Population Density Estimates Research Articles

Monitoring GPS‐collared moose by ground versus drone approaches: efficiency and disturbance effects

Efficient wildlife management requires precise monitoring methods, for example to estimate population density, reproductive success, and survival. Here, we compared the efficiency of drone (equipped with a RGB camera) and ground approaches to detect and observe GPS‐collared female moose Alces alces and their calves. We also quantified how drone (n = 42) and ground (n = 41) approaches affected moose behavior and space use (n = 24 individuals). The average time used for drone approaches was 17 min compared to 97 min for ground approaches, with drone detection probability being higher (95% of adult female moose and 88% of moose calves) compared to ground approaches (78% of adult females and 82% of calves). Drone detection success increased at lower drone altitudes (50–70 m). Adult female moose left the site in 35% of drone approaches (with > 40% of those moose becoming disturbed once the drone hovered < 50 m above ground) compared to 56% of ground approaches. We failed to find short‐term effects (3 h after approaches) of drone approaches on moose space use, but moose moved > fourfold greater distances and used larger areas after ground approaches (compared to before the approaches had started). Similarly, longer‐term (24 h before and after approaches) space use did not differ between drone approaches compared to days without known disturbance, but moose moved comparatively greater distances during days of ground approaches. In conclusion, we could show that drone approaches were highly efficient to detect adult moose and their calves in the boreal forest, being faster and less disturbing than ground approaches, making them a useful tool to monitor and study wildlife.

Wolverine population density and home range size in Arctic Alaska

AbstractUnderstanding the spatial requirements of exploited wildlife species, including population density and home range size, is important for wildlife management and conservation. Wolverines (Gulo gulo) are hunted and trapped across the Arctic, and are vulnerable to numerous, often interrelated, threats resulting from anthropogenic changes in their environment. Previous population density estimates for wolverines in the Arctic range tenfold, from the lowest to highest available for the species, limiting their utility outside the specific areas and times they were derived. The most recent density estimate in Arctic Alaska, USA, was produced 4 decades ago and was derived from a relatively small study area. We evaluated wolverine population density and home range size across the North Slope of Alaska during 2017–2022 using global positioning system (GPS)‐based collar data and spatial capture‐recapture models. Population density estimates were 2.0 individuals/1,000 km2 (95% credible interval = 1.3–3.5) in 2018 and 2.8 individuals/1,000 km2 (95% credible interval = 1.7–3.5) in 2021. Median home range sizes modeled with autocorrelated kernel density estimators and Ornstein‐Uhlenbeck foraging movement processes were 699 km2 (range = 158–2,895 km2) among 12 females and 2,332 km2 (range = 797–4,699 km2) among 10 males. These population density estimates are nearly 10 times lower than the previous estimate for Arctic Alaska. We recommend incorporating this information into management strategies to ensure sustainable harvest, particularly as the region's remote areas are more efficiently accessed by hunters and are being considered for transportation corridors supporting new industrial development.

Status assessment of a recently reintroduced eurasian lynx (Lynx lynx) population in the Palatinate Forest, South-West Germany

To reinforce Eurasian lynx populations in central Europe, 20 lynx from Slovakia and Switzerland were translocated to the Palatinate Forest between 2016 and 2020. Using a systematic camera trapping array consisting of 80 camera trapping sites in a 1,000 km² study area located in the centre of the approximately 1,800 km² Palatinate Forest, we aim to describe the status of the population in the final stages of the reintroduction project in winter and spring 2019/20 and 2020/21. We also use our data to provide a first estimate of population density of the newly established population. With an estimate of 0.52 independent individuals per 100 km², population density in the Palatinate Forest was still significantly lower than the densities of well-established reintroduced populations. The number of independent individuals detected in the study area decreased from 15 individuals in 2019/20 to 11 individuals in 2020/21, thus significantly below the number of lynx translocated. The low abundance in the Palatinate Forest can be explained by the dispersal of several individuals to the Vosges (France), which, together with the Palatinate Forest, form a continuous area of suitable lynx habitat of approximately 8,000 km². Our results may thus reflect the status of a young population that can expand over a potentially large area. Nevertheless, in light of the low population density, we strongly recommend a synchronized and harmonized transboundary monitoring program to keep track of the development of this important Franco-German lynx population. In case population density remains low, supportive measures need to be considered.

Applying a Random Encounter Model to Estimate the Asiatic Black Bear (Ursus thibetanus) Density from Camera Traps in the Hindu Raj Mountains, Pakistan.

Estimating the population density of vulnerable species, such as the elusive and nocturnal Asiatic black bear (Ursus thibetanus), is essential for wildlife conservation and management. We used camera traps and a Random Encounter Model (REM) to estimate the population density of U. thibetanus during the autumn and winter seasons in the Hindu Raj Mountains. We installed 23 camera traps from October to December 2020 and acquired 66 independent pictures of Asiatic black bears over 428 trap nights. Our results showed that the bears preferred lowland areas with the presence of Quercus spp. We estimated, using the REM, a population density of U. thibetanus of 1.875 (standard error = 0.185) per square kilometer, which is significantly higher than that in other habitats. Our results showed that during autumn and winter, the bear population density tends to concentrate at lower elevations. Forest cover showed a positive correlation with the rates of bear encounters unlike the Euclidean distance to human settlements, altitude, and aspect variables. The approaches used here are cost-effective for estimating the population density of rare and vulnerable species such as U. thibetanus, and can be used to estimate their population density in Pakistan. Population density estimation can identify areas where the bears live and human-bear conflicts occurred and use this information in future wildlife management plans.

Extracting building outlines based on convolutional neural networks using the property of linear connectivity

Abstract. For years, researchers have been developing an automated method that can replace humans by drawing the outlines of individual buildings in a vector format, which plays an important role in GIS creation, environmental monitoring, urban planning, population density estimation, and energy supply. There is no doubt that this is an extremely difficult task, not only because of the labor required to develop such a highly intelligent algorithm, but also because of the challenges posed by imperfect imaging conditions, different building structures, and the complexity of the background. One of the current challenges in extracting building outlines is to accurately recreate the polygonal boundaries of the building while extracting vectorized building masks as output for direct use in various applications. This work provides a comprehensive workflow for building extraction and improves the predicted area of buildings through boundary regularization. First, a convolutional neural network is used to train instance segmentation model, then regularization and vectorization processes are performed. The main difference from existing methods is a new regularization method based on the concepts of linear connectivity and convexity of a set of points. This approach can effectively identify and remove points that do not belong to the detected building but were incorrectly segmented by the algorithm. Based on the results of experiments, the algorithm showed a high level of efficiency, comparable to leading methods for extracting building boundaries as PolyWorld.

A conservation assessment of birds in the Karoo region of South Africa: densities, populations, ranges, and trend estimates

The Karoo region of South Africa, which includes the Succulent and Nama Karoo biomes, supports a unique avian fauna, with ten bird species occurring exclusively in this arid-zone region and many others exhibiting a strong preference for this habitat. To better determine the conservation status of these birds, we conducted point counts to estimate population densities of bird species occurring in the South African Karoo region in 2017 and 2018. We also used data of the South African Bird Atlas Projects (SABAP2) to estimate the species’ ranges and to determine population trends. Although the population densities are naturally low for most species, their ranges are very large, and reporting-rate trends appear stable for most species. Our analysis reveals that none of the Karoo bird species are currently of serious conservation concern. However, the Red Lark Calendulauda burra and Sclater’s Lark Spizocorys sclateri should be considered regionally Near Threatened as they are habitat specialists with inferred declining populations and are not currently protected within any designated conservation areas. Given the rapid transformation of landscapes linked to mining and alternative energy developments currently underway in the Karoo, combined with the poor representation of bird species in protected areas, it is imperative that special attention be paid to the conservation of bird species endemic to the Karoo, and that appropriate mitigation measures be taken by developers.

Population Abundance and Density Estimates of Poorly Documented Near-Threatened Calabar Angwantibo (Arctocebus calabarensis) in Oban Hills Region.

Population abundance and density estimates play important roles in biodiversity conservation assessment and can lead to prioritization of conservation efforts, strategies, and management. The Calabar angwantibo (Arctocebus calabarensis) is a poorly studied, Near-Threatened nocturnal, arboreal mammal species occurring only in the lowland moist tropical rainforest blocks of southeastern Nigeria and southwestern Cameroon. Like other arboreal nocturnal mammals, there are gaps in knowledge of the distribution and abundance of this species, which may be facing population declines due to habitat loss and hunting. In this study, we investigated the abundance and density of A. calabarensis in the Oban Hills Region of Nigeria. We conducted systematic distance sampling survey along 32 transects in different habitats in a 1227 km of survey efforts. A total of 41 sightings of A. calabarensis were detected, resulting in an abundance of 7345 individuals (95% CI = 1.51-4.37) with an estimated density of 2.57 animals/km2. The estimated population abundance is 6515 individuals in closed-canopy forests and 830 individuals in secondary forests, with encounter rates of 0.52 individual/km2 and 0.60 individuals/km2 in the closed canopy and secondary forest habitats. The global estimates encounter rate of A. calabarensis across the habitat types is 0.33 individuals/km2 and population abundance of 4456 individuals. Our findings indicate that the A. calabarensis populations can adapt to low changes in forest habitat modifications resulting from increasing and widespread forest disturbance by human-dominated activity, which is giving way to forest clearance for agriculture cultivation and infrastructural development. Our findings help to fill a knowledge gap regarding this species and may help establish a baseline for future management, population monitoring, and conservation of the cryptic population of A. calabarensis in Cross-Sanaga Forests.

On an Aggregated Estimate for Human Mobility Regularities through Movement Trends and Population Density.

This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic.

Dynamic analysis of a fuzzy Bobwhite quail population model under g-division law

This paper is concerned with a kind of Bobwhite quail population model xn+1=A+Bxn+xnxn-1xn-2,n=0,1,⋯,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\begin{aligned} x_{n+1}=A+Bx_n+\\frac{x_n}{x_{n-1}x_{n-2}},\\ \\ n=0,1,\\cdots , \\end{aligned}$$\\end{document}where the parameters and initial values are positive parabolic fuzzy numbers. According to g-division of fuzzy sets and based on the symmetrical parabolic fuzzy numbers, the conditional stability of this model is proved. Besides the existence, boundedness and persistence of its unique positive fuzzy solution. When some fuzzy stability conditions are satisfied, the model evolution exhibits oscillations with return to a fixed fuzzy equilibrium no matter what the initial value is. This phenomena provided a vivid counterexample to Allee effect in density-dependent populations of organisms. As a supplement, two numerical examples with data-table are interspersed to illustrate the effectiveness. Our findings have been verified precise with collected northern bobwhite data in Texas, and will help to form some efficient density estimates for wildlife populations of universal applications.

Population of The Javan Surili Langur (Presbytis Comata) in The Taman Safari Indonesia Bogor Forest Area

Taman Safari Indonesia Bogor is a buffer zone for the Taman Nasional Gunung Gede Pangrango conservation forest area and is one of the habitats for the Javan surili langurs, but there is no research data on wild Javan surili langur populations. The object of research is to find out how many populations of Javan surili langurs are in the TSI Bogor forest area. The research method used the line transect method by collecting data on the number of individuals, the number of groups, the sex ratio, and the age structure. The research was conducted in four observation areas with varying lengths, observations were made at (06.00 - 17.00 WIB), and four repetitions were carried out on each observation path, the results showed that there were 16 Javan surili langurs individuals divided into one group, and the estimated population density was 0.06 individual/ha. The sex diversity of male and female surili langurs in the TSI Bogor forest area is 1:6 where the female Javan surili langurs are more than the male Javan surili langurs and for the age structure the largest Javan surili langurs are in the adult age class with a percentage of 43.75%, juvenile 31.25%, and the percentage of infant is 25%.

Faecal Standing Crop with real time correction using scat detection dogs to estimate population density

Abstract Population density is fundamental information for assessing the conservation status of species and support management and conservation actions for in situ populations, but is unknown for many forest species due to their difficulty in detection. The Faecal Standing Crop (FSC) method using detection dogs is an alternative for cryptic or elusive species. An intrinsic difficulty of FSC is the ability to find faecal samples in the field and to estimate the probability of which faeces detection is influenced by degradation due to climatic conditions. Our goal was to propose a concurrent FSC parameter estimation using a scat detection dog under different climatic conditions and apply those parameters in a wild deer population. Ten faecal samples of grey brocket deer (Subulo gouazoubira) were placed weekly in a transect (24 × 1440 m) in both dry and wet seasons (12 weeks each). A scat detection dog was then employed to find experimental faecal samples to determine the FSC parameters that were subsequently used with naturally occurring faecal samples (also dog‐detected) to estimate population density. The oldest dog found samples were 21 (Dry) and seven (Wet) days after placement, resulting in dog efficiency of 22.5% (Dry) and 30% (Wet). Adjusting the model to account for efficiency and scat durability, we estimated similar, seasonal, densities of 4.51 individuals km−2 (SD = 2.21, Dry) and 5.37 individuals km−2 (SD = 3.71, Wet). Synthesis and applications: Our results demonstrate that our concurrent methodology corrected the effects of weather and habitat on FSC parameters thereby allowing for accurate population density estimation. Additionally, this method can provide reasonably precise density estimates with a logistically feasible sample size, as demonstrated by simulation. Following our recommendations, this method allows a reliable estimate of population density because it incorporates any influence of study area, dog ability and climate in faecal sample detection, providing fundamental information for the conservation of many cryptic and elusive species.

Evaluating the representativeness of mobile big data: A comparative analysis between China's mobile big data and census data at the county level

Mobile big data has emerged as an essential tool for various scientific research fields. However, the credibility of mobile big data and the extent to which it can represent the real-world population remain unclear. This study evaluated the representativeness of mobile big data by comparing it to the most recent census data at the county level in China. Using power-law and multiple linear regression models, we aim to determine the accuracy and reliability of mobile big data in reflecting the population dynamics and characteristics of different geographical areas. Our results indicate that disparities among individuals with different socioeconomic statuses, demographic characteristics, or geographic locations may contribute to biased estimations of the actual population density. Higher illiteracy rates and median ages may be associated with underestimating population density. In contrast, higher GDP per capita, elevated urbanization levels, and larger percentages of the 15–64 year age group may be associated with overestimating population density. Our research highlights the importance of cross-validating population estimates and offering practical statistical methods for addressing potential biases and estimating population dynamics in future applications of mobile big data.

Estimating groundwater geogenic arsenic contamination and the affected population of river basins underlain mostly with crystalline rocks in Ghana

Arsenic is a human carcinogen and contributes to the incidences of cancer, diabetes, and skin diseases in the exposed populations. Therefore, its occurrence in drinking water is of public health concern worldwide, especially in the Tano, Pra, and Ankobra River Basins in Ghana. The metasediments and metavolcanic formations which underlie these basins (42,092.5 km2) host arsenic sulphide minerals that are a source of arsenic contamination of the weathered and fractured aquifers that serve as drinking water supply to most of the population (∼9.8 million), especially in the rural areas. A random forest machine learning method and partial dependence plots were applied to maps of spatially continuous environmental factors (fault density, surface bulk density, coarse fragment and soil pH; and sub-surface silt and soil pH) and hydrochemical variables, respectively, and arsenic measurements from wells (n = 229) which included 57 new datasets of which 7.86 % exceeded the 10 µg/L to develop arsenic prediction models for the basins at thresholds of 1 µg/L, 5 µg/L, and 10 µg/L. Fault density and coarse fragments were more reliable contributors to the models. A partial dependence plot and Spearman's rank correlation analysis showed a significant positive correlation (p < 0.01) between arsenic enrichment and HCO3−, pH, Fe, and Mn, except NO3− in groundwater. Arsenic hotspots occurred in urban districts in the Ashanti Region and known gold-mining areas in Nzema, Obuasi, Prestea, and Tarkwa. Spatially, arsenic contamination in groundwater covered 49.44 % of the land area of the basins. By cross-referencing population density estimates and the arsenic hazard map,15.8 % of the population is exposed to arsenic-contaminated groundwater in the basins. The hazard model will facilitate efforts to reduce rural poverty and protect public health by delivering potable water in Ghana. The hazard models apply to crystalline terrain in other sub-Saharan African countries.

Marine soundscape monitoring from underwater autonomous vehicles—Passive acoustic monitoring gliders

Ocean gliders are buoyancy-driven autonomous underwater platforms, able to collect oceanographic measurements along vertical profiles during multi-months missions, covering thousands of kilometers. They glide quietly through the water column without propulsion noise and are therefore extremely suitable for Passive Acoustic Monitoring (PAM) of the marine environment. From PAM glider data in the Mediterranean Sea and the Southern Ocean, we illustrate the current and potential uses of PAM gliders for the study of physical oceanography, biology, ecology and for regulatory purposes. We evaluate limiting factors for PAM glider survey, such as platform-generated and flow noise, instrument size and power constraints, profiling ability and movement of the platform. We provide recommendations and good practices for typical PAM glider surveys and present future developments identified by the PAM glider community to further develop the readiness level and societal impact of PAM glider observation: (1) Calibration of the PAM glider to collect absolute sound levels; (2) adapted sampling methods and statistical analysis techniques to perform population density estimation; and (3) Integration of PAM glider observation to existing monitoring programs.

Compiling Granular Population Data Using Geospatial Information

Detailed data on the distribution of human populations are valuable inputs to research and decision making. This study aims at compiling data on population density that are more granular than government-published estimates and assessing different methods and model specifications. As a first step, we combine government-published data with publicly available data like land cover classes, elevation, slope, and nighttime lights, and then apply a random forest approach to estimate population density in the Philippines and Thailand at the 100 meter (m) by 100[Formula: see text]m level. Second, we use different specifications of random forest and Bayesian model averaging (BMA) techniques to forecast grid-level population density and evaluate their predictive power. The use of a random forest model showed that reasonable forecasts of grid-level population growth rates are achievable. The results of this study contribute to the assessment of methods like random forest and BMA in forecasting population distributions.

Motion‐sensitive cameras track population abundance changes in a boreal mammal community in southwestern Yukon, Canada

AbstractMotion‐sensitive cameras are commonly used to monitor wildlife occupancy rates; however, few studies have assessed whether data from cameras are correlated with density estimates obtained from more traditional labor‐intensive methods such as those based on capture‐mark‐recapture. We used data from a boreal forest community to test whether camera data were correlated with densities estimated from independent monitoring methods. We placed 72 covert cameras in the forest around Lhù'ààn Mân' (Kluane Lake), Yukon, Canada, for 7 years and tracked changes in population densities by camera hit rates. We independently estimated population densities of snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus) using capture‐mark‐recapture via live trapping, and Canada lynx (Lynx canadensis), coyotes (Canis latrans), and moose (Alces americanus) by snow track transects. Density estimates obtained from conventional aerial surveys were also periodically available for moose. Except for red squirrels, camera hit rates were highly correlated with population density estimates obtained by traditional methods, including across a large range of estimated densities corresponding to cyclic population dynamics in several species. Accordingly, we infer that motion‐sensitive cameras could supplement or replace traditional methods for monitoring key species in boreal forest food webs. Using cameras to monitor population change has several advantages; they require less effort in the field, are non‐invasive compared to live‐trapping, include multiple species at the same time, and rely less on weather than either aerial surveys or snow track transects. Tracking changes across the vast boreal forest is becoming increasingly necessary because of climate and landscape change and our data validate the use of motion‐sensitive cameras to provide a useful quantitative method for state‐of‐the‐environment reporting.

Is a Māori contact‐era population of 100,000 too low? Evidence from population density analogues

AbstractThis research considers the current New Zealand conventional wisdom of a Māori contact‐era population of 100,000 circa‐1770 using a variety of population density analogues. The first set of analogues examines estimated population densities of six districts in early‐contact period New Zealand for which reasonable population estimates can be constructed using methods of historical demography. The second set examines estimated population densities of pre‐industrial societies on large, relatively isolated temperate islands outside of New Zealand. The density research indicates that a contact‐era Māori population in excess of 200,000 is a distinct possibility. Based on this density analysis the current conventional wisdom's figure of 100,000 appears to be—considerably—on the low side, and suggesting considerable catastrophic early post‐contact population decline.

Calling for the future of conservation: a protocol for passive acoustic monitoring of small arboreal primates

Biodiversity conservation faces challenges due to a lack of accurate information on species occurrence. Various techniques have been used to survey species diversity and estimate population density, but monitoring species over large spatial and temporal scales remains challenging. Passive acoustic monitoring (PAM) has emerged as a cost-effective and non-invasive method for monitoring biodiversity. PAM utilizes autonomous recording units (ARUs) installed in different areas and is particularly relevant for monitoring threatened species in tropical forest regions. In the case of non-human primates, PAM has proven effective in detecting endangered species, monitoring populations, studying vocal behavior, and evaluating territory use. The black lion tamarin (Leontopithecus chrysopygus), an endangered species of the Atlantic Forest, relies on acoustic signals for communication. This study proposes a PAM protocol for monitoring arboreal primates using the black lion tamarin as a model. It reviews PAM's use in primate research and emphasizes defining target vocalizations. We recommend optimal recording conditions, including distance, height, and equipment. Recordings should be positioned high above the ground, considering the arboreal nature of primates. The choice of spatial distribution, including random placement, transects, and grids, depends on the research question and objectives. Lastly, the study addresses the recording schedule, considering periods of greater species activity, such as from sunrise to sunset. In summary, this study highlights PAM's potential for monitoring arboreal primates providing recommendations for vocalizations, recording conditions, equipment, spatial distribution, and schedules, contributing to effective monitoring, and supporting conservation efforts in tropical forests.

Economics and the dreamtime revisited: Creating a truly Australian economic history?

AbstractThe Economics and the Dreamtime was a landmark in Australian Economic History where Noel Butlin elevated awareness of the central importance of Indigenous economic history. It was a sprawling inter‐disciplinary work that used economic tools to understand Indigenous society before first contact and in the early colonial period. This article revisits that book to provide a critical evaluation of the major contributions of Butlin's research on Indigenous Australians. His primary contribution was to make Indigenous people more visible in the Australian economy in the early colonial period. He created a unique backcasting methodology that allowed Indigenous population to be estimated in the first six decades of the colony based on depopulation from disease, resource loss and frontier violence. I argue that the two main shortcomings of Butlin's research is that his method used colonial estimates of the population and that the population estimates are not sufficiently geographically differentiated. The main criticism of Butlin's research in the literature is that it is too speculative. However, his methodological innovation allows considerable transparency in the assumptions used and can create a range of plausible estimates that give us a sense of the unreliability of the existing population estimates. Alternative methodologies based on estimating population densities in 1788 from anthropological evidence are historically point estimates, which do not provide a sense of how uncertain the estimates might be. The way forward for this debate is to combine Butlin's demographic backcast methodology with population density estimates that take into account the selective mortality from disease and frontier violence. Finally, in order to create a truly Australian Economic History, it is necessary to also augment the methodology to incorporate Indigenous perspectives into the analysis and to utilise a local geography that acknowledges the diversity of Indigenous Australia.

Biogeographic analysis of population density of white-tailed deer in Mexico: Importance of the Protected Natural Areas and Wildlife Management Units

The white-tailed deer Odocoileus virginianus is the wildlife species with the greatest geographic distribution and economic importance in Mexico. This article presents a biogeographic analysis of the population density of this deer species by federal states, vegetation types, biogeographic provinces, and field methods, based on 200 selected studies. Estimates are highly variable and potentially biased due to the different field designs and statistical analyses. The national average density was estimated at 6.9 deer/km2 (SD = 5.1); specifically, 75.5 % of the estimates were less than 10 deer/km2, and only 5.5 % were greater than 15 deer/km2. The highest densities were obtained in the northern region by applying the strip transect counts; while estimations using the fecal group count method were more variable and were the most used method in temperate and tropical dry forest regions. The states with the highest densities were Coahuila, Tamaulipas, Jalisco, Morelos, Michoacán, and Durango. The highest densities were estimated in the xerophilous scrublands of the northeast, intermediate for temperate, tropical dry, and sub-deciduous forests; and the lowest in the tropical wet forest. The highest densities were reported for the Tamaulipeca province followed by the Altiplano Chihuahuense, Sierra Madre Occidental, Costa Pacífica, and Depresión del Balsas. The results of this analysis could guide management strategies for the conservation and sustainable use of this species in extensive UMAs and ANPs, and also to test ecological hypotheses. However, applying more rigorous field design and statistical analysis is important to obtain confident estimates of population density and other demographic parameters to monitor population dynamics.