Density Surface Models Research Articles

A density surface model describing the habitat of the Critically Endangered Rice’s whale Balaenoptera ricei in the Gulf of Mexico

The newly recognized Rice’s whale Balaenoptera ricei is among the most endangered large whale species in the world and primarily occupies a region near the continental shelf break in the northeastern Gulf of Mexico (GoMex). We analyzed visual line-transect survey data collected throughout the northern GoMex from 2003-2019 and developed spatially explicit density maps using a density surface modeling approach to examine relationships between Rice’s whale density and bathymetric and oceanographic features. We identified water depth, surface chl a concentration, bottom temperature, and bottom salinity as key parameters that define the Rice’s whale habitat. This is consistent with upwelling of cold, high-salinity water along the continental shelf break and seasonal input of high-productivity surface water originating from coastal sources. The dominant circulation patterns in the GoMex, including the presence of Loop Current eddies, lead to increased productivity and likely play a role in maintaining high densities of forage species needed to support Rice’s whales. Extrapolation of the model suggests additional regions in Mexican waters of GoMex that may be suitable for Rice’s whales. This study informs the designation of critical habitat as defined by the US Endangered Species Act and will assist in marine spatial planning activities to avoid additional anthropogenic impacts to Rice’s whales associated with the development of wind energy and aquaculture.

Three decades of nearshore surveys reveal long-term patterns in gray whale habitat use, distribution, and abundance in the Northern California Current

The nearshore waters of the Northern California Current support an important seasonal foraging ground for Pacific Coast Feeding Group (PCFG) gray whales. We examine gray whale distribution, habitat use, and abundance over 31 years (1992–2022) using standardized nearshore (< 5 km from shore) surveys spanning a large swath of the PCFG foraging range. Specifically, we generated density surface models, which incorporate detection probability into generalized additive models to assess environmental correlates of gray whale distribution and predict abundance over time. We illustrate the importance of coastal upwelling dynamics, whereby increased upwelling only yields higher gray whale density if interspersed with relaxation events, likely because this combination optimizes influx and retention of nutrients to support recruitment and aggregation of gray whale prey. Several habitat features influence gray whale distribution, including substrate, shelf width, prominent capes, and river estuaries. However, the influence of these features differs between regions, revealing heterogeneity in habitat preferences throughout the PCFG foraging range. Predicted gray whale abundance fluctuated throughout our study period, but without clear directional trends, unlike previous abundance estimates based on mark-recapture models. This study highlights the value of long-term monitoring, shedding light on the impacts of variable environmental conditions on an iconic nearshore marine predator.

Spatial variation of guanaco (Lama guanicoe) densities influenced by natural and anthropogenic variables in Southern Andean Precordillera (Argentina)

ABSTRACT The spatial distribution of ungulate densities is determined by their decisions on habitat selection, modulated by environmental characteristics and human activities. Poaching and habitat degradation are threats to the guanaco, a native herbivore of arid environments of South America. Seasonal surveys of guanacos were carried out during two independent years in mountain environments of Andean Precordillera, inside a protected area and surroundings. Field surveys and GIS analyses estimated environmental variables. Density surface models estimated spatial distribution of guanacos, based on predictions about food availability, weather, risk perception, and human activities. The current distribution of densities is mainly influenced by the availability of preferred food and water, and protection effectiveness. Twelve years ago, disturbing human activities were also relevant. High densities in great altitudes yearlong, and a winter expansion through lower altitudes, are evidence of partial migrations, related to climatic events and food declines. Selective use of Puna grasslands and association with wetlands agree with food and risk predictions. Greater densities inside than outside the protected area, and decreasing guanaco–observer distances, are evidence of continued effective protection. Density surface modeling, applied to multi-year distance sampling, highlights as a useful tool for understanding the spatial dynamics of guanaco populations, and aiding management decisions.

Using density surface models to assess the ecological effectiveness of a protected area network in Tanzania

AbstractGiven recent global endeavors to increase protected area coverage, it is crucial to comprehensively evaluate the efficacy of various area‐based conservation strategies in effectively reducing biodiversity loss. Here, we investigated the responses of wildlife populations to different protection levels and environmental variables at the landscape scale in the Katavi–Rukwa Ecosystem, western Tanzania. To this end, we conducted line distance sampling surveys and counted the dung of six target mammal species (elephant, giraffe, buffalo, zebra, topi, and hartebeest) along foot transects within areas differing in protection levels (from strict to less‐strictly protected: national park, game reserve, forest reserve, game‐controlled area, and unprotected areas). Based on these dung counts, we modeled the spatial distribution of these six mammal species using a species‐specific density surface modeling framework. We found consistent effects of protection level and land use variables on the spatial distribution of the target mammal species: dung densities were highest in the national park and game reserves, intermediate in less‐strictly protected areas, and lowest in unprotected areas. Beyond species‐specific environmental predictors for dung densities, our results highlight consistent negative associations between dung densities of the target species and distance to cropland and avoidance of areas in proximity to houses. Our findings underpin differences in ecological effectiveness of protected areas within one ecosystem. Protection level and land use play crucial roles in moderating the spatial distribution of all considered mammal species. Our findings suggest that a landscape approach needs to guide effective conservation across the entire protection gradient of the Katavi–Rukwa Ecosystem.

North Atlantic right whale density surface model for the US Atlantic evaluated with passive acoustic monitoring

The Critically Endangered North Atlantic right whale Eubalaena glacialis entered a population decline around 2011. To save this species without closing the ocean to human activities requires detailed information about its intra-annual density patterns that can be used to assess and mitigate human-caused risks. Using 2.9 million km of visual line-transect survey effort from the US Atlantic and Canadian Maritimes conducted in 2003-2020 by 11 institutions, we modeled the absolute density (ind. km-2) of the species using spatial, temporal, and environmental covariates at a monthly time step. We accounted for detectability differences between survey platforms, teams, and conditions, and corrected all data for perception and availability biases, accounting for platform differences, whale dive behavior, group composition, and group size. We produced maps of predicted density and evaluated our results using independently collected passive acoustic monitoring (PAM) data. Densities correlated positively (r = 0.46, ρ = 0.58, τ = 0.46) with acoustic detection rates obtained at 492 stationary PAM recorders deployed across the study area (mean recorder duration = 138 d). This is the first study to quantify the concurrence of visual and acoustic observations of the species in US waters. We summarized predictions into mean monthly density and uncertainty maps for the 2003-2009 and 2010-2020 eras, based on the significant changes in the species’ spatial distribution that began around 2010. The results quantify the striking distribution shifts and provide effort- and bias-corrected density surfaces to inform risk assessments, estimations of take, and marine spatial planning.

Sea turtle density surface models along the United States Atlantic coast

Spatially explicit estimates of marine species distribution and abundance are required to quantify potential impacts from human activities such as military training and testing, fisheries interactions, and offshore energy development. There are 4 protected species of sea turtle (loggerhead, green, Kemp’s ridley, and leatherback) commonly found along the east coast of the USA, our study area, and which require impact assessments. Data from 7 different survey organizations were used to create density surface models for the 4 sea turtle species utilizing 1.2 million km of line-transect surveys. A substantial portion (29.7%) of available sightings were not identified to the species level. Not including these sightings would underestimate density, so a conditional random forest model was used to assign unidentified sightings to species. Higher densities of loggerhead, green, and Kemp’s ridley sea turtles were predicted south of the Outer Banks in cool months, transitioning northwards in late spring to occupy seasonal neritic habitats. The highest leatherback densities were predicted off the coasts of Georgia and Florida. Leatherbacks were also predicted throughout offshore areas. The predicted distribution patterns generally matched satellite tracking and strandings data, indicating the models reproduced established seasonal movements. Surveys rarely detect sea turtles smaller than 40 cm, so these age classes are not represented. The models are the first for the study area to apply availability bias estimates developed in or near the study area and attempt to classify unidentified sightings to the species level, providing an updated, critical tool for conservation management along the eastern seaboard.

Acoustic estimates of sperm whale abundance in the Mediterranean Sea as part of the ACCOBAMS Survey Initiative

Acoustic surveys for sperm whales (Physeter macrocephalus) were conducted in the Mediterranean Sea in summer 2018 as part of the vessel-based component of the ACCOBAMS Survey Initiative (ASI). Equal-spaced zigzag transects provided uniform coverage of key sperm whale habitats and were surveyed using a towed hydrophone array deployed from a research vessel at speeds of 5-8 knots. A total of 14,039 km of tracklines were surveyed in the western basin, Hellenic Trench and Libyan waters, with an acoustic coverage of 10% realised for sperm whales. During these surveys, 254 individual sperm whales were detected on the trackline, with an additional 66 individuals off-track. Sperm whales were only seen ten times on-track, with an additional 16 off-track sightings. Estimates of slant range to echolocating whales were used to derive density estimates through both design- and model-based distance sampling methodologies. An acoustic availability of 0.912 (sd = 0.036) was derived from via published models. When correcting for availability bias, a design-based abundance estimates of 2,673 individuals (95% CI 1,739-4,105; CV = 0.21) was derived for the surveyed blocks, which incorporated most known sperm whale habitat in the Mediterranean Sea. The equivalent model-based estimate was 2,825 whales (2,053-3,888; CV = 0.16). Over 97% of detected whales were in the western basin, with highest densities in the Algerian and Liguro-Provencal Basins between Algeria and Spain/France. In the eastern basin, detections were sparse and concentrated along the Hellenic Trench. A density surface modelling (DSM) exercise identified location and benthic aspect as being the most instructive covariates for predicting whale abundance. Distance sampling results were used in a power analysis to quantify the survey effort required to identify population trends. In the most extreme scenario modelled (10% per annum decline with decennial surveys), the population could have dropped by 90% before the decline was identified with high statistical power. Increasing the regularity of surveys would allow population trends to be detected more expediently. Mediterranean sperm whales are listed as Endangered on the IUCN’s Red List and the need for urgent conservation measures to reduce injury and mortality remains paramount for this unique sub-population.

Rapid population decline in McKay’s Bunting, an Alaskan endemic, highlights the species’ current status relative to international standards for vulnerable species

Abstract The McKay’s Bunting (Plectrophenax hyperboreus) is endemic to Alaska, breeds solely on the remote and uninhabited St. Matthew and Hall islands (332 km2) in the central Bering Sea, and is designated as a species of high conservation concern due to its small population size and restricted range. A previous hypothesized population estimate (~2,800 to 6,000 individuals) was greatly increased (~31,200 individuals) after systematic surveys of the species’ entire breeding range in 2003, establishing McKay’s Bunting as one of the rarest passerines in North America. In 2018, we replicated the 2003 surveys and used density surface models to estimate breeding season densities, distributions, and population change over the intervening time period. Our results indicate that the McKay’s Bunting population declined by 38% (95% CI: 27 to 48%) from ~31,560 to 19,481 individuals since 2003. Spatial model predictions showed no areas with an increase of birds on either St. Matthew or Hall islands but revealed declines across 13% (42 km2) of St. Matthew Island. Declines disproportionately occurred both in marginal habitats with reduced rocky nesting substrate and in high-density hotspots along the coast of St. Matthew Island. The total area occupied by breeding adults decreased by 8%, and high-density hotspots shifted inland from the coast of St. Matthew Island to higher elevations on both islands, the latter potentially responses to exceptionally warm weather and reduced spring snow cover in 2018. Additionally, we observed low numbers of predators and interspecific competitors in 2018, suggesting that these did not cause the decline. Our findings indicate that McKay’s Bunting meets international standards for elevating its conservation status from Least Concern to Endangered based on the International Union for Conservation of Nature Red List of Threatened Species ranking criteria. Additional population monitoring and studies to identify the causal mechanisms of the recent population decline of this rare species could assist future population assessments.

Planning from scratch: A new modelling approach for designing protected areas in remote, data‐poor regions

Abstract Human pressure on ecosystems has strongly increased over the last decades and now impacts even the most remote regions. To help mitigate these impacts, it is crucial to designate protected areas in regions that retain a high level of ecological integrity. However, ecological data remain scarce for many such areas, making the systematic design of new protected zones challenging. Following a request from local managers, we developed an original methodological approach to help design new zoning for a pre‐existing protected area in a remote, data‐poor Sahelian wetland of southern Chad, a vast area rich in biodiversity and exploited by diverse human activities. The method involved first collecting extensive aerial survey data (6252 records) on birds and mammals and then analysing this through a combination of distance sampling and density surface modelling. The biodiversity data, combined with ecological predictors, helped model species distribution layers that were then incorporated with socio‐economic constraints into the systematic conservation planning tool Marxan. This approach produced an array of protected zoning options that met three levels of conservation objectives set by experts, corresponding to proportions of individuals from given species to protect in the proposed protected area. Frequent exchanges with local managers allowed the analyses to be refined, resulting in seven potential scenarios to be considered for conservation purposes. Synthesis and applications. In a context of high data scarcity, lack of access and short‐term conservation objectives, this combined approach that optimizes newly obtained data via a suite of modelling tools can facilitate identifying and protecting natural areas in regions most in need of urgent conservation policy.

Acoustic density estimates of beaked whales off the mid-Atlantic coast of the USA in winter and spring

Increasing amounts of noise have been introduced into the marine environment by commercial, military and recreational activities over recent decades. Ziphiids (beaked whales in the Family Ziphiidae) are particularly sensitive to anthropogenic noise, which can lead to behavioural and physiological changes that may cause death in extreme cases. Despite these concerns, there are significant gaps in our knowledge of ziphiid distribution and density in areas exposed to noise. This study presents data from acoustic and visual vessel surveys conducted across the Outer Continental Shelf of North and South Carolina and southern Virginia in the USA (NOAA permits 14,809-03 and 16,473) with the aim of addressing data gaps for this region in spring and winter. Echolocation click trains were attributed to either Cuvier's (Ziphius cavirostris) or Gervais' (Mesoplodon europaeus) beaked whales based on peak frequency, 3 dB and 10 dB bandwidths, and inter-click interval. Estimates of click depth were used to correct estimates of perpendicular distance and improve detection functions used in Multiple Covariate Distance Sampling. Availability bias was quantified using tag data from other regions modified with local dive data. Swell height and sea surface temperature were found to affect the detection function and were therefore included in the final model. Incorporating cruise identity (winter vs. spring), candidate species (Cuvier's vs. Gervais' beaked whale) and/or cluster size did not improve model fit, suggesting there was no discernible seasonal effect, variation in detectability by species or increased probability of detection for larger groups. Design-based estimates of global beaked whale density (1.64 individuals per 100 km2: CI 0.88–3.03) and abundance (2963: CI 1597-5497) were then made incorporating a g(0) estimate of 0.43. These represent the first abundance estimates made for ziphiids using a towed hydrophone array off the USA's eastern seaboard. A Density Surface Model suggested slope and Sea Surface Temperature may influence ziphiid density in the region. This study provides seasonal data on deep diving beaked whales that can be used to inform management decisions regarding anthropogenic activities in this region.

Human–wildlife conflicts in Patagonia: ranchers’ perceptions of guanacoLama guanicoeabundance

AbstractConflicts between people and wildlife have become widespread as people move to areas previously home to wildlife and as wild populations recover. In Patagonia, one of the main threats to guanacoLama guanicoeconservation is the animosity of sheep ranchers towards the species. As key stakeholders in guanaco conservation we assessed ranchers’ perceptions regarding guanaco abundance in Isla Grande de Tierra del Fuego, Argentina. We contrasted these perceptions with estimated guanaco abundance and explored the socio-ecological factors influencing perceptions and how perceptions of overabundance are rooted in contextual factors rather than actual abundance. We performed semi-structured interviews with ranchers from Isla Grande and estimated guanaco abundance independently using density surface modelling. Ranchers were divided into three categories depending on their perception of guanaco abundance: ‘too many’, ‘many’ and ‘normal’. Those in the ‘many’ and ‘normal’ categories perceived guanaco abundance as being similar to actual abundance, whereas those in the category ‘too many' overestimated guanaco abundance. The perceived issues affecting livestock production varied between categories, although feral dogs emerged as the main problem. Negative perceptions of the guanaco stemmed from ranchers' beliefs that the species reduces forage availability for livestock, and from their disappointment about the government's handling of concerns regarding livestock production. Greater understanding and integration of the human dimension in conservation are needed to design more inclusive and resilient management plans.

Modelling density surfaces of intraspecific classes using camera trap distance sampling

AbstractSpatially explicit densities of wildlife are important for understanding environmental drivers of populations, and density surfaces of intraspecific classes allow exploration of links between demographic ratios and environmental conditions. Although spatially explicit densities and class densities are valuable, conventional design‐based estimators remain prevalent when using camera‐trapping methods for unmarked populations.We developed a density surface model that utilized camera trap distance sampling data within a hierarchical generalized additive modelling framework. We estimated density surfaces of intraspecific classes of a common ungulate, white‐tailed deerOdocoileus virginianus, across three large management regions in Indiana, United States. We then extended simple statistical theory to test for differences in two ratios of density.Deer density was influenced by landscape fragmentation, wetlands and anthropogenic development. We documented class‐specific responses of density to availability of concealment cover, and found strong evidence that increased recruitment of young was tied to increased resource availability from anthropogenic agricultural land use. The coefficients of variation of the total density estimates within the three regions we surveyed were 0.11, 0.10 and 0.06.Synthesis and applications. Our strategy extends camera trap distance sampling and enables managers to use camera traps to better understand spatial predictors of density. Our density estimates were more precise than previous estimates from camera trap distance sampling. Population managers can use our methods to detect finer spatiotemporal changes in density or ratios of intraspecific‐class densities. Such changes in density can be linked to land use, or to management regimes on habitat and harvest limits of game species.

Do-It-Yourself 5-Color 3D Printing of Molecular Orbitals and Electron Density Surfaces

This report outlines an approach for preparing 5-color 3D printed plastic models of molecular orbitals and electron density surfaces using a hobby-grade 3D printer. Instructions are provided for preparing 3D orbital and electron density surface (EDS) models using solid or mesh representations in ground state and transition state structures. We show that the information content of 3D orbital and surface models can be enhanced with text annotation, bisection, strut and dashed bond placement, and composite orbital-EDS model constructions. Example prints illustrate orbital concepts in organic and inorganic chemistry, such as the ethyl cation (σ–p hyperconjugation), methane (hybridization and C–H bonding), ethane (σ–σ* hyperconjugation in the staggered and eclipsed conformations), 2-hydroxytetrahydropyran (the anomeric effect/n−σ* hyperconjugation), the water dimer (hydrogen bonding/n−σ* overlap), ethylene, 1,3-butadiene, and benzene (π molecular orbitals), Re2Cl82–, and U2(COT)2 (metal–metal quadruple bonds). Transition state models illustrate orbital interactions in the SN2 reaction of cyanide with methyl, ethyl, and isopropyl chloride and in a hydroboration reaction of BH3 with propene. Composite EDS models of methyl and isopropyl chloride (for exploring their relative reactivities as SN2 electrophiles) and methylcyclohexane (visualizing 1,3-diaxial interactions) are described. Student perceptions of a multicolor 3D orbital print used in an introductory organic chemistry laboratory course are reported.

Spatial density patterns of herbivore response to seasonal dynamics in the tropical deciduous forest of central India

AbstractResource dynamism in seasonal forests leads ungulates to differential habitat preference; hence, their distribution aligns with environmental covariates across spatial and temporal scales. Seasonal patterns of four species of ungulates, namely sambar, chital, nilgai, and wild pig, were investigated and identified as the environmental variables driving the density gradient across two seasons, summer and winter, in the tropical dry deciduous forest of Panna Tiger Reserve, central India. Distance sampling data were analyzed using density surface modeling for ungulates with a survey effort of 518 km in winter and 356 km in summer in a generalized additive modeling framework. We found that season significantly affected the spatial densities of all ungulates, with sambar, chital, and nilgai congregating in summer and wild pig in winter. All ungulates showed a clear seasonal shift to the valley in summer and preferred plateaus in winter. The spatially explicit map outputs draw attention to the seasonal hot spots for ungulates abundance and the species and season‐specific roles of environment variables in defining their distribution. These results provide a scientific basis for direct conservation efforts to the spatially prioritized habitats for cost‐effective management interventions.

Updated marine mammal distribution and abundance estimates in British Columbia

Information relating to the distribution and abundance of species is critical for effective conservation and management. For many species, including cetacean species of conservation concern, abundance estimates are lacking, out of date and/or highly uncertain. Systematic, line-transect marine mammal surveys were conducted in British Columbia’s (BC) coastal waters over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007). In total, 10,057km of transects were surveyed in an 83,547km2 study area. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. The summer abundance estimates (with lower and upper 95% confidence intervals; all DSM method unless otherwise stated), assuming certain trackline detection (underestimates true population size) were: harbour porpoise (Phocoena phocoena) 8,091 (4,885–13,401); Dall’s porpoise (Phocoenoides dalli) 5,303 (4,638–6,064); Pacific white-sided dolphin (Lagenorhynchus obliquidens) 22,160 (16,522–29,721); humpback whale (Megaptera novaeangliae) 1,092 (993–1,200); fin whale (Balaenoptera physalus) 329 (274–395); killer whale (all ecotypes; Orcinus orca), 371 (222–621); common minke whale (B. acutorostrata) 522 (295–927); harbour seal (total; Phoca vitulina) 24,916 (19,666–31,569); Steller sea lion (total; Eumetopias jubatus) 4,037 (1,100–14,815); and northern elephant seal (CDS method; Mirounga angustirostris) 65 (35–121). Abundance estimates are provided on a stratum-specific basis with additional estimates provided for Steller sea lions and harbour seals that were ‘hauled out’ and ‘in water’. This analysis updates previous estimates by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Aerial abundance estimates for two sympatric dolphin species at a regional scale using distance sampling and density surface modeling

Monitoring wildlife populations over scales relevant to management is critical to supporting conservation decision-making in the face of data deficiency, particularly for rare species occurring across large geographic ranges. The Pilbara region of Western Australia is home to two sympatric and morphologically similar species of coastal dolphins—the Indo-pacific bottlenose dolphin (Tursiops aduncus) and Australian humpback dolphin (Sousa sahulensis)—both of which are believed to be declining in numbers and facing increasing pressures from the combined impacts of environmental change and extensive industrial activities. The aim of this study was to develop spatially explicit models of bottlenose and humpback dolphin abundance in Pilbara waters that could inform decisions about coastal development at a regional scale. Aerial line transect surveys were flown from a fixed-wing aircraft in the austral winters of 2015, 2016, and 2017 across a total area of 33,420 km2. Spatio-temporal patterns in dolphin density were quantified using a density surface modeling (DSM) approach, accounting for imperfect detection as well as both perception and availability bias. We estimated the abundance of bottlenose dolphins at 3,713 (95% CI = 2,679–5,146; average density of 0.189 ± 0.046 SD individuals per km2) in 2015, 2,638 (95% CI = 1,670–4,168; 0.159 ± 0.135 individuals per km2) in 2016 and 1,635 (95% CI = 1,031–2,593; 0.101 ± 0.103 individuals per km2) in 2017. Too few humpback dolphins were detected in 2015 to model abundance, but their estimated abundance was 1,546 (95% CI = 942–2,537; 0.097 ± 0.03 individuals per km2) and 2,690 (95% CI = 1,792–4,038; 0.169 ± 0.064 individuals per km2) in 2016 and 2017, respectively. Dolphin densities were greatest in nearshore waters, with hotspots in Exmouth Gulf, the Dampier Archipelago, and Great Sandy Islands. Our results provide a benchmark on which future risk assessments can be based to better understand the overlap between pressures and important dolphin habitats in tropical northwestern Australia.

Pampas fox spatial and temporal variation in Argentinean agroecosystems

Context Agricultural activities have reduced wildlife natural habitats and increased the spatial overlap between animals’ distribution and human activities. However, carnivores with a broad diet and flexible habitat requirements can tolerate human-induced environmental changes. Thus, identifying changes in their densities and spatial distribution are important factors to take into consideration when working towards minimising human–carnivore conflict. Aims Our aim was to identify the main environmental and human variables influencing Pampas fox density and to produce density maps in the reproductive and non-reproductive seasons. Methods We performed spotlight counts at night, following the line transect method in the non-reproductive and reproductive seasons during two consecutive years. We also obtained landscape, human-impact and environmental spatial variables using remote sensing data and Geographic Information Systems. We modelled and mapped the Pampas fox’s spatial density using Density Surface Models. Key results We found that disturbance by human activities and landscape configuration influenced the spatial variation of the Pampas fox density across time and space. We registered a positive association between the number of foxes and the proximity to urban areas and paved roads, and we also found higher densities near grasslands areas and less modified habitats varying with the season and year. A higher density of foxes was observed in the non-reproductive season compared with the reproductive season. Conclusions and Implications This study provides insight on the variation in Pampas fox densities across agroecosystems. It highlights the relevance of more naturalised and protected habitats to sustain the Pampas fox population in highly fragmented landscapes, but also shows a positive association with disturbed areas. The spatial information developed in this study is useful to identify areas where ecosystem services could be encouraged, helping to maintain the ecosystems’ equilibrium and biodiversity conservation, and develop new management programs creating human–wildlife coexistence.

Density surface and excursion sets modeling as an approach to estimating population densities

AbstractEffective species management and conservation require knowledge of species distribution and status. We used point‐transect distance sampling surveys of the endangered palila (Loxioides bailleui), a honeycreeper currently found only on the Island of Hawai'i, USA, to generate robust estimates of total abundance and simultaneously model the distribution, abundance, and spatial correlation of the species as a density surface model (DSM). Point‐transect distance sampling is a widely applied method to estimate bird densities accounting for imperfect detection probability. For the DSM we used a generalized additive model framework and soap film smoothers to control the effects of boundary features. This modeling approach allowed us to account for imperfect detection and propagate detection probability uncertainty. We compared the uncertainty in palila abundance estimates using standard point‐transect distance sampling to estimates from the DSM. The DSM, accounting for both distance‐sampling‐derived detection probability variance and the generalized additive model density estimate variance, did not improve population estimator precision; however, it provided insight into the species' distribution, density, and uncertainty. We also applied excursion sets analysis to objectively identify areas where the species occurs in high densities. The 2017 global population of &lt;2,000 individuals was limited to an excursion area of 1,500 ha. Our findings can help management and regulatory agencies by simultaneously mapping a species' distribution and density, improving survey protocols, and providing information important to species conservation.

Spatio-temporal changes in chimpanzee density and abundance in the Greater Mahale Ecosystem, Tanzania.

Species conservation and management require reliable information about animal distribution and population size. Better management actions within a species' range can be achieved by identifying the location and timing of population changes. In the Greater Mahale Ecosystem (GME), western Tanzania, deforestation due to the expansion of human settlements and agriculture, annual burning, and logging are known threats to wildlife. For one of the most charismatic species, the endangered eastern chimpanzee (Pan troglodytes schweinfurthii), approximately 75% of the individuals are distributed outside national park boundaries, requiring monitoring and protection efforts over a vast landscape of various protection statuses. These efforts are especially challenging when we lack data on trends in density and population size. To predict spatio-temporal chimpanzee density and abundance across the GME, we used density surface modeling, fitting a generalized additive model to a 10-year time-series data set of nest counts based on line-transect surveys. The chimpanzee population declined at an annual rate of 2.41%, including declines of 1.72% in riparian forests (from this point forward, forests), 2.05% in miombo woodlands (from this point forward, woodlands) and 3.45% in nonforests. These population declines were accompanied by ecosystem-wide declines in vegetation types of 1.36% and 0.32% per year for forests and woodlands, respectively; we estimated an annual increase of 1.35% for nonforests. Our model predicted the highest chimpanzee density in forests (0.86 chimpanzees/km2 , 95% confidence intervals (CIs) 0.60-1.23; as of 2020), followed by woodlands (0.19, 95% CI 0.12-0.30) and nonforests (0.18, 95% CI 0.10-1.33). Although forests represent only 6% of the landscape, they support nearly one-quarter of the chimpanzee population (769 chimpanzees, 95% CI 536-1103). Woodlands dominate the landscape (71%) and therefore support more than a half of the chimpanzee population (2294; 95% CI 1420-3707). The remaining quarter of the landscape is represented by nonforests and supports another quarter of the chimpanzee population (750; 95% CI 408-1381). Given the pressures on the remaining suitable habitat in Tanzania, and the need of chimpanzees to access both forest and woodland vegetation to survive, we urge future management actions to increase resources and expand the efforts to protect critical forest and woodland habitat and promote strategies and policies that more effectively prevent irreversible losses. We suggest that regular monitoring programs implement a systematic random design to effectively inform and allocate conservation actions and facilitate interannual comparisons for trend monitoring, measuring conservation success, and guiding adaptive management.

A model-based estimate of winter distribution and abundance of white-tailed deer in the Adirondack Park.

In the Adirondack Park region of northern New York, USA, white-tailed deer (Odocoileus virginianus) and moose (Alces alces) co-occur along a temperate-boreal forest ecotone. In this region, moose exist as a small and vulnerable low-density population and over-browsing by white-tailed deer is known to reduce regeneration, sustainability, and health of forests. Here, we assess the distribution and abundance of white-tailed deer at a broad spatial scale relevant for deer and moose management in northern New York. We used density surface modeling (DSM) under a conventional distance sampling framework, tied to a winter aerial survey, to create a spatially explicit estimate of white-tailed deer abundance and density across a vast, northern forest region. We estimated 16,352 white-tailed deer (95% CI 11,762–22,734) throughout the Adirondack Park with local density ranging between 0.00–5.73 deer/km2. Most of the Adirondack Park (91.2%) supported white-tailed deer densities of ≤2 individuals/km2. White-tailed deer density increased with increasing proximity to anthropogenic land cover such as timber cuts, roads, and agriculture and decreased in areas with increasing elevation and days with snow cover. We conclude that climate change will be more favorable for white-tailed deer than for moose because milder winters and increased growing seasons will likely have a pronounced influence on deer abundance and distribution across the Adirondack Park. Therefore, identifying specific environmental conditions facilitating the expansion of white-tailed deer into areas with low-density moose populations can assist managers in anticipating potential changes in ungulate distribution and abundance and to develop appropriate management actions to mitigate negative consequences such as disease spread and increased competition for limiting resources.