frequency of meal occasions. Multiple linear regression models and hierarchical analyses were employed to examine the relationship between meal timing and PSQI scores, adjusting for various demographic and habitat covariates. Statistical analysis revealed a positive correlation between delayed meal timings, increased meal occasions, and elevated PSQI scores, indicating that later meal timing are intricately linked with diminished sleep quality. Both later meal timings and more frequent meal occasions were significantly associated with poorer sleep quality. Compared to the first tertile, the β (95%CI) values of the third tertile were 0.545 (0.226, 0.864) for first meal timing, 0.586 (0.277, 0.896) for midpoint meal timing, 0.385 (0.090, 0.680) for last meal timing, and 0.332 (0.021, 0.642) for meal occasions in the adjusted models. These findings suggest that late initial, midpoint, and final meal timing, as well as more frequent meal occasions, are chrono-nutrition patterns associated with poor sleep quality.

Dynamic occupancy modeling of a cryptic ground-dwelling pheasant species in the Upper Blue Nile Basin in Ethiopia

Modeling the occupancy of species in the context of habitat components is a crucial step to deliver an appropriate conservation strategy. Accounting for imperfect detection in occupancy models helps to conclude on true species distribution and occupancy. We used dynamic occupancy modeling to investigate the influence of habitat covariates on occupancy dynamics of the Near Threatened Harwood’s Francolin (Pternistis harwoodi) in the Upper Blue Nile Basin in Ethiopia. We used direct observation and playback technique to collect presence/absence data both during a wet and a dry season in 2019 and 2020. By accounting for species’ imperfect detection, the model averaged estimates of occupancy probabilities (mean ± SE) across respective seasons were 0.81 ± 0.08 and 0.79 ± 0.07 and detection probabilities were 0.47 ± 0.08 and 0.62 ± 0.06. The colonization and local extinction probability estimates between seasons were 0.59 ± 0.20 and 0.12 ± 0.07, respectively. We demonstrate that occupancy probability significantly decreased with increasing both Normalized Difference Vegetation Index (NDVI: ꞵmean ± SE = −1.83 ± 0.66; 95% CI: −3.12, −0.54) and quadratic term of slope (SL2 = −1.51 ± 0.62; 95% CI: −2.73, −0.29) in the study area. Furthermore, human disturbance index (HDI: = −1.06 ± 0.54; 95% CI: −2.12, −0.004) significantly negatively influenced the occupancy of the species. As we hypothesized, the detection probability increased significantly as a function of average temperature (0.37 ± 0.13; 95% CI: 0.12, 0.63). There were no statistically significant associations among covariates and the dynamic parameters, yet important covariates such as NDVI slightly negatively influenced colonization, whereas HDI positively influenced local extinction. The aversion of the species towards human disturbance and its persistence at lower NDVI and lower slopes has important implications for conservation strategy in the area. The current study demonstrates empirical evidence of dynamic occupancy modeling for a cryptic ground-dwelling pheasant species in the Upper Blue Nile Basin. Further study is recommended to understand spatiotemporal species-habitat association at fine and landscape scales.

Linking species distribution models with structured expert elicitation for predicting management effectiveness

AbstractEffective biodiversity conservation requires robust and transparent prioritization of management actions. However, this is often hampered by a lack of spatially‐explicit data on habitat variables and empirical data on the effect of management actions. Although approaches exist that integrate structured expert elicitation (SEE) with species distribution models (SDMs) to encode species responses across habitat gradients, difficulties remain in predicting management outcomes under different settings, at a region‐wide scale when key habitat covariates are not spatially explicit. Therefore, we developed an approach to integrate SDMs with SEE to capture expert understanding of likely outcomes of management actions for individual frog species, and use this to spatially predict the effect of management actions. We demonstrate our approach across approximately 4000 wetlands in greater Melbourne, Victoria, Australia. As a measure of management effectiveness, we used the change in predicted probability of occurrence of seven frog species at wetlands 10 years after conservation actions are implemented (or not implemented). Management effect was elicited from experts under six scenarios. Individual expert estimates were aggregated using generalized linear models that were then used to spatially predict expected management effects, and a measure of uncertainty in the prediction, at all wetlands. Predicted management effect was strongly influenced by species initial probability of occurrence, with enhancing aquatic and surrounding vegetation an effective action for most species. We discuss practical challenges and recommend solutions in the integration of SDMs and SEE for the spatial prediction of management effect.

Eat or be eaten: Implications of potential exploitative competition between wolves and humans across predator-savvy and predator-naive deer populations.

Recolonization of predators to their former ranges is becoming increasingly prevalent. Such recolonization places predators among their prey once again; the latter having lived without predation (from such predators) for a considerable time. This renewed coexistence creates opportunities to explore predation ecology at both fundamental and applied levels. We used a paired experimental design to investigate white-tailed deer risk allocation in the Upper and Lower Peninsulas (UP and LP) in Michigan, USA. Wolves are functionally absent in the LP, while deer in the UP coexist with a re-established wolf population. We treated 15 sites each in UP and LP with wolf olfactory cues and observed deer vigilance, activity, and visitation rates at the interface of habitat covariates using remote cameras. Such a paired design across wolf versus no-wolf areas allowed us to examine indirect predation effects while accounting for confounding parameters such as the presence of other predators and human activity. While wolf urine had no effect across most metrics in both UP and LP, we observed differences in deer activity in areas with versus without wolves. Sites treated with wolf urine in the UP showed a reduction in crepuscular deer activity, compared to control/novel-scent treated sites. Furthermore, we observed a strong positive effect of vegetation cover on deer vigilance in these sites. This indicates that simulated predator cues likely affect deer vigilance more acutely in denser habitats, which presumably facilitates predation success. Such responses were however absent among deer in the LP that are presumably naïve toward wolf predation. Where human and non-human predators hunt shared prey, such as in Michigan, predators may constrain human hunting success by increasing deer vigilance. Hunters may avoid such exploitative competition by choosing hunting/bait sites located in open areas. Our results pertaining to fundamental predation ecology have strong applied implications that can promote human-predator coexistence.

Occupancy of the Ethiopian endemic Moorland Francolin in pristine and degraded Afroalpine biome using a camera trap approach.

Occupancy modeling is an essential tool for understanding species-habitat associations, thereby helping to plan the conservation of rare and threatened wildlife species. The conservation status and ecology of several avian species, particularly ground-dwelling birds, are poorly known in Ethiopia. We used camera trap-based occupancy modeling to investigate habitat covariate influence on occupancy (Ψ) and detection probability (ρ) estimates of Moorland Francolins Scleroptila psilolaema from spatially replicated surveys across both relatively pristine and disturbed landscapes in the Afroalpine biome of Ethiopia. Model-averaged estimate of across all sites was 0.76 (SD = 0.28) and was 0.77 (SD = 0.13) in the pristine landscape. The of the species in the disturbed landscape was 0.56 (SD = 0.19) and was 0.48 (SD = 0.06). As hypothesized, based on our model-averaged beta coefficient estimates (βmean ± SE), predators significantly negatively influenced the occupancy of Moorland Francolins in pristine habitat. We also found a significant positive association of occupancy with herb species richness. Contrary to our prediction, distance to road significantly negatively influence the occupancy of the species, suggesting that occupancy probability was highest in proximity to roadsides and trails in the pristine habitat. There was no significant influence of habitat covariates on the occupancy of the species in the disturbed habitat. The most important covariates that significantly influence the detectability of the species in pristine habitat included sampling occasion and precipitation. The greater occupancy and detectability of this endemic species in the pristine habitat could be linked with the particular conservation status and management of this biodiversity hotspot in the central highlands of Ethiopia. Our results suggest that strict legal enforcement is required to sustainably preserve Moorland Francolins and the ecological integrity of the entire Afroalpine biome. We recommend using camera traps in order to develop realistic and effective conservation and management strategies for rare, sensitive, cryptic, and ground-dwelling animals in the region.

A preliminary camera trapping study of mammals of Monti Lepini (Central Italy)

We used 52 camera traps to survey mammal species in the Lepini Mountains (Lazio, Central Italy) during three trapping sessions. Thirteen mammal species have been recorded. Compared to data based on previous opportunistic observations (2000-2018), camera trapping has quickly increased knowledge about the distribution of species, especially for elusive ones. We modelled species and average community occupancy also considering habitat covariates in a hierarchical modelling framework. Occupancy at community level was positively impacted by woods and negatively impacted by open habitats, indicating that the ongoing reforestation of the area may favour mammal diversity. Open surfaces have a negative effect on the presence of Sciurus vulgaris, a species for which our study confirms extensive recolonization of the area. We have also shown that woods increase the probability of occupation by Canis lupus and Felis silvestris, confirming that these species could be negatively impacted by increased deforestation.

Waterfowl distribution and productivity in the Prairie Pothole Region of Canada: tools for conservation planning

AbstractSpecies conservation requires an understanding of the factors and interactions affecting species distribution and behavior, habitat availability and use, and corresponding vital rates at multiple temporal and spatial scales. Opportunities to investigate these relationships across broad geographic regions are rare. We combined long‐term waterfowl population surveys, and studies of habitat use and breeding success, to develop models that identify and incorporate these interactions for upland‐nesting waterfowl in the Prairie Pothole Region (PPR) of Canada. Specifically, we used data from the annual Waterfowl Breeding Population and Habitat Survey (1961–2009) at the survey segment level and associated habitat covariates to model and map the long‐term average duck density across the Canadian PPR. We analyzed nest location and fate data from approximately 25,000 duck nests found during 3 multi‐year nesting studies (1994–2011) to model factors associated with nest survival and habitat selection through the nesting season for the 5 most common upland nesting duck species: mallard (Anas platyrhynchos), gadwall (Mareca strepera), blue‐winged teal (Spatula discors), northern shoveler (Spatula clypeata), and northern pintail (Anas acuta). Duck density was highly variable across the Canadian PPR, reflecting positive responses to local wetland area and count, and amounts of cropland and grassland, a regional positive response to latitude, and a negative response to local amounts of tree cover. Nest survival was affected by temporal and spatial variables at multiple scales. Specifically, nest survival demonstrated interactive effects among species, nest initiation date, and nesting cover type and was influenced by relative annual wetness, population density, and surrounding landscape composition at landscape scales, and broad geographic gradients (east‐west and north‐south). Likewise, species‐specific probability of nest habitat selection was influenced by timing of nest initiation, population density, relative annual wetness, herbaceous cover, and tree cover in the surrounding landscape, and location within the Canadian PPR. We combined these models, with estimates of breeding effort (nesting, renesting, and nest attempts) from existing literature, in a stochastic conservation planning model that estimates nest distribution and success given spatiotemporal variation in duck density, habitat availability, and influential covariates. We demonstrate the use of this model by examining various conservation planning scenarios. These models allow estimation of local, landscape, and regional influence of conservation investments and other landscape changes on the productivity of breeding duck populations across the PPR of Canada. These models lay the groundwork for the incorporation of conservation delivery costs for full return‐on‐investment analyses and scenario analyses of climate, habitat, and land use change in regional and continental population models.

Understanding carnivore interactions in a cold arid trans-Himalayan landscape: What drives co-existence patterns within predator guild along varying resource gradients?

Predators compete for resources aggressively, forming trophic hierarchies that shape the structure of an ecosystem. Competitive interactions between species are modified in the human-altered environment and become particularly important where an introduced predator can have negative effects on native predator and prey species. The trans-Himalayan region of northern India has seen significant development in tourism and associated infrastructure over the last two decades, resulting in many changes to the natural setting of the landscape. While tourism, combined with unmanaged garbage can facilitate red fox (Vulpes vulpes), it also allows free-ranging dogs (Canis lupus familiaris), an introduced mesopredator to thrive, possibly more than the native red fox. We look at the little-known competitive dynamics of these two meso-carnivores, as well as their intra-guild interactions with the region's top carnivores, the snow leopard (Panthera uncia) and the Himalayan wolf (Canis lupus chanco). To study interactions between these four carnivores, we performed multispecies occupancy modeling and analyzed spatiotemporal interactions between these predators using camera trap data. We also collected scat samples to calculate dietary niche overlaps and determine the extent of competition for food resources between these carnivores. The study found that, after controlling for habitat and prey covariates, red fox site use was related positively to snow leopard site use, but negatively to dog and wolf site use. In addition, site use of the dog was associated negatively with top predators, that is, snow leopard and Himalayan wolf, while top predators themselves related negatively in their site use. As anthropogenic impacts increase, we find that these predators coexist in this resource-scarce landscape through dietary or spatiotemporal segregation, implying competition for limited resources. Our research adds to the scant ecological knowledge of the predators in the region and improves our understanding of community dynamics in human-altered ecosystems.

Evaluating translocation success of wild eastern hellbenders (Cryptobranchus alleganiensis alleganiensis) in Blue Ridge Ecoregion streams using pre- and post-translocation home range sizes and movement metrics.

Translocations of freshwater species have become a widespread conservation strategy to mitigate the impacts of habitat fragmentation, yet they are not often rigorously monitored using animal movement data to determine their success. We demonstrate the value of monitoring pre- and post-translocation movements and home-range sizes of a fully-aquatic, benthic stream salamander, the eastern hellbender (Cryptobranchus a. alleganiensis) to determine translocation success. We studied the home range sizes, movements, and habitat use of individuals (n = 27) in two self-sustaining populations (S1 & S2) for one year, and then subsequently collected similar data from a subset of these individuals (n = 17) that were translocated into two nearby streams (T1 & T2) with dam-isolated, declining populations in the Blue Ridge Ecoregion of Tennessee. We collected 1,571 location data points (869 pre-translocation and 715 post-translocation) from four study sites, and evaluated effects of mass, sex, and pre-translocation home range size/sedentariness, as well as habitat covariates on home range size and movements. Hellbender home range sizes increased from pre-translocation estimates at both sites, but response depended primarily on physical characteristics of release sites. Home range and fine-scale movement metrics indicated that hellbenders translocated from S1 to T1 settled in more quickly, had greater site fidelity, and smaller home ranges than hellbenders translocated from S2 to T2. Hellbender movements were influenced by cover rock size and density rather than individual characteristics. Study-long survival rates of translocated hellbenders increased from S1 to T1 (80% to 100%) and decreased from S2 to T2 (76% to 33%). Monitoring pre- and post-translocation movements was a valuable method for evaluating short-term translocation success in a freshwater environment. For future hellbender translocations, managers should prioritize selecting suitable release sites with contiguous boulder-dense areas (1-2 per m2), adequate prey (crayfish) densities (>1/m2), and habitats with low risk of predation.

Joint spatiotemporal models to predict seabird densities at sea

IntroductionSeabirds are abundant, conspicuous members of marine ecosystems worldwide. Synthesis of distribution data compiled over time is required to address regional management issues and understand ecosystem change. Major challenges when estimating seabird densities at sea arise from variability in dispersion of the birds, sampling effort over time and space, and differences in bird detection rates associated with survey vessel type.MethodsUsing a novel approach for modeling seabirds at sea, we applied joint dynamic species distribution models (JDSDM) with a vector-autoregressive spatiotemporal framework to survey data collected over nearly five decades and archived in the North Pacific Pelagic Seabird Database. We produced monthly gridded density predictions and abundance estimates for 8 species groups (77% of all birds observed) within Cook Inlet, Alaska. JDSDMs included habitat covariates to inform density predictions in unsampled areas and accounted for changes in observed densities due to differing survey methods and decadal-scale variation in ocean conditions. ResultsThe best fit model provided a high level of explanatory power (86% of deviance explained). Abundance estimates were reasonably precise, and consistent with limited historical studies. Modeled densities identified seasonal variability in abundance with peak numbers of all species groups in July or August. Seabirds were largely absent from the study region in either fall (e.g., murrelets) or spring (e.g., puffins) months, or both periods (shearwaters).DiscussionOur results indicated that pelagic shearwaters (Ardenna spp.) and tufted puffin (Fratercula cirrhata) have declined over the past four decades and these taxa warrant further investigation into underlying mechanisms explaining these trends. JDSDMs provide a useful tool to estimate seabird distribution and seasonal trends that will facilitate risk assessments and planning in areas affected by human activities such as oil and gas development, shipping, and offshore wind and renewable energy.

Extensive protected area coverage and an updated global population estimate for the Endangered Madagascar Serpent-eagleEutriorchis astur

SummaryKnowledge gaps regarding distribution, habitat associations, and population size for rare and threatened range-restricted taxa lead to uncertainty in directing conservation action. Quantifying range metrics and species–habitat associations using Species Distribution Models (SDMs) with remote-sensing habitat data can overcome these setbacks by establishing baseline estimates for biological parameters critical for conservation assessments. Area of Habitat (AOH) is a new range metric recently developed by the International Union for Conservation of Nature (IUCN) Red List. AOH seeks to quantify inferred habitat within a species’ range to inform extinction risk assessments. Here, we used SDMs correlating occurrences with remote-sensing covariates to calculate a first estimate of AOH for the Endangered Madagascar Serpent-eagleEutriorchis astur, and then updated additional IUCN range metrics and the current global population estimate. From these baselines we then conducted a gap analysis assessing protected area coverage. Our continuous SDM had robust predictive performance (Continuous Boyce Index = 0.835) and when reclassified to a binary model estimated an AOH = 30,121 km2, 13% less than the current IUCN range map. We estimated a global population of 533 mature individuals derived from the Madagascar Serpent-eagle AOH metric, which was within current IUCN population estimates. The current protected area network covered 95% of AOH, with the binary model identifying three additional key habitat areas as new protected area designations to fully protect Madagascar Serpent-eagle habitat. Our results demonstrated that correlating presence-only occurrences with remote-sensing habitat covariates can fill knowledge gaps useful for informing conservation action. Applying this spatial information to conservation planning would ensure almost full protected area coverage for this endangered raptor. For tropical forest habitat specialists, we recommend that potential predictors derived from remote sensing, such as vegetation indices and biophysical measures, are considered as covariates, along with other variables including climate and topography.

Density-habitat relationships of white-tailed deer (Odocoileus virginianus) in Finland.

In heterogeneous landscapes, resource selection constitutes a crucial link between landscape and population-level processes such as density. We conducted a non-invasive genetic study of white-tailed deer in southern Finland in 2016 and 2017 using fecal DNA samples to understand factors influencing white-tailed deer density and space use in late summer prior to the hunting season. We estimated deer density as a function of landcover types using a spatial capture-recapture (SCR) model with individual identities established using microsatellite markers. The study revealed second-order habitat selection with highest deer densities in fields and mixed forest, and third-order habitat selection (detection probability) for transitional woodlands (clear-cuts) and closeness to fields. Including landscape heterogeneity improved model fit and increased inferred total density compared with models assuming a homogenous landscape. Our findings underline the importance of including habitat covariates when estimating density and exemplifies that resource selection can be studied using non-invasive methods.

Patterns of species richness, abundance and individual-size distributions in native stream-fish assemblages invaded by exotic and translocated fishes.

Predicting the impacts of species introductions long has attracted the attention of ecologists yet there still is limited insight into how impacts on native assemblages vary with the degree of shared evolutionary context. Here, we used data from 535 stream-fish surveys from 15 catchments in north-eastern Spain (99,700 km2) to explore whether the relative effects on native fishes differ between fish introductions from two different ecoregions (i.e., evolutionary contexts), namely, catchments within Iberian Peninsula (i.e., 'translocated species') and catchments beyond Iberian Peninsula (i.e., 'exotic fishes'). We used hierarchical Bayesian models to relate taxon richness, abundance, and the individual-size distributions (ISDs) of native fishes to the presence, abundance, and weighted trophic level (TL) of translocated and exotic fishes, conditional on geographic and habitat covariates. Environmental covariates dominated the percentage of explained variance (≥ 65%) for all responses. Translocated fishes accounted for more of the explained variance than did exotic fishes for ISDs and abundance, but not for native fish species richness. The presence of translocated fishes was associated with lower abundance and richness of native fishes, with individuals being smaller in the presence of translocated fishes of higher TL. The presence of exotic fishes was associated with a greater abundance and richness of native fishes, with individuals generally being larger in the presence of exotic fishes. Our study suggests that translocated fishes could be as problematic as exotic fishes when angling and water transfers among catchments to deal with climate change may increase the establishment of translocated fishes. We also discuss the difficulties of using fish body size as species-blind, transferable assemblage-level trait in fish monitoring.

Landscape use and co-occurrence pattern of snow leopard (Panthera uncia) and its prey species in the fragile ecosystem of Spiti Valley, Himachal Pradesh.

The snow leopard (Panthera uncia) plays a vital role in maintaining the integrity of the high mountain ecosystem by regulating prey populations and maintaining plant community structure. Therefore, it is necessary to understand the role of the snow leopard and its interaction with prey species. Further, elucidating landscape use and co-occurrence of snow leopard and its prey species can be used to assess the differential use of habitat, allowing them to coexist. We used camera trapping and sign survey to study the interactions of snow leopard and its prey species (Siberian Ibex- Capra sibrica and Blue sheep-Pseudois nayaur) in the Spiti valley Himachal Pradesh. Using the occupancy modelling, we examined whether these prey and predator species occur together more or less frequently than would be expected by chance. To understand this, we have used ten covariates considering the ecology of the studied species. Our results suggest habitat covariates, such as LULC16 (barren area), LULC10 (grassland), ASP (aspect), SLP (slope) and DW (distance to water), are important drivers of habitat use for the snow leopard as well as its prey species. Furthermore, we found that the snow leopard detection probability was high if the site was used by its prey species, i.e., ibex and blue sheep. Whereas, in the case of the prey species, the probability of detection was low when the predator (snow leopard) was present and detected. Besides this, our results suggested that both species were less likely to detect together than expected if they were independent (Snow leopard—Ibex, Delta = 0.29, and snow leopard—blue sheep, Delta = 0.28, both the values are <1, i.e., avoidance). Moreover, despite the predation pressure, the differential anti-predation habitat selection and restriction of temporal activities by the prey species when snow leopard is present allows them to co-exist. Therefore, considering the strong link between the habitat use by the snow leopard and its prey species, it is imperative to generate quantitative long-term data on predator-prey densities and the population dynamics of its prey species in the landscape.

Large Felid and Peccary Habitat Use in Isolated and Contiguous Forest in Panamá: Implications for Conservation

Background and Research Aims Wildlife research in Panamá has focused primarily on protected areas along the Central Cordillera, where much of the remaining mature rainforest habitat is located. Information on large felid and prey habitat use in isolated habitats in Panamá is therefore limited. Here, we estimated occupancy and detection probabilities, as affected by habitat and anthropogenic influences, for 2 felid species (jaguars [ Panthera onca] and pumas [ Puma concolor]), and 2 prey species (white-lipped peccaries [ Tayassu pecari] and collared peccaries [ Pecari tajacu]). Methods Camera trap surveys were conducted during 2014–2015 at Cerro Hoya National Park (CHNP), an isolated remnant of tropical rainforest habitat, and Darién National Park (DNP), a large tract of continuous rainforest habitat. We used single-season, single-species occupancy modeling to estimate probabilities of detection and habitat use of our focal species. Results Three of the 4 focal species were detected at both sites, excluding white-lipped peccary at CHNP. Detection of jaguars and white-lipped peccaries at DNP was highest in February, while detection of collared peccaries at DNP and pumas at CHNP was highest in May and April, respectively. Peccary habitat use was uniform across sites and unaffected by habitat covariates. Both felids preferred habitat further away from anthropogenic disturbance, and jaguars preferred habitat at higher elevations than pumas. Conclusion We further confirm the presence of jaguars and likely local extirpation of white-lipped peccaries in CHNP. Temporal variations influenced detections of focal species. Habitat use of felids was negatively affected by anthropogenic disturbance and elevation. Implications for Conservation Habitat fragmentation and human activities negatively influenced habitat use of felids at both study areas. Given that CHNP serves as one of the last remnants of forest habitat outside the Central Cordillera, we recommend that CHNP be considered a top priority area for wildlife conservation in Panamá.