Laboratory of Animal Behaviour and Conservation

About the lab

Welcome to the Laboratory of Animal Behaviour and Conservation at Nanjing Forestry University. Here, we primarily focus on animal behaviour and the conservation of species in general.

For updates on life in the lab, please head this way:

Featured research (108)

Undocumented species represent one of the largest hurdles for conservation efforts due to the uncertainty they introduce into conservation planning. Until the distribution of earth's biodiversity is better understood, substantial conjecture will continue to be required for protecting species from anthropogenic extinction. Therefore, we developed a novel approach for identifying regions with promising biodiscovery prospects, linked to integrative conservation priorities, which we illustrate using amphibians. Our approach builds on previous estimates of biodiscovery priorities by simultaneously (1) considering linkages between spatio-environmental variables and biodiversity, (2) accounting for the negative relationship between past sampling intensity and future biodiscovery potential, (3) incorporating a priori knowledge about global species distribution patterns, (4) addressing spatial autocorrelation in community composition, and (5) weighting theoretical undocumented species by their predicted levels of conservation need. Using boosted regression trees and 50km^2 map pixels spread across the global range of amphibians, we identified several regions likely to contain many undocumented amphibian species and conservation needs, including the Southeast Asian Archipelago, humid portions of sub-Saharan Africa, and undersampled portions of the Amazon, Andes Mountains, and Central America. We also ranked top-scoring ecoregions by their mean and maximum biodiscovery potential and found that the top-20 ranked ecoregions were most concentrated in the Southeast Asian Archipelago and tropical Africa for undocumented species richness, and in tropical Africa and tropical South America for integrative undocumented amphibian conservation needs. However, high-scoring pixels tended to be widely distributed across different ecoregions for both biodiscovery scoring approaches.
Species distribution modeling is an essential tool for understanding the ecology of species and has many applications in conservation. Using maximum entropy (MaxEnt) modeling, we identify the key factors shaping the potential distribution of the endangered Javan Gibbons Hylobates moloch in one of the main remnant habitats, Gunung Halimun Salak National Park (GHSNP), Indonesia, using presence-only data collected between October and November 2015, and in April and May 2016. Maxent results showed that forest canopy density and annual temperature were the principal variables predicting the distribution of Javan Gibbons, with contribution scores of 53.9% and 35.6%, respectively. The predictive distribution map indicated that suitable habitat for Javan Gibbons is not uniformly distributed within GHSNP, i.e., suitable habitat is not located evenly throughout the region, with some areas more suitable than others. Highly suitable habitat comprises the largest proportion of habitat, with 42.1% of GHSNP classified as highly suitable habitat, whereas 24.7% was moderately suitable, and 33.2% of habitat was of low suitability for Javan Gibbons. Priority should be given to increasing habitat quality in degraded areas and law enforcement patrols to reduce degradation in peripheral regions of the park as part of the conservation management strategy.
Biodiversity is declining at a record rate. Unfortunately, attitudes favoring non-advocacy remain prevalent in conservation science. Despite our detailed knowledge of biodiversity losses, we, the conservation science community as a whole, are failing to reverse species declines, transforming us into mere accountants of extinction. Conservation scientists frequently miss the opportunity to utilize scientific knowledge for helping reverse species’ declines by not comprehensively or effectively engaging policymakers with conservation-related recommendations. The lack of translation of conservation science into policies therefore represents a detrimental blind spot of conservation biologists. Perhaps older generations had an excuse to practice conservation science without advocating for specific conservation policies, but the urgency of ongoing drastic biodiversity losses make unengaged approaches unacceptable for modern conservation biologists and tantamount to an implicit acceptance of anthropogenic mass extinction.
Ecological models including population viability analyses (PVAs) can help predict the trajectory of populations, a useful tool for threatened species. Here, we integrate PVAs and habitat suitability models to suggest protected areas for two threatened treefrog species endemic to the Korean Peninsula, Dryophytes suweonensis and Dryophytes flaviventris. We used an integrated modelling approach combining ecological niche, connectivity, and PVAs in Vortex to determine the likelihood of extinction of each species. We relied on two scenarios, a baseline “no management” approach, and a protected area designation scenario (“active management”). The latter scenario was simulated by halting future degradation to sites, and reduction in carrying capacity, through the designation of protected areas; mitigating the effects of drought to decrease the effects of climate change; and controlling invasive predator populations and raising tadpoles ex-situ to reduce mortality rates. In addition, we used a stepwise approach to determine the designation priority of individual patches. Under the current “no management” approach, the resulting effective metapopulations after 100 years were between 160 and 170 individuals for both species, with an 86.5% extinction probability for D. suweonensis and a 90.3% extinction probability for D. flaviventris. Under “active management” for each site separately, the extinction probability was 0% for both species with significantly increased metapopulation sizes, ca. 15,910 individuals for D. suweonensis, and ca. 4,400 individuals for D. flaviventris. Determining the designation priority of sites and the type of management needed can inform regulatory bodies on which area to protect. Without intervention, these species are facing extinction. PUBLICATION AVAILABLE HERE:
Inhibitory control is a complex cognition which includes complex motor reflexes. It is necessary for the survival of an individual as it influences ecologically relevant tasks such as foraging and predator evading. Studies exploring such complex cognition are restricted chiefly to adult life history stages as previous experience influences developing motor reflexes. However, in early life history stages animals do encounter situations where complex motor reflexes are required. One such problem is when a direct path leading to food is blocked and individuals have to detour, which requires inhibitory complex, working memory, route planning and object permanence. This is the first study to look at complex cognition in larvae of Salamanders who successfully make detours to acquire a goal.

Lab head

Amaël Borzée
  • College of Biology and the Environment
About Amaël Borzée
  • I’m leading the Laboratory of Animal Behaviour and Conservation, where we focus on a broad range of species and systems. Projects were so far focused on the behavioural ecology and conservation of amphibians in East Asia (with a personal preference for treefrogs), but this is changing and you are welcome to inquire, maintaining a focus on northeast Asia. I am also Co-Chair for the IUCN SSC Amphibian Specialist Group.

Members (8)

Yucheol Shin
  • Kangwon National University
Yoonjung Yi
  • Nanjing Forestry University
Yoon Hyuk Bae
  • Nanjing Forestry University
Siti N. Othman
  • Nanjing Forestry University
Vishal Kumar Prasad
  • Laboratory of Animal Behaviour and Conservation
Marjan Maria
  • Jagannath University - Bangladesh
Deyatima Ghosh
  • Nanjing Forestry University
Hina Amin
  • Nanjing Forestry University
Lab Member
Lab Member
  • Not confirmed yet

Alumni (3)

Johanna Ambu
  • Nanjing Forestry University
Hassan Al-Razi
  • University of Western Australia
Tusnuva Jahan
  • École d’Ingénieurs de PURPAN