Identification of Areas Highly Vulnerable to Land Conversion: A Case Study From Southern Thailand.

Land conversion is having major impacts on wildlife globally, and thus understanding and predicting patterns of land conversion is an important component of conservation planning. Southeast Asia is undergoing rapid habitat conversion; however, most countries in the region have very limited human resources devoted to planning, and typically land-cover trend assessments are often challenging. Here we demonstrate a rapid method for land-cover change quantification for areas of terrestrial, mangrove and peat swamp forests at high risk from land conversion that can be quickly and simply predicted using southern Thailand as an example. Land-cover maps from two time periods (1995/1996 and 2015/2016) were produced and compared to determine changes between the two time periods. Five land-cover categories (terrestrial forest, mangrove forest, peat swamp forest, human settlement, agriculture) were estimated along with land-cover changes. Hot spots of high percentage change for human settlement and agriculture were identified, and vulnerable habitats were mapped including terrestrial forest, mangrove forest and peat swamp forest. Between 1996 and 2016, 22.1% of terrestrial forests, 26.2% of mangrove forests and 55% of peat swamp forests were lost. The losses of these natural habitats were clearly associated with agricultural expansion. Approximately 10.6%, 14.3% and 33% of terrestrial, mangrove and peat swamp forest remaining were identified as highly vulnerable, of which the majority were at the boundaries between natural and human-dominated areas. The technique offers promise for rapidly identifying high priority areas for more detailed analysis and potential conservation interventions.

Native Burmese pythons exhibit site fidelity and preference for aquatic habitats in an agricultural mosaic.

Animal movement and resource use are tightly linked. Investigating these links to understand how animals use space and select habitats is especially relevant in areas affected by habitat fragmentation and agricultural conversion. We set out to explore the space use and habitat selection of Burmese pythons (Python bivittatus) in a heterogenous, agricultural landscape within the Sakaerat Biosphere Reserve, northeast Thailand. We used VHF telemetry to record the daily locations of seven Burmese pythons and created dynamic Brownian Bridge Movement Models to produce occurrence distributions and model movement extent and temporal patterns. To explore relationships between movement and habitat selection we used integrated step selection functions at both the individual and population level. Burmese pythons had a mean 99% occurrence distribution contour of 98.97 ha (range 9.05-285.56 ha). Furthermore, our results indicated that Burmese pythons had low mean individual motion variance, indicating infrequent moves and long periods at a single location. In general, Burmese pythons restricted movement and selected aquatic habitats but did not avoid potentially dangerous land use types like human settlements. Although our sample is small, we suggest that Burmese pythons are capitalizing on human disturbed landscapes.

Loss and vulnerability of lowland forests in mainland Southeast Asia.

Despite containing extraordinary levels of biodiversity, lowland (<200 m asl) tropical forests are extremely threatened globally. Southeast Asia is an area of high species richness and endemicity under considerable anthropogenic threat with, unfortunately, scant focus on its lowland forests. We estimated extent of lowland forest loss from 1998 to 2018, including inside protected areas and determined the vulnerability of this remaining forest. Maximum likelihood classification techniques were used to classify Landsat images to estimate lowland forest cover in 1998 and 2018. We used Bayesian belief networks with 20 variables to evaluate vulnerability of the forest that remained in 2018. Analyses were conducted at two spatial scales: landscape patch (analogous to ecoregion) and country level. Over 20 years, >120,000 km2 of forest (50% of forest present in 1998) was lost. Of the 14 lowland forest patches, 6 lost >50% of their area. At the country scale, Cambodia had the greatest deforestation (>47,500 km2 ). In 2018, 18% of the lowlands were forested, and 20% of these forests had some formal protection. Approximately 50% of the lowland forest inside protected areas (c. 11,000 km2 ) was also lost during the study period. Most lowland forest remaining is highly vulnerable; eight landscape patches had >50% categorized as such. Our results add to a growing body of evidence that the presence of protected areas alone will not prevent further deforestation. We suggest that more collaborative conservation strategies with local communities that accommodate conservation concessions specifically for lowland forests are urgently needed to prevent further destruction of these valuable habitats.

Pérdida y Vulnerabilidad de los Bosques de Tierras Bajas en la Parte Continental del Sudeste Asiático Resumen A pesar de que contienen niveles extraordinarios de biodiversidad, los bosques tropicales de tierras bajas (<200 m snm) se encuentran bajo amenazas extremas en todo el mundo. El sudeste de Asia es un área con una riqueza alta de especies y endemismos bajo amenazas antropogénicas considerables, desafortunadamente, con un enfoque exiguo sobre sus bosques de tierras bajas. Estimamos la extensión de la pérdida de bosques de tierras bajas desde 1998 hasta 2018, incluyendo aquellos bosques que se encuentran dentro de áreas protegidas, y determinamos la vulnerabilidad del bosque que permanece. Usamos técnicas de clasificación de la probabilidad máxima para clasificar imágenes Landsat y así estimar la cobertura de bosque de tierras bajas en 1998 y 2018. Usamos redes de opinión bayesiana con 20 variables para evaluar la vulnerabilidad del bosque que permanecía en pie en 2018. Los análisis fueron realizados a dos escalas espaciales: a nivel de fragmento de paisaje (análogo a la ecorregión) y a nivel de país. A lo largo de 20 años, se perdieron >120,000 km2 de bosque (50% del bosque presente en 1998). De los 14 fragmentos de bosque de tierras bajas, seis perdieron >50% de su área. A la escala de país, Camboya tuvo la mayor deforestación (>47,500 km2 ). En 2018, el 18% de las tierras bajas contaban con bosque y el 20% de estos bosques tenían algún tipo de protección formal. Aproximadamente el 50% del bosque de tierras bajas que se encuentra dentro de áreas protegidas (aprox. 11,000 km2 ) también se perdió durante el periodo de estudio. La mayoría del bosque de tierras bajas que todavía permanece tiene una vulnerabilidad muy alta; ocho de los fragmentos de paisaje tenían >50% categorizado de tal manera. Nuestros resultados se suman a un cuerpo creciente de evidencia de que la sola presencia de las áreas protegidas no va a prevenir una mayor deforestación. Sugerimos que se necesitan urgentemente más estrategias de conservación colaborativa con comunidades locales que acomoden las concesiones de conservación específicamente para los bosques de tierras bajas para prevenir una mayor destrucción de estos hábitats tan valiosos.

COVID-19 Highlights the Need for More Effective Wildlife Trade Legislation.

Zoonosis-based epidemics are inevitable unless we revisit our relationship with the natural world, protect habitats, and regulate wildlife trade, including live animals and non-sustenance products. To prevent future zoonoses, governments must establish effective legislation addressing wildlife trade, protection of habitats, and reduction of the wildlife-livestock-human interface.

Bayesian networks for habitat suitability modeling: a potential tool for conservation planning with scarce resources.

Bayesian networks (BN) have been increasingly used for habitat suitability modeling of threatened species due to their potential to construct robust models with limited survey data. However, previous applications of this approach have only occurred in countries where human and budget resources are highly available, but the highest concentrations of threatened vertebrates globally are located in the tropics where resources are much more limited. We assessed the effectiveness of Bayesian networks in generating habitat suitability models in Thailand, a biodiversity-rich country where the knowledge base is typically sparse for a wide range of threatened species. The Bayesian network approach was used to generate habitat suitability maps for 52 threatened vertebrate species in Thailand, using a range of evidence types, from relatively well-documented species with good local knowledge to poorly documented species, with few local experts. Published information and expert knowledge were used to define habitat requirements. Focal species were categorized into 22 groups based on known habitat preferences, and then habitat suitability models were constructed with outcomes represented spatially. Models had a consistent structure with three major components: potential habitat, known range, and threat level. Model classification sensitivity was tested using presence-only field data for 21 species. Habitat models for 12 species were relatively sensitive (>70% congruency between observed and predicted locations), three were moderately congruent, and six were poor. Classification sensitivity tended to be high for bird models and moderate for mammals, whereas sensitivity for reptiles was low, presumably reflecting the relatively poor knowledge base for reptiles in the region. Bayesian network models show significant potential for biodiversity-rich regions with scarce resources, although they require further refinement and testing. It is possible that one detailed ecological study is sufficient to develop a model with reasonable sensitivity, but BN models for species groups with no quantitative data continue to be problematic.

Positive relationships between association strength and phenotypic similarity characterize the assembly of mixed-species bird flocks worldwide.

Competition theory predicts that local communities should consist of species that are more dissimilar than expected by chance. We find a strikingly different pattern in a multicontinent data set (55 presence-absence matrices from 24 locations) on the composition of mixed-species bird flocks, which are important subunits of local bird communities the world over. By using null models and randomization tests followed by meta-analysis, we find the association strengths of species in flocks to be strongly related to similarity in body size and foraging behavior and higher for congeneric compared with noncongeneric species pairs. Given the local spatial scales of our individual analyses, differences in the habitat preferences of species are unlikely to have caused these association patterns; the patterns observed are most likely the outcome of species interactions. Extending group-living and social-information-use theory to a heterospecific context, we discuss potential behavioral mechanisms that lead to positive interactions among similar species in flocks, as well as ways in which competition costs are reduced. Our findings highlight the need to consider positive interactions along with competition when seeking to explain community assembly.

Plant-frugivore interactions in an intact tropical forest in north-east Thailand.

Fleshy-fruited plants in tropical forests largely rely on vertebrate frugivores to disperse their seeds. Although this plant-animal interaction is typically considered a diffuse mutualism, it is fundamental as it provides the template on which tropical forest communities are structured. We applied a mutualistic network approach to investigate the relationship between small-fruited fleshy plant species and the fruit-eating bird community in an intact evergreen forest in northeast Thailand. A minimum of 53 bird species consumed fruits of 136 plant species. Plant-avian frugivore networks were highly asymmetrical, with observed networks filling 30% of all potential links. Whereas some of the missing links in the present study might be due to undersampling, forbidden links can be attributed to size constraints, accessibility and phenological uncoupling, and although the majority of missing links were unknown (58.2%), many were probably due to a given bird species being either rare or only a very occasional fruit eater. The most common frugivores were bulbuls, barbets and fairy-bluebirds, which were responsible for the majority of fruit removal from small fleshy fruited species in our system. Migratory birds seemed to be a minor component of the plant-frugivore networks, accounting for only 3% of feeding visits to fruiting trees; they filled 2% of the overall potential networks. The majority of interactions were generalized unspecific; however, Saurauia roxburghii Wall. appeared to be dependent on flowerpeckers for dispersal, while Thick-billed Pigeons were only seen to eat figs.

Assessment of indirect pesticide effects on worm-eating warbler populations in a managed forest ecosystem.

Ecological risk assessments rarely evaluate indirect pesticide effects. Pesticides causing no direct mortality in wildlife can still reduce prey availability, resulting in a lower reproductive rate or poor juvenile condition. Few studies have examined these consequences at the population level. We use a four-year data set from a forest ecosystem in which Bacillus thuringiensis kurstaki (Btk) was applied to control gypsy moths (Lymantria dispar L.). Lower worm-eating warbler (Helmitheros vermivorus) productivity on Btk plots contributed to an intrinsic growth rate <1. Altered provisioning behavior by adults led to lower nestling mass in Btk-treated plots, and simulations of reduced juvenile survival expected as a result further reduced population growth rate. The present study explored different spatial representations of treated areas, using a two-patch matrix model incorporating dispersal. Minimal migration from areas with increasing subpopulations could compensate for detrimental reductions in reproductive success and juvenile survival within treated subpopulations. We also simulated population dynamics with different proportions of treated areas to inform management strategies in similar systems. Nontoxic insecticides are capable of impacting nontarget populations with consistent, long-term use and should be evaluated based on the spatial connectivity representative of habitat availability and the time period appropriate for risk assessment of pesticide effects in wildlife populations.

Selection of sleeping trees in pileated gibbons (Hylobates pileatus).

Selection and use patterns of sleeping sites in nonhuman primates are suggested to have multiple functions, such as predation avoidance, but they might be further affected by range defense as well as foraging constraints or other factors. Here, we investigate sleeping tree selection by the male and female members of one group of pileated gibbons (Hylobates pileatus) at Khao Ang Rue Nai Wildlife Sanctuary, Thailand. Data were collected on 113 nights, between September 2006 and January 2009, yielding data on 201 sleeping tree choices (107 by the female and 94 by the male) and on the characteristics of 71 individual sleeping trees. Each sleeping tree and all trees > or =40 cm diameter at breast height (DBH) in the home range were assessed (height, DBH, canopy structure, liana load) and mapped using a GPS. The gibbons preferentially selected tall (mean=38.5 m), emergent trees without lianas. The majority of the sleeping trees (53.5%) were used only once and consecutive reuse was rare (9.5%). Sleeping trees were closer to the last feeding tree of the evening than to the first feeding tree in the morning, and sleeping trees were located in the overlap areas with neighbors less often than expected based on time spent in these areas. These results suggest avoidance of predators as the main factor influencing sleeping tree selection in pileated gibbons. However, other non-mutually exclusive factors may be involved as well.

In search of cyclooxygenase inhibitors, anti-Mycobacterium tuberculosis and anti-malarial drugs from Thai flora and microbes.

Malaria continues to be a major infectious disease of the developing world and the problem is compounded not only by the emergence of drug resistant strains but also from a lack of a vaccine. The situation for tuberculosis (TB) infection is equally problematic. Once considered a "treatable" disease for which eradication was predicted, TB has re-emerged as highly lethal, multi-drug resistant strains after the outbreak of AIDS. Worldwide, the disease causes millions of deaths annually. Similarly, treatments for chronic inflammatory diseases such as arthritis have been impeded due to the potentially lethal side effects of the new and widely prescribed non-steroidal anti-inflammatory compounds. Thais have utilized bioresources from plants and some microorganisms for medicine for thousands of years. Because of the need for new drugs to fight malaria and TB, with radically different chemical structures and mode of actions other than existing drugs, efforts have been directed towards searching for new drugs from bioresources. This is also true for anti-inflammatories. Although Thailand is considered species-rich, only a small number of potential bioresources has been investigated. This article briefly describes the pathogenesis of 2 infectious diseases, malaria and TB, and modern medicines employed in chemotherapy. Diversities of Thai flora and fungi and their chemical constituents with antagonistic properties against these 2 diseases are described in detail. Similarly, anti-inflammatory compounds, mostly cyclooxygenase (COX) inhibitors, are also described herein to demonstrate the potential of Thai bioresources to provide a wide array of compounds for treatment of diseases of a different nature.