Density of Large Predators on Commercial Farmland in Ghanzi, Botswana

Large carnivores are decreasing in number due to growing pressure from an expanding human population. It is increasingly recognised that state-protected conservation areas are unlikely to be sufficient to protect viable populations of large carnivores, and that private land will be central to conservation efforts. In 2000, a fast-track land reform programme (FTLRP) was initiated in Zimbabwe, ostensibly to redress the racial imbalance in land ownership, but which also had the potential to break up large areas of carnivore habitat on private land. To date, research has focused on the impact of the FTLRP process on the different human communities, while impacts on wildlife have been overlooked. Here we provide the first systematic assessment of the impact of the FTLRP on the status of large carnivores. Spoor counts were conducted across private, resettled and communal land use types in order to estimate the abundance of large carnivores, and to determine how this had been affected by land reform. The density of carnivore spoor differed significantly between land use types, and was lower on resettlement land than on private land, suggesting that the resettlement process has resulted in a substantial decline in carnivore abundance. Habitat loss and high levels of poaching in and around resettlement areas are the most likely causes. The FTLRP resulted in the large-scale conversion of land that was used sustainably and productively for wildlife into unsustainable, unproductive agricultural land uses. We recommended that models of land reform should consider the type of land available, that existing expertise in land management should be retained where possible, and that resettlement programmes should be carefully planned in order to minimise the impacts on wildlife and on people.

Section: Methodsmentioning

confidence: 99%

The impact of land reform on the status of large carnivores in Zimbabwe

Williams

Joubert³

et al. 2016

“…Lack of empirical field data on distribution status and population size has prevented a range-wide population estimate, although researchers have guessed or estimated population size for all subspecies in IUCN assessments and recent papers ( Laguardia et al, 2015 ; Rostro-García et al, 2016 ; Stein et al, in press ). At the local scale, estimates of leopard population densities vary 300-fold from 0.1 individuals/100 km 2 in the Ghanzi region of Botswana ( Boast & Houser, 2012 ), to 30.9/100 km 2 in Sariska Tiger Reserve, India ( Edgaonkar, 2008 ). The variation in leopard densities is at least partially attributable to habitat productivity ( Macdonald & Loveridge, 2010 ).…”

Section: Introductionmentioning

confidence: 99%

Leopard (Panthera pardus) status, distribution, and the research efforts across its range

Jacobson

Gerngross

Lemeris

et al. 2016

291

357

The leopard’s (Panthera pardus) broad geographic range, remarkable adaptability, and secretive nature have contributed to a misconception that this species might not be severely threatened across its range. We find that not only are several subspecies and regional populations critically endangered but also the overall range loss is greater than the average for terrestrial large carnivores. To assess the leopard’s status, we compile 6,000 records at 2,500 locations from over 1,300 sources on its historic (post 1750) and current distribution. We map the species across Africa and Asia, delineating areas where the species is confirmed present, is possibly present, is possibly extinct or is almost certainly extinct. The leopard now occupies 25–37% of its historic range, but this obscures important differences between subspecies. Of the nine recognized subspecies, three (P. p. pardus, fusca, and saxicolor) account for 97% of the leopard’s extant range while another three (P. p. orientalis, nimr, and japonensis) have each lost as much as 98% of their historic range. Isolation, small patch sizes, and few remaining patches further threaten the six subspecies that each have less than 100,000 km2 of extant range. Approximately 17% of extant leopard range is protected, although some endangered subspecies have far less. We found that while leopard research was increasing, research effort was primarily on the subspecies with the most remaining range whereas subspecies that are most in need of urgent attention were neglected.

“…This calibration included data for five of the seven large carnivores in Africa and spanned 18 different study sites from seven study areas in Namibia, Botswana, South Africa, Zimbabwe, Kenia and Tanzania (Funston et al, 2010). Some recent studies used these models to assess large carnivore densities in parts of Botswana (Bauer et al, 2014; Boast & Houser, 2012; Ferreira, Govender & Herbst, 2013; Kent & Hill, 2013). Refer to Funston et al (2010) for the protocols to conduct track count surveys.…”

Section: Introductionmentioning

confidence: 99%

“…This formula would yield negative density estimates below track densities of 0.4 tracks/100 km, for example carnivore density would be estimated as −0.06 animals per 100 km 2 from a track density of 0.2 tracks per 100 km. Boast & Houser (2012) resolved this problem for leopard by using the formula from Stander (1998) to estimate leopard densities at low track densities. Williams (2011) and Williams et al (2016) opted to use the lion and wild dog model from Stander (1998) to estimate carnivore densities, although this model is based on only four data points.…”

Section: Introductionmentioning

confidence: 99%

Simplified large African carnivore density estimators from track indices

Winterbach

Ferreira

Funston³

et al. 2016

BackgroundThe range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices.MethodsWe did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y = αx + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models.ResultsThe Lion on Clay and Low Density on Sand models with intercept were not significant (P > 0.05). The other four models with intercept and the six models thorough origin were all significant (P < 0.05). The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support.DiscussionOur results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26 × carnivore density can be used to estimate densities of large African carnivores using track counts on sandy substrates in areas where carnivore densities are 0.27 carnivores/100 km2 or higher. To improve the current models, we need independent data to validate the models and data to test for non-linear relationship between track indices and true density at low densities.