Trophy hunting is often employed as a conservation management tool for large predators. However, in order for this method to succeed, hunting levels must be sustainable. Very little robust population data exist for African leopards (Panthera pardus) in general, and almost no density or spatial ecology data exist for leopards in Zimbabwe. Zimbabwe has one of the highest annual CITES leopard trophy hunting quotas in Africa, the sustainability of which has not been assessed, despite large scale landuse changes over the last 12 years. The focal area of this study was within the Mangwe district, in the south-west of Zimbabwe. The region is dominated by cattle and wildlife ranches, with high levels of leopard hunting, making it an important area for assessing leopard population density and spatial ecology. Three population density estimation methods were employed in my study: a spoor index survey, an unbaited camera-trapping survey and a baited camera-trapping survey. Using three calibration equations, spoor indices appeared to underestimate the leopard population (1.28-3.29 leopards/ 100 km²) as the equations were calibrated for areas with different habitats and leopard densities. In addition, the unbaited camera survey only produced six leopard photographs, unsuitable for individual identification and analysis. By contrast, the baited camera survey produced 292 identifiable leopard photographs, from which 13 individuals were identified. Density estimates calculated using the programme CAPTURE and the M[subscript]h model with the Mean Maximum Distance Moved Outside of Study Area (MMDMOSA) buffer method (4.79±0.83 leopards/100 km²), and the programme SPACECAP, using a buffer of 2.5 km (5.12±0.62 leopards/100 km²), appeared to generate the most reliable leopard population estimates. To assess the spatial ecology, three leopards (one male, two females) were captured and fitted with GPS collars. The home range estimates of the three leopards (95% Kernel UD: male 263 km², females 31 and 45 km²) were smaller than those of leopards in more arid regions, but larger than those of mesic habitats. This suggests that the Mangwe area has a higher quality habitat than the arid regions of Namibia, but less suitable habitat than protected bushveld areas (e.g. Kruger National Park, South Africa). My data represents the first robust leopard density and home range assessment for Zimbabwe. In addition, my results indicate that the current hunting quota issued to the Mangwe area is unsustainable. Consequently, I recommend revising the quota to five leopards for the entire area, and halving the current national leopard quota to 250, until a national leopard census is completed.

Biodiversity monitoring and predictions of species occurrence are essential to develop outcome-oriented conservation management plans for endangered species and assess their success over time. To assess distribution and patterns of habitat use of large mammal assemblages in Thailand, with a focus on the endangered dhole (Cuon alpinus), I first implemented a long-term camera-trapping project carried out with park rangers from October 2003 through October 2007 in Khao Yai National Park. This project was extremely successful and may serve as a regional model for wildlife conservation. I found significantly lower relative abundance indices for carnivore species, and collectively for all mammals compared to data obtained in 1999-2000, suggesting population declines resulting from increased human activity. I integrated this data into maximum entropy modeling (Maxent) to further evaluate whether ranger stations reduced poaching activity and increased wildlife diversity and abundances. I then conducted a focused camera trap survey from January 2008 through February 2010 in Khao Ang Rue Nai Wildlife Sanctuary to gather critical baseline information on dholes, one of the predator species that seemed to have declined over time and that is exposed to continued pressure from humans. Additionally, I led a collaborative effort with other colleagues in the field to collate and integrate camera trap data from 15 protected areas to build a country-wide habitat suitability map for dholes, other predators, and their major prey species. The predicted presence probability for sambar (Rusa unicolor) and leopards (Panthera pardus) were the most important variables in predicting dhole presence countrywide. Based on my experience from these different field ecological surveys and endeavors, it became clear that local people's beliefs may have a strong influence on dhole management and conservation. Thus, I conducted villager interview surveys to identify local attitudes towards dholes, document the status of dholes in wildlife sanctuaries adjacent to Cambodia, and determine the best approach to improve local support for dhole conservation before proceeding with further field studies of the species in Thailand. A photograph of a dhole was correctly identified by only 20% of the respondents. My studies provide evidence that some protected areas in Thailand continue to support a diversity of carnivore speices of conservation concern, including clouded leopards (Neofelis nebulosa), dholes, and small felids. However, dholes' impact on prey populations may be increasing as tiger (Panthera tigris) and leopards are extripated from protected areas. The next step in dhole conservation is to estimate the size and stability of their fragmented populations and also focus on maintaining adequate prey bases that would support both large felids and dholes

The study was conducted in the Greater Kruger National Park Complex (GKNP), which consists of the Kruger National Park (KNP) and adjacent private game reserves and focuses primarily on the following objectives: • To monitor and evaluate the standard of the existing disease surveillance programmes for the following diseases, Foot and Mouth, Anthrax, Tuberculosis, Brucellosis and Rabies, within the Kruger National Park and adjacent private game reserves by evaluating the level of competency and knowledge in field rangers, field guides and trails rangers with regard to these specific diseases. It can be stated that important differences exist between disease surveillance techniques used for domestic animals and those used for wildlife (Bengis, R.G., Kock, R.A., & Fischer, J., 2002). According to Morner, T., Obendorf, D.L., Artios, M., & Woodford, M.H., 2002, it is more difficult to monitor diseases in wildlife than in domestic animals because wild animals are not constrained by boundaries and can roam over large. distances. For significant diseases in wildlife, an active surveillance programme may be the preferred approach with the aim to collect a certain number of samples from a target population (live or dead animals) to determine the point prevalence of certain pathogens. Active veterinary participation is essential in protected area management, with emphasis on training of technicians, rangers and field biologists with regard to specific diseases and their clinical signs, surveillance and sampling techniques, data collection, and reporting. For the purpose of this study, data collection was conducted by means of a questionnaire drawn up according to the related critical points as described in the Dufour grid (Dufour, 1998). The results of this study clearly showed a need to address certain important aspects regarding a wildlife disease programme within the GKNP. A more efficient wildlife disease surveillance programme, which included more specific and “hands-on” trained staff, would definitely ensure a better early warning system which would detect new or emerging disease outbreaks. / M. Tech. (Nature Conservation))

Thesis (M.S.)--University of Tennessee, Knoxville, 2008. / Title from title page screen (viewed on Sept. 23, 2009). Thesis advisor: Frank T. van Manen. Vita. Includes bibliographical references.

The study was conducted in the Greater Kruger National Park Complex (GKNP), which consists of the Kruger National Park (KNP) and adjacent private game reserves and focuses primarily on the following objectives: • To monitor and evaluate the standard of the existing disease surveillance programmes for the following diseases, Foot and Mouth, Anthrax, Tuberculosis, Brucellosis and Rabies, within the Kruger National Park and adjacent private game reserves by evaluating the level of competency and knowledge in field rangers, field guides and trails rangers with regard to these specific diseases. It can be stated that important differences exist between disease surveillance techniques used for domestic animals and those used for wildlife (Bengis, R.G., Kock, R.A., & Fischer, J., 2002). According to Morner, T., Obendorf, D.L., Artios, M., & Woodford, M.H., 2002, it is more difficult to monitor diseases in wildlife than in domestic animals because wild animals are not constrained by boundaries and can roam over large. distances. For significant diseases in wildlife, an active surveillance programme may be the preferred approach with the aim to collect a certain number of samples from a target population (live or dead animals) to determine the point prevalence of certain pathogens. Active veterinary participation is essential in protected area management, with emphasis on training of technicians, rangers and field biologists with regard to specific diseases and their clinical signs, surveillance and sampling techniques, data collection, and reporting. For the purpose of this study, data collection was conducted by means of a questionnaire drawn up according to the related critical points as described in the Dufour grid (Dufour, 1998). The results of this study clearly showed a need to address certain important aspects regarding a wildlife disease programme within the GKNP. A more efficient wildlife disease surveillance programme, which included more specific and “hands-on” trained staff, would definitely ensure a better early warning system which would detect new or emerging disease outbreaks. / M. Tech. (Nature Conservation))

Abstract Wild populations of large carnivores in Europe were almost wiped out during the last centuries. Nowadays, the number of brown bears in North and Eastern Europe has increased, and the current situation suggests that these populations have recovered or are in the process of recovery. Knowledge of the population genetic consequences of demographic recovery in large carnivores, especially across national borders and on broader geographical scales, is still limited. In this study, we collected 3,757 fecal and hair samples as well as 881 tissue samples from brown bears across Northern Europe, with a focus on the Finnish population and neighboring areas, to investigate the population structure, connectivity, and genetic diversity on a spatial as well as a temporal scale. Bayesian clustering analysis of the population structure suggested the division of brown bears in Northern Europe into several genetic clusters, and the subdivision of the Finnish population into a northern and southern subpopulation. The estimation of gene flow pointed to better connectivity of the bears between Southern Finland and Western Russia, while migration between Scandinavia and Northern Finland as well as between Scandinavia and Southern Finland/Western Russia appeared to be restricted. Genetic clusters identified in Finland, Russia and Northern Norway displayed high genetic diversity, which was among the highest reported in wild brown bears. Recovery of the Finnish population has been accompanied by a detected range expansion towards the north, while genetic differentiation between clusters has decreased and genetic diversity has increased in the southern population, suggesting expansion from the south. Our results demonstrated that the immigration of bears from Russia still plays a major role in the Finnish bear population; however, connectivity between the Finnish-Russian population and Scandinavian bears appears to be restricted and should be improved, as well as regularly monitored. / Tiivistelmä Suurpetojen luonnonpopulaatiot hävisivät Euroopasta melkein kokonaan viimeisten vuosisatojen aikana. Ruskeakarhujen määrä on viime aikoina kasvanut Pohjois- ja Itä-Euroopassa, ja karhupopulaatiot ovat toipuneet tai toipumassa. Tieto demografisen toipumisen geneettisistä seurauksista populaatioissa on varsin rajoittunutta etenkin laajemmassa maantieteellisessä mittakaavassa, yli valtiorajojen. Keräsimme tätä tutkimusta varten 3757 uloste- ja karvanäytettä ja 881 kudosnäytettä Suomesta ja sen lähialueilta. Tarkoituksenamme oli kartoittaa Pohjois-Euroopan karhupopulaatioiden geneettistä rakennetta ja monimuotoisuutta, sekä populaatioiden välisiä yhteyksiä huomioiden ajallinen ja maantieteellinen ulottuvuus. Bayesiläisen ryhmittelyanalyysin perusteella Pohjois-Euroopan karhut jakaantuvat useaan geneettiseen ryhmään. Suomen populaatiossa erottuivat eteläinen ja pohjoinen alapopulaatio. Analyysit geenivirran määrästä osoittivat, että Etelä-Suomen ja Länsi-Venäjän karhupopulaatiot ovat yhteneväisemmät, kun taas migraatio Skandinavian ja Pohjois-Suomen sekä Etelä-Suomen ja Länsi-Venäjän välillä vaikuttaisi olevan rajoittunutta. Suomesta, Venäjältä ja Pohjois-Norjasta tunnistetut alaryhmät olivat geneettisesti hyvin monimuotoisia, ja muuntelu oli korkeampaa kuin koskaan aiemmin karhuilla havaittu. Suomen karhupopulaation toipuessa ja levitessä pohjoiseen, geneettinen erilaistuminen maan sisällä on vähentynyt ja eteläisen alapopulaation monimuotoisuus kasvanut. Tämä viittaa populaation laajentumiseen etelästä käsin. Tulosten perusteella karhujen tulomuutto Venäjältä on yhä tärkeää Suomen populaatiolle. Suomen ja Venäjän karhupopulaatioiden yhteyttä Skandinavian karhupopulaatioihin tulisi seurata ja parantaa.

Leopards (Panthera pardus) are the most common large predators, free roaming outside of protected areas across most of South Africa. Leopard persistence is attributed to their tolerance of rugged terrain that is subject to less development pressure, as well as their cryptic behaviour. Nevertheless, existing leopard populations are threatened indirectly by ongoing transformation of natural habitat and directly through hunting and conflict with livestock farmers. Together these threats may further isolate leopards to fragmented areas of core natural habitat. I studied leopard habitat preferences, population density, diet and the attitudes of landowners towards leopards in the Little Karoo, Western Cape, South Africa, an area of mixed land-use that contains elements of three overlapping global biodiversity hotspots. Data were gathered between 2010 and 2012 using camera traps set up at 141 sites over an area of ~3100km², GPS tracking collars fitted to three male leopards, scat samples (n=76), interviews with landowners (n=53) analysed in combination with geographical information system (GIS) layers. My results reveal that leopards preferred rugged, mountainous terrain of intermediate elevation, avoiding low-lying, open areas where human disturbance was generally greater. Despite relatively un-fragmented habitat within my study area, the leopard population density (0.75 leopards/100km²) was one of the lowest yet recorded in South Africa. This may reflect low prey densities in mountain refuges in addition to historical human persecution in the area. Currently local landowners are more tolerant of leopards than other wildlife species with incidents of conflict involving leopards being rare relative to black-backed jackals (Canis mesomelas), baboons (Papio hamadryas), caracals (Caracal caracal) and porcupine (Hystrix africaeaustralis). Although current levels of conflict between leopards and stock farmers are low, leopards do depredate livestock, which constitute 10-15% of their diet. Improved livestock husbandry measures and co-operation between conservation authorities and farmers are necessary to mitigate such conflict and balance economic security with biodiversity conservation in the region. Leopards are the only remaining top predators throughout much of the Little Karoo and the Western Cape and as such are predicted to play a critical role in ecosystem structure and the survival of other species. Current high levels of connectivity between areas of suitable leopard habitat bode well for the conservation status of leopards within this region and future conservation efforts need to ensure that narrow corridors linking such habitat are preserved. The potential for leopards to serve as both an umbrella and a flagship species for biodiversity conservation suggests that long term monitoring of this population would be a conservation priority for the Little Karoo.

The conservation of leopards in the Eastern Cape Province requires a holistic approach that considers both predator-human interactions as well as the biology of the carnivore. Numerous studies have been conducted on leopards within protected areas; however more information regarding the species is needed outside these areas to facilitate effective management of predators. The spatial ecology of the leopard (Panthera pardus) were studied in the Baviaanskloof and GAENP in the Eastern Cape. The Baviaanskloof is an extensive area of mountainous terrain (approximately 2665km²) which has a mosaic of land uses, and leopards move from conservation areas to farmland where they come into contact and conflict with farmers. This study examined the spatial ecology of leopards living on farmlands adjacent to protected land. The space utilization and activity patterns of six leopards were analysed. These animals were caught and released on farmlands in the Baviaanskloof (n=4) or translocated (n=2) when not possible to release on site. The animals were caught by means of fall-door, walk-in traps and fitted with Vectronic GPS collars that facilitated the collection of high quality GPS fixes from each animal. Data was collected using VHF and UHF telemetry to download data. An understanding of spatial requirements in areas with different land use, and the extent of overlap of space use with other leopards allow, for the first time in the region, the calculation of possible maximum population size. Analysis of range size was carried out using two methods: minimum convex polygon, and Kernel Utilization Distribution. Finally, a key predictor of space use is prey availability. I assessed the prey base using a grid of camera traps. The studied leopards revealed large range utilization with minimal overlap. The activity patterns suggest there is no preference between diurnal and nocturnal activity patterns and the population density was estimated between 0.3 - 1.3 leopards per 100km². Large home range sizes and low population densities suggest that leopards require large areas of suitable habitat, and that conservation efforts need to be extended beyond protected areas to ensure the long-term viability of leopard populations in such areas.

This master’s thesis investigates the application of advanced machine learning models for the identification and classification of Swedish predators using camera trap images. With the growing threats to biodiversity, there is an urgent need for innovative and non-intrusive monitoring techniques. This study focuses on the development and evaluation of object detection models, including YOLOv5, YOLOv8, YOLOv9, and Faster R-CNN, aiming to enhance the surveillance capabilities of Swedish predatory species such as bears, wolves, lynxes, foxes, and wolverines. The research leverages a dataset from the NINA database, applying data preprocessing and augmentation techniques to ensure robust model training. The models were trained and evaluated using various dataset sizes and conditions, including day and night images. Notably, YOLOv8 and YOLOv9 underwent extended training for 300 epochs, leading to significant improvements in performance metrics. The performance of the models was evaluated using metrics such as mean Average Precision (mAP), precision, recall, and F1-score. YOLOv9, with its innovative Programmable Gradient Information (PGI) and GELAN architecture, demonstrated superior accuracy and reliability, achieving an F1-score of 0.98 on the expanded dataset. The research found that training models on images captured during both day and night jointly versus separately resulted in only minor differences in performance. However, models trained exclusively on daytime images showed slightly better performance due to more consistent and favorable lighting conditions. The study also revealed a positive correlation between the size of the training dataset and model performance, with larger datasets yielding better results across all metrics. However, the marginal gains decreased as the dataset size increased, suggesting diminishing returns. Among the species studied, foxes were the least challenging for the models to detect and identify, while wolves presented more significant challenges, likely due to their complex fur patterns and coloration blending with the background.