scholarly journals Estimating the density of small population of leopard Panthera pardus using multi-session photographic□sampling data

2020 ◽  
Author(s):  
Mohammad S. Farhadinia ◽  
Pouyan Behnoud ◽  
Kaveh Hobeali ◽  
Seyed Jalal Mousavi ◽  
Fatemeh Hosseini-Zavarei ◽  
...  
Keyword(s):  
Population Density ◽  
Arid Regions ◽  
Animal Movement ◽  
Small Population ◽  
Conservation Priorities ◽  
Large Carnivores ◽  
Panthera Pardus ◽  
Demographic Stochasticity ◽  
Density Estimates ◽  
Capture Recapture

AbstractWest Asian drylands host a number of threatened large carnivores, including the leopard (Panthera pardus) which is limited to spatially scattered landscapes with generally low primary productivity. While conservation efforts have focused on these areas for several decades, reliable population density estimates are missing. Spatially-explicit capture-recapture (SECR) methodology, incorporating animal movement in density estimates, is widely used to monitor populations of large carnivores. We employed multi-session SECR modeling to estimate the density of a small population of leopard (Panthera pardus) in a mountainous stretch surrounded by deserts in central Iran. During 6724 camera trap nights, we detected eight and five independent leopards in 2012 and 2016 sessions, respectively. The top performing model demonstrated density estimates of 1.6 (95% CI = 0.9-2.9) and 1.0 (95% CI = 0.6-1.6) independent leopards/100 km2 in 2012 and 2016, respectively. Both sex and season had substantial effects on spatial scale (σ), with larger movements for males and during winter. Currently available estimates in arid regions represent some of the lowest densities across the leopard global range. These small populations are vulnerable to demographic stochasticity. Monitoring temporal changes in population density and composition can inform conservation priorities.

scholarly journals Estimating the density of a small population of leopards (Panthera pardus) in central Iran using multi-session photographic‐sampling data

2021 ◽  
Author(s):  
Mohammad S. Farhadinia ◽  
Pouyan Behnoud ◽  
Kaveh Hobeali ◽  
Seyed Jalal Mousavi ◽  
Fatemeh Hosseini-Zavarei ◽  
...  
Keyword(s):  
Population Density ◽  
Density Estimation ◽  
Animal Movement ◽  
Small Population ◽  
Central Iran ◽  
Large Carnivores ◽  
Panthera Pardus ◽  
Demographic Stochasticity ◽  
Density Estimates ◽  
Capture Recapture

AbstractWest Asian drylands host a number of threatened large carnivores, including the leopard (Panthera pardus) which is limited generally to areas with low primary productivity. While conservation efforts have focused on these areas for several decades, reliable population density estimates are missing for many of them. Spatially explicit capture–recapture (SECR) methodology is a widely accepted population density estimation tool to monitor populations of large carnivores and it incorporates animal movement in the statistical estimation process. We employed multi-session maximum-likelihood SECR modeling to estimate the density of a small population of leopard in a mountainous environment surrounded by deserts in central Iran. During 6724 camera trap nights, we detected 8 and 5 independent leopards in 2012 and 2016 sessions, respectively. The top-performing model produced density estimates of 1.6 (95% CI = 0.9–2.9) and 1.0 (95% CI = 0.6–1.6) independent leopards/100 km2 in 2012 and 2016, respectively. Both sex and season had substantial effects on spatial scale (σ), with larger movements recorded for males, and during winter. The estimates from our density estimation exercise represent some of the lowest densities across the leopard global range and strengthen the notion that arid habitats support low densities of the species. These small populations are vulnerable to demographic stochasticity, and monitoring temporal changes in their population density and composition is a critical tool in assisting conservation managers to better understand their population performance.

scholarly journals Assumptions about fence permeability influence density estimates for brown hyaenas across South Africa

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kathryn S. Williams ◽  
Samual T. Williams ◽  
Rebecca J. Welch ◽  
Courtney J. Marneweck ◽  
Gareth K. H. Mann ◽  
...  
Keyword(s):  
South Africa ◽  
Population Density ◽  
Wildlife Management ◽  
Management Decisions ◽  
Density Estimates ◽  
Future Studies ◽  
Dominant Feature ◽  
Capture Recapture ◽  
Number Of Individuals ◽  
Density Results

AbstractWildlife population density estimates provide information on the number of individuals in an area and influence conservation management decisions. Thus, accuracy is vital. A dominant feature in many landscapes globally is fencing, yet the implications of fence permeability on density estimation using spatial capture-recapture modelling are seldom considered. We used camera trap data from 15 fenced reserves across South Africa to examine the density of brown hyaenas (Parahyaena brunnea). We estimated density and modelled its relationship with a suite of covariates when fenced reserve boundaries were assumed to be permeable or impermeable to hyaena movements. The best performing models were those that included only the influence of study site on both hyaena density and detection probability, regardless of assumptions of fence permeability. When fences were considered impermeable, densities ranged from 2.55 to 15.06 animals per 100 km2, but when fences were considered permeable, density estimates were on average 9.52 times lower (from 0.17 to 1.59 animals per 100 km2). Fence permeability should therefore be an essential consideration when estimating density, especially since density results can considerably influence wildlife management decisions. In the absence of strong evidence to the contrary, future studies in fenced areas should assume some degree of permeability in order to avoid overestimating population density.

scholarly journals Leopard Panthera pardus fusca Density in the Seasonally Dry, Subtropical Forest in the Bhabhar of Terai Arc, Nepal

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Kanchan Thapa ◽  
Rinjan Shrestha ◽  
Jhamak Karki ◽  
Gokarna Jung Thapa ◽  
Naresh Subedi ◽  
...  
Keyword(s):  
Winter Season ◽  
Population Monitoring ◽  
Panthera Pardus ◽  
Density Estimates ◽  
Seasonally Dry ◽  
Abundance Estimates ◽  
Capture Recapture ◽  
Modelling Techniques ◽  
Wildlife Reserve

We estimated leopard (Panthera pardus fusca) abundance and density in the Bhabhar physiographic region in Parsa Wildlife Reserve, Nepal. The camera trap grid, covering sampling area of 289 km2 with 88 locations, accumulated 1,342 trap nights in 64 days in the winter season of 2008-2009 and photographed 19 individual leopards. Using models incorporating heterogeneity, we estimated 28 (±SE 6.07) and 29.58 (±SE 10.44) leopards in Programs CAPTURE and MARK. Density estimates via 1/2 MMDM methods were 5.61 (±SE 1.30) and 5.93 (±SE 2.15) leopards per 100 km2 using abundance estimates from CAPTURE and MARK, respectively. Spatially explicit capture recapture (SECR) models resulted in lower density estimates, 3.78 (±SE 0.85) and 3.48 (±SE 0.83) leopards per 100 km2, in likelihood based program DENSITY and Bayesian based program SPACECAP, respectively. The 1/2 MMDM methods have been known to provide much higher density estimates than SECR modelling techniques. However, our SECR models resulted in high leopard density comparable to areas considered better habitat in Nepal indicating a potentially dense population compared to other sites. We provide the first density estimates for leopards in the Bhabhar and a baseline for long term population monitoring of leopards in Parsa Wildlife Reserve and across the Terai Arc.

scholarly journals Divergent population trends following the cessation of legal grizzly bear hunting in southwestern British Columbia, Canada

2020 ◽  
Author(s):  
Michelle McLellan ◽  
BN McLellan ◽  
R Sollmann ◽  
CT Lamb ◽  
CD Apps ◽  
...  
Keyword(s):  
British Columbia ◽  
Population Density ◽  
Habitat Quality ◽  
Ursus Arctos ◽  
Population Change ◽  
High Energy ◽  
Small Population ◽  
Dominant Factor ◽  
Grizzly Bear ◽  
Capture Recapture

© 2019 Elsevier Ltd We conducted DNA capture-recapture monitoring of grizzly bears (Ursus arctos) from 5 to 17 years after hunting was stopped in two adjacent but genetically distinct populations in southwestern British Columbia, Canada. We used spatial capture-recapture and non-spatial Pradel robust design modelling to estimate population density, trends, and the demographic components of population change for each population. The larger population had 21.5 bears/1000 km 2 and was growing (λ Pradel = 1.02 ± 0.02 SE; λ secr = 1.01 ± 4.6 × 10 −5 SE) following the cessation of hunting. The adjacent smaller population had 6.3 bears/1000 km 2 and was likely declining (λ Pradel = 0.95 ± 0.03 SE; λ secr = 0.98 ± 0.02 SE). Estimates of apparent survival and apparent recruitment indicated that lower recruitment was the dominant factor limiting population growth in the smaller population. Factors limiting reproductive rates and population density could include poor habitat quality, particularly the abundance of high-energy foods, genetic Allee effects due to a long period of population isolation, or demographic effects affecting infanticide rates. The cessation of hunting was insufficient to promote population recovery for the low density, isolated population. Our research highlights the importance of considering mortality thresholds in addition to small population effects and habitat quality when recovering large carnivore populations.

scholarly journals Divergent population trends following the cessation of legal grizzly bear hunting in southwestern British Columbia, Canada

2020 ◽  
Author(s):  
Michelle McLellan ◽  
BN McLellan ◽  
R Sollmann ◽  
CT Lamb ◽  
CD Apps ◽  
...  
Keyword(s):  
British Columbia ◽  
Population Density ◽  
Habitat Quality ◽  
Ursus Arctos ◽  
Population Change ◽  
High Energy ◽  
Small Population ◽  
Dominant Factor ◽  
Grizzly Bear ◽  
Capture Recapture

© 2019 Elsevier Ltd We conducted DNA capture-recapture monitoring of grizzly bears (Ursus arctos) from 5 to 17 years after hunting was stopped in two adjacent but genetically distinct populations in southwestern British Columbia, Canada. We used spatial capture-recapture and non-spatial Pradel robust design modelling to estimate population density, trends, and the demographic components of population change for each population. The larger population had 21.5 bears/1000 km 2 and was growing (λ Pradel = 1.02 ± 0.02 SE; λ secr = 1.01 ± 4.6 × 10 −5 SE) following the cessation of hunting. The adjacent smaller population had 6.3 bears/1000 km 2 and was likely declining (λ Pradel = 0.95 ± 0.03 SE; λ secr = 0.98 ± 0.02 SE). Estimates of apparent survival and apparent recruitment indicated that lower recruitment was the dominant factor limiting population growth in the smaller population. Factors limiting reproductive rates and population density could include poor habitat quality, particularly the abundance of high-energy foods, genetic Allee effects due to a long period of population isolation, or demographic effects affecting infanticide rates. The cessation of hunting was insufficient to promote population recovery for the low density, isolated population. Our research highlights the importance of considering mortality thresholds in addition to small population effects and habitat quality when recovering large carnivore populations.

Estimating lizard population density: an empirical comparison between line-transect and capture–recapture methods

2013 ◽  
Vol 40 (7) ◽  
pp. 552 ◽  
Author(s):  
J. Ruiz de Infante Anton ◽  
A. Rotger ◽  
J. M. Igual ◽  
G. Tavecchia
Keyword(s):  
Population Density ◽  
Spatial Data ◽  
Natural Populations ◽  
Line Transect ◽  
Sampling Errors ◽  
Density Estimates ◽  
Mark Recapture ◽  
The Real ◽  
Podarcis Lilfordi ◽  
Capture Recapture

Context In most natural populations, exhaustive counts are not possible and estimates need to be derived from partial sampling by using analytical methods that account for biological processes, sampling errors and detection probability. The methods available have contrasting pitfalls and payoffs in relation to the assumptions made but are seldom contrasted on the same population. Aims We compared density estimates derived by different sampling methods. Despite the real density being unknown, the ‘soft’ validation of density estimates might help to better understand the possible pitfalls and payoffs of each method. This was done in three closed populations and with three different habitat typologies to disentangle the effects of different capture-detection processes to those introduced by the method itself. Methods We considered the problem of estimating population density of the endemic Balearic lizard, Podarcis lilfordi, in three island populations. We compared estimates derived by distance sampling (LT) in three types of habitat with those calculated from a simultaneous 3-day capture–mark–recapture study. Capture histories of marked individuals were used to estimate density using spatially explicit capture–recapture models (SECR) and a capture–mark–recapture model without spatial data (CMR). Moreover, we empirically assessed the influence of survey duration by extending the survey in the largest island to five occasions. The real population density was unknown and absolute accuracy of each method cannot be assessed; nevertheless, relative estimates might be informative. Key results LT estimates had the greatest coefficient of variation in vegetated habitats, corresponding to possible departures from model assumptions. SECR estimates differed among islands and were from 12% to 37% lower than those derived by LT but only in the largest islands with high and dense vegetation. CMR estimates depended on the number of occasions whereas SECR did not and showed lower variance. LT and SECR estimates showed differences across islets. Conclusions Line-transect and capture–recapture methods gave comparable results but the interaction between recapture processes and habitat types should be considered when inferring density to the whole area. We found density estimates between 1500 and 2500 individuals ha–1, being a higher value than those found for lizards in continental regions. Implications Pitfalls and payoffs of each method are discussed to optimise experimental design in estimating population density.

scholarly journals Abundance and density estimates for common leopard Panthera pardus and clouded leopard Neofelis nebulosa in Manas National Park, Assam, India

Oryx ◽  
2013 ◽  
Vol 48 (1) ◽  
pp. 149-155 ◽  
Author(s):  
Jimmy Borah ◽  
Tridip Sharma ◽  
Dhritiman Das ◽  
Nilmani Rabha ◽  
Niraj Kakati ◽  
...  
Keyword(s):  
National Park ◽  
Camera Traps ◽  
Camera Trapping ◽  
Spatially Explicit ◽  
Panthera Pardus ◽  
Density Estimates ◽  
Clouded Leopard ◽  
Neofelis Nebulosa ◽  
Capture Recapture ◽  
The Common

AbstractEffective conservation of rare carnivores requires reliable estimates of population density for prioritizing investments and assessing the effectiveness of conservation interventions. We used camera traps and capture–recapture analysis to provide the first reliable abundance and density estimates for the common leopard Panthera pardus and clouded leopard Neofelis nebulosa in Manas National Park, India. In 57 days of camera trapping, with a total of 4,275 camera-trap days, we photo-captured 27 individually identified common leopards (11 males, 13 females and three unidentified), and 16 clouded leopards (four males, five females and seven unidentified). The abundance estimates using the Mh jackknife and Pledger model Mh were 47.0 and 35.6, respectively, for the common leopard, and 21.0 and 25.0, respectively, for the clouded leopard. Density estimates using maximum likelihood spatially-explicit capture–recapture were 3.4 ± SE 0.82 and 4.73 ± SE 1.43 per 100 km2 for the common and clouded leopards, respectively. Spatially-explicit capture–recapture provided more realistic density estimates compared with those obtained from conventional methods. Our data indicates that camera trapping using a capture–recapture framework is an effective tool for assessing population sizes of cryptic and elusive carnivores such as the common and clouded leopards. The study has established a baseline for the long-term monitoring programme for large carnivores in Manas National Park.

scholarly journals Population Density or Populations Size. Which Factor Determines Urban Traffic Congestion?

2021 ◽  
Vol 13 (8) ◽  
pp. 4280
Author(s):  
Yu Sang Chang ◽  
Sung Jun Jo ◽  
Yoo-Taek Lee ◽  
Yoonji Lee
Keyword(s):  
Population Density ◽  
Population Size ◽  
Traffic Congestion ◽  
Critical Role ◽  
Small Population ◽  
High Density ◽  
Urban Traffic ◽  
Contradictory Result ◽  
Low Density

A large number of articles have documented that as population density of cities increases, car use declines and public transit use rises. These articles had a significant impact of promoting high-density compact urban development to mitigate traffic congestion. Another approach followed by other researchers used the urban scaling model to indicate that traffic congestion increases as population size of cities increases, thus generating a possible contradictory result. Therefore, this study examines the role of both density and population size on traffic congestion in 164 global cities by the use of Stochastic Impacts by Regression on Population, Affluence and Technology model. We divide 164 cities into the two subgroups of 66 low density cities and 98 high density cities for analysis. The findings from the subgroups analysis indicated a clear-cut difference on the critical role of density in low-density cities and the exclusive role of population size in high-density cities. Furthermore, using threshold regression model, 164 cities are divided into the two regions of large and small population cities to determine population scale advantage of traffic congestion. Our findings highlight the importance of including analysis of subgroups based on density and/or population size in future studies of traffic congestion.

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