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Banteng (Bos javanicus) is listed as an endangered species because of a global population decline of at least 50% over the last 25 years. The Western Forest Complex (WEFCOM) of Thailand has been identified as a priority site for banteng population recovery, and Huai Kha Keang Wildlife Sanctuary (HKK) is the most important source site for this species within the WEFCOM. We have provided evidence and discussed banteng dispersal from HKK to Thung Yai Naresuan West Wildlife Sanctuary (TYW). We sampled an area of 147 km2 in banteng habitat next to the border between HKK and TYW using camera traps. We divided the sampled area into four grid cells and placed camera traps during January to December 2022. We setup the camera traps near saltlicks and natural water sources, as important resources for banteng, to maximize capture probability. In total, 2835 trap days were obtained. Bantengs were captured in all seasons (RAI = 1.66), especially in dry dipterocarp forest, which contains the ground forage availability for banteng, and the low‐slope area with elevation 600–700 m adjacent to the border between HKK and TYW. The results highlighted that banteng, which had never been reported in TYW before, appeared there for the first time. They most likely dispersed from the population source in HKK and settled in a habitat that is considered suitable for them. The habitat management and protection are significant for the future recovery of banteng populations in the TYW and the rest of protected areas in the WEFCOM. This article provided evidence and discussed the first dispersal of endangered banteng from Huai Kha Keang Wildlife Sanctuary, the core area of the world natural heritage site in Thailand, to Thung Yai Naresuan West Wildlife Sanctuary where the species has never been reported.

  Funding: The study (13) of the geographic distribution of tiger populations and the costs of protecting source sites was supported by a grant (GEF MSP grant TF093667) from the World Bank acting as implementing agency of the Global Environment Facility (GEF). While the scale of the challenge is enormous, we submit that the complexity of effective implementation is not: commitments should shift to focus on protecting tigers at spatially well-defined priority sites, supported by proven best practices of law enforcement, wildlife management, and scientific monitoring. If Russia is excluded from the analysis, 74% of the world's remaining tigers live in less than 4.5% of current tiger range. [...]protecting source sites offers the most pragmatic and efficient opportunity to conserve most of the world's remaining wild tigers.

Despite their extensive distribution globally, recent reports indicate leopards are declining, especially in Southeast Asia. To support conservation efforts we analyzed the behavioral interactions between leopards ( ), their prey, and tigers to determine if leopards fine-tune their activity to maximize contact with four prey species (sambar; wild boar; barking deer; banteng) and avoid tigers and if prey alter their temporal activity in response to variation in their relative abundance ratio with leopards. A lower density of sambar in the northern part of our study area and a lower density of wild boar and a higher density of tigers in the southern part allowed us to examine fine-grained differences in the behavior of leopards and their prey. We used camera trap data to investigate spatial and temporal overlap. Differences in tiger relative abundance did not appear to impact the temporal activity of leopards. Leopards had similar cathemeral activity at all sites with highest activity at dawn and dusk. This behavior appears to be a compromise to provide access to diurnal wild boar and barking deer and nocturnal sambar and banteng. Sambar showed higher temporal avoidance of leopards in the north where its RAI was lowest; in contrast, wild boar had the highest temporal avoidance in the south where its density was lowest. This is the first study in Southeast Asia to quantify spatial and temporal interactions between the leopard, its primary ungulate prey, and the tiger. It provides new insights for conserving this declining subspecies.

Many hornbill species in Thailand are categorized as Endangered or Critically Endangered on the IUCN Red List. The objectives of this research were to predict hornbill distributions in Thailand and to assess the national conservation status of the species using extent of occurrence. We employed maximum entropy modelling, using 10 environmental variables that were believed to directly or indirectly influence hornbill distributions across Thailand, to predict the habitats potentially suitable for 10 of the country's 13 hornbill species. Data on the presence of hornbills were gathered from the Thailand Hornbill Project and additional field surveys in protected area complexes during 2004–2006. The results indicated that patch size is the most important factor affecting distribution, followed by latitude, ecoregion and distance to villages. All hornbill species were predicted to occur primarily in intact protected area complexes. The total extent of all hornbill habitats covers 9.3% of the country's land area. Seven of the 10 modelled species are at risk and the current distribution pattern is expected to reflect stochastic extinctions because of small population size. We recommend that the conservation status of Austen's brown hornbill Anorrhinus austeni and Tickell's brown hornbill Anorrhinus tickelli should be changed from Vulnerable to Endangered. The model identified five protected area complexes as hornbill hotspots in Thailand. These findings will help guide conservation management.

Recovering small populations of threatened species is an important global conservation strategy. Monitoring the anticipated recovery, however, often relies on uncertain abundance indices rather than on rigorous demographic estimates. To counter the severe threat from poaching of wild tigers (Panthera tigris), the Government of Thailand established an intensive patrolling system in 2005 to protect and recover its largest source population in Huai Kha Khaeng Wildlife Sanctuary. Concurrently, we assessed the dynamics of this tiger population over the next 8 years with rigorous photographic capture-recapture methods. From 2006 to 2012, we sampled across 624-1026 km² with 137-200 camera traps. Cameras deployed for 21,359 trap days yielded photographic records of 90 distinct individuals. We used closed model Bayesian spatial capture-recapture methods to estimate tiger abundances annually. Abundance estimates were integrated with likelihood-based open model analyses to estimate rates of annual and overall rates of survival, recruitment, and changes in abundance. Estimates of demographic parameters fluctuated widely: annual density ranged from 1.25 to 2.01 tigers/100 km², abundance from 35 to 58 tigers, survival from 79.6% to 95.5%, and annual recruitment from 0 to 25 tigers. The number of distinct individuals photographed demonstrates the value of photographic capture-recapture methods for assessments of population dynamics in rare and elusive species that are identifiable from natural markings. Possibly because of poaching pressure, overall tiger densities at Huai Kha Khaeng were 82-90% lower than in ecologically comparable sites in India. However, intensified patrolling after 2006 appeared to reduce poaching and was correlated with marginal improvement in tiger survival and recruitment. Our results suggest that population recovery of low-density tiger populations may be slower than anticipated by current global strategies aimed at doubling the number of wild tigers in a decade. Recuperar las poblaciones pequeñas de las especies amenazadas es una importante estrategia global de conservación. Sin embargo, monitorear la recuperación esperada generalmente depende de índices inciertos de abundancia en lugar de estimados demográficos rigurosos. Para contrarrestar la gran amenaza causada por la cacería furtiva de tigres (Panthera tigris), el Gobierno de Tailandia estableció un sistema intensivo de patrullaje en 2005 para proteger y recuperar la población fuente más grande en el Santuario Huai Kha Khaeng. Simultáneamente, evaluamos las dinámicas de esta población de tigres durante los siguientes ocho años con rigurosos métodos fotográficos de captura-recaptura. De 2006 a 2012 muestreamos a lo largo de 624-1026 km² con 137-200 trampas cámara. Las cámaras desplegadas durante 21,359 días de trampa produjeron registros fotográficos de 90 individuos distinguibles. Usamos métodos espaciales de capturarecaptura y modelo bayesiano cerrado para estimar anualmente la abundancia de los tigres. Los estimados de abundancia estuvieron integrados por análisis de modelo abierto basados en la probabilidad para estimar la tasa anual y las tasas generales de supervivencia, reclutamiento y cambios en la abundancia. Los estimados de los parámetros demográficos fluctuaron ampliamente: la densidad anual varió entre 1.25 y 2.01 tigres/100 km², la abundancia entre 35 a 58 tigres, la supervivencia entre 79-6 y 95.5% y el reclutamiento anual de 0 a 25 tigres. El número de individuos distinguibles que fue fotografiado demuestra el valor de los métodos de captura-recaptura para la evaluación de las dinámicas poblacionales de especies raras y elusivas que son identificables gracias a marcas naturales. Posiblemente por causa de la presión ejercida por la caza furtiva, la densidad general de los tigres en Huai Kha Khaeng fue 82-90% más baja que en sitios ecológicamente comparables de India. Sin embargo, el patrullaje intensivo después de 2006 pareció reducir la caza furtiva y estuvo correlacionado con el mejoramiento marginal de la supervivencia y reclutamiento de los tigres. Nuestros resultados sugieren que la recuperación de las poblaciones de tigres con baja densidad puede ser más lenta de lo esperado por las estrategias globales actuales enfocadas en la duplicación del número de tigres en una década.

Despite conservation efforts, large mammals such as tigers (Panthera tigris) and their main prey, gaur (Bos gaurus), banteng (Bos javanicus), and sambar (Rusa unicolor), are highly threatened and declining across their entire range. The only large viable source population of tigers in mainland Southeast Asia occurs in Thailand's Western Forest Complex (WEFCOM), an approximately 19,000 km2 landscape of 17 contiguous protected areas. We used an occupancy modeling framework, which accounts for imperfect detection, to identify the factors that affect tiger distribution at the approximate scale of a female tiger's home range, 64 km2, and site use at a scale of 1‐km2. At the larger scale, we estimated the proportion of sites at WEFCOM that were occupied by tigers; at the finer scale, we identified the key variables that influence site‐use and developed a predictive distribution map. At both scales, we examined key anthropogenic and ecological factors that help explain tiger distribution and habitat use, including probabilities of gaur, banteng, and sambar occurrence from a companion study. Occupancy estimated at the 64‐km2 scale was primarily influenced by the combined presence of all three large prey species, and 37% or 5,858 km2 of the landscape was predicted to be occupied by tigers. In contrast, site use estimated at the scale of 1 km2 was most strongly influenced by the presence of sambar. By modeling occupancy while accounting for imperfect probability of detection, we established reliable benchmark data on the distribution of tigers in WEFCOM. This study also identified factors that limit tiger distributions; which managers can then target to expand tiger distribution and guide recovery elsewhere in Southeast Asia. This research presents the results of a multiple scale occupancy analysis of one of the largest tiger landscapes, the 19,000 km2 Western Forest Complex in Thailand. Despite its population is the best in Thailand and the large area that it occupies, tigers are estimated to occupy < half of this landscape. Our analysis demonstrates that the presence of the combination of all large mammals is the primary predictor on tiger occupancy at the approximate scale of a female tiger's home range (64 km2), but at a finer grain of site use (1 km2), sambar is primary predictor of habitat use.

Distance sampling is usually preferred over uncorrected point counts for surveys of forest birds, but rarely has its accuracy been assessed against known numbers, particularly in tropical forests. We compared density estimates of eight species of breeding bird—Black-naped Monarch (Hypothymis azurea), Hill Blue Flycatcher (Cyornis banyumas), White-rumped Shama (Copsychus malabaricus), Puff-throated Bulbul (Alophoixus pallidus), Abbott's Babbler (Malacocincla abbotti), Puff-throated Babbler (Pellorneum ruficeps), White-browed Scimitar Babbler (Pomatorhinus schisticeps), and White-bellied Yuhina (Yuhina zantholeuca)—obtained through color-banding, nest finding, and territory mapping with those derived from distance methods in evergreen forest in northeastern Thailand. We also assessed the availability of birds to be detected using a closed-capture model and incorporated this with point-transect distance sampling. Abundance estimates from territory mapping and distance sampling were highly correlated, but biased for two species using line transects and five species using point transects. Six of the seven biased estimates were biased low. Probabilities of detection were not significantly different between lines and points, and there was no significant difference in the overall accuracy between methods. Accounting for observer differences improved density estimates but reduced precision. The variance in accuracy was mostly related to the behavior of the different species. Adjusting for availability did not improve the overall accuracy of the estimates, because of the low singing rates of tropical birds. Nonetheless, distance sampling provided relatively robust estimates despite the near total dependence on aural cues. Violations of distance-sampling assumptions may be frequent in heavily forested habitats, where both availability for detection and probability of detection on the transect line (or point) are likely to be <1.

We used capture-recapture analyses to estimate the density of a tiger Panthera tigris population in the tropical forests of Huai Kha Khaeng Wildlife Sanctuary, Thailand, from photographic capture histories of 15 distinct individuals. The closure test results (z = 0.39, P = 0.65) provided some evidence in support of the demographic closure assumption. Fit of eight plausible closed models to the data indicated more support for model Mh, which incorporates individual heterogeneity in capture probabilities. This model generated an average capture probability $\\hat p$ = 0.42 and an abundance estimate of $\\widehat{N}(\\widehat{SE}[\\widehat{N}])$ = 19 (9.65) tigers. The sampled area of $\\widehat{A}(W)(\\widehat{SE}[\\widehat{A}(W)])$ = 477.2 (58.24) km2 yielded a density estimate of $\\widehat{D}(\\widehat{SE}[\\widehat{D}])$ = 3.98 (0.51) tigers per 100 km2. Huai Kha Khaeng Wildlife Sanctuary could therefore hold 113 tigers and the entire Western Forest Complex c. 720 tigers. Although based on field protocols that constrained us to use sub-optimal analyses, this estimated tiger density is comparable to tiger densities in Indian reserves that support moderate prey abundances. However, tiger densities in well-protected Indian reserves with high prey abundances are three times higher. If given adequate protection we believe that the Western Forest Complex of Thailand could potentially harbour >2,000 wild tigers, highlighting its importance for global tiger conservation. The monitoring approaches we recommend here would be useful for managing this tiger population.

Funding: The study (13) of the geographic distribution of tiger populations and the costs of protecting source sites was supported by a grant (GEF MSP grant TF093667) from the World Bank acting as implementing agency of the Global Environment Facility (GEF). While the scale of the challenge is enormous, we submit that the complexity of effective implementation is not: commitments should shift to focus on protecting tigers at spatially well-defined priority sites, supported by proven best practices of law enforcement, wildlife management, and scientific monitoring. If Russia is excluded from the analysis, 74% of the world's remaining tigers live in less than 4.5% of current tiger range. [...]protecting source sites offers the most pragmatic and efficient opportunity to conserve most of the world's remaining wild tigers.

We surveyed birds in two remnant patches of montane evergreen forest landscapes differing in intensity of habitat fragmentation, land use patterns and development. Present landscape configurations in Mae Tuen and Om Koi show that both became heavily fragmented (Table 1, see also Figure 1) between 1954 and 1996. The low abundance at Om Koi of large frugivores, such as Brown Hornbills Ptilolaemus tickelli and Great Hornbills Buceros bicornis, and their lack at Mae Tuen, are probably effects of prolonged fragmentation.