Recovery of Logged Tropical Montane Rainforests as Potential Habitats for Hainan Gibbon

As the world’s rarest ape, the main threat facing Hainan gibbon (Nomascus hainanus) is habitat degradation and loss caused by human disturbances. The insufficient area and continuous human disturbance in most of the existing habitats can hardly maintain the future recovery and development of the gibbon population. A large area of secondary tropical montane rainforest in recovery was retained in Bawangling National Nature Reserve after disturbance. Therefore, it is of great significance to study the recovery of these secondary forests for the protection and restoration of Hainan gibbon habitat. To explore the recovery of secondary tropical rainforests after different disturbances, and whether they have the potential to serve as the future habitats for Hainan gibbon, we calculated four dynamic indexes (including recruitment rate, mortality/loss rate, relative growth rate and turnover rate) of abundance and basal area for the total community and for food plants of Hainan gibbon based on data from two censuses of secondary forests recovered nearly 45 years after different disturbances (clear-cutting and selective-logging) and old-growth forest of tropical montane rainforest. The results are as follows: (1) There were no significant differences in recruitment rates, mortality rates and turnover rates of abundance and basal area between recovered clear-cutting forests, selectively logged forests and old-growth forests. (2) Abundance, basal area and species of small (1 < DBH ≤ 10 cm) and medium (10 ≤ DBH < 30 cm) food plants in the two disturbed forests were higher, while those of large food plants (DBH ≥ 30 cm) in the two forests were lower than in old-growth forests. (3) For the common food species occurring in all three kinds of communities, the relative growth rate of most small trees in clear-cutting forest was higher than that of old-growth forest. Our research demonstrates that the lack of large food plants is the key limiting factor for the development of the secondary mountain rainforest as habitats for Hainan gibbon at present. However, it has great potential to transform into suitable habitats through targeted restoration and management due to the high recruitment rate and relative growth rate of the small- and medium-sized food plants.

Assessing the effectiveness of public awareness-raising initiatives for the Hainan gibbon Nomascus hainanus

Many protected areas conduct awareness-raising activities to increase local knowledge and support conservation programmes, but the effectiveness of such activities is rarely assessed. Public awareness-raising has been carried out since the early 2000s around Bawangling National Nature Reserve, Hainan, China, to improve conservation knowledge about the Critically Endangered Hainan gibbon Nomascus hainanus, one of the rarest mammals. We conducted 207 interviews in 25 villages around Bawangling National Nature Reserve to evaluate the outcome of previous conservation education, through comparison of variation in local respondent knowledge and attitudes, and specific enquiries about sources of knowledge acquisition. Likelihood of accurate responses to most of our questions regarding the species was positively correlated with local exposure to gibbon-themed billboards and murals, and respondents exhibited greater knowledge about several key conservation indices for gibbons compared to their knowledge about sympatrically occurring rhesus macaques Macaca mulatta. Many respondents specifically reported they knew about local existence, population size, conservation status, and threats to gibbons from past awareness-raising activities, with village education sessions and billboards widely identified as key sources of information. However, other known awareness-raising approaches have had little detectable effect on shaping local conservation awareness. Although educational activities have improved awareness about gibbons and their conservation requirements in relative terms, overall levels of knowledge remain low in many important areas and ongoing improvement of local awareness is still needed, in particular around poorly-understood topics such as gibbon conservation status, rarity and threats, and for socio-demographic groups possessing less conservation knowledge.

The Genetic Status of the Critically Endangered Hainan Gibbon (Nomascus hainanus): A Species Moving Toward Extinction

The Hainan gibbon (Nomascus hainanus), once widespread across Hainan, China, is now found only in the Bawangling National Nature Reserve. With a remaining population size of 33 individuals, it is the world’s rarest primate. Habitat loss and fragmentation are the primary drivers of Hainan gibbon population decline. In this study, we integrated data based on field investigations and genotype analyses of 10 microsatellite loci (from fecal samples) to assess genetic diversity in this Critically Endangered primate species. We found that the genetic diversity of the Hainan gibbon is extremely low, with 7 of 8 microsatellite loci exhibiting decreased diversity. Additional molecular analyses are consistent with field observations indicating that individuals in groups A, B, and C are closely related, the female–male sex ratios of the offspring deviates significantly from 1:1, and the world’s remaining Hainan gibbon population is expected to experience continued high levels of inbreeding in the future. Given extensive habitat loss (99.9% of its natural range has been deforested) and fragmentation, this rarest ape species faces impending extinction unless corrective measures are implemented immediately.

First use of artificial canopy bridge by the world’s most critically endangered primate the Hainan gibbon Nomascus hainanus

All gibbon species (Primates: Hylobatidae) are facing high extinction risk due to habitat loss and hunting. The Hainan gibbon Nomascus hainanus is the world’s most critically endangered primate, and one of the priority conservation actions identified is to establish artificial canopy corridors to reconnect fragmented forests. The effectiveness of artificial canopy bridge as a conservation tool for wild gibbons has not been widely tested, and the results are rarely published. We constructed the first canopy bridge for Hainan gibbon in 2015 to facilitate passage at a natural landslide; mountaineering-grade ropes were tied to sturdy trees with the help of professional tree climbers and a camera trap was installed to monitor wildlife usage. Hainan gibbon started using the rope bridge after 176 days, and usage frequency increased with time. All members in the gibbon group crossed the 15.8 m rope bridge except adult male. Climbing was the predominant locomotor mode followed by brachiation. This study highlights the use and value of rope bridges to connect forest gaps for wild gibbons living in fragmented forests. While restoring natural forest corridors should be a priority conservation intervention, artificial canopy bridges may be a useful short-term solution.

Automated detection of Hainan gibbon calls for passive acoustic monitoring

1AbstractExtracting species calls from passive acoustic recordings is a common preliminary step to ecological analysis. For many species, particularly those occupying noisy, acoustically variable habitats, the call extraction process continues to be largely manual, a time-consuming and increasingly unsustainable process. Deep neural networks have been shown to offer excellent performance across a range of acoustic classification applications, but are relatively underused in ecology.We describe the steps involved in developing an automated classifier for a passive acoustic monitoring project, using the identification of calls of the Hainan gibbon (Nomascus hainanus), one of the world’s rarest mammal species, as a case study. This includes preprocessing - selecting a temporal resolution, windowing and annotation; data augmentation; processing - choosing and fitting appropriate neural network models; and postprocessing - linking model predictions to replace, or more likely facilitate, manual labelling.Our best model converted acoustic recordings into spectrogram images on the mel frequency scale, using these to train a convolutional neural network. Model predictions were highly accurate, with per-second false positive and false negative rates of 1.5% and 22.3%. Nearly all false negatives were at the fringes of calls, adjacent to segments where the call was correctly identified, so that very few calls were missed altogether. A postprocessing step identifying intervals of repeated calling reduced an eight-hour recording to, on average, 22 minutes for manual processing, and did not miss any calling bouts over 72 hours of test recordings. Gibbon calling bouts were detected regularly in multi-month recordings from all selected survey points within Bawangling National Nature Reserve, Hainan.We demonstrate that passive acoustic monitoring incorporating an automated classifier represents an effective tool for remote detection of one of the world’s rarest and most threatened species. Our study highlights the viability of using neural networks to automate or greatly assist the manual labelling of data collected by passive acoustic monitoring projects. We emphasise that model development and implementation be informed and guided by ecological objectives, and increase accessibility of these tools with a series of notebooks that allow users to build and deploy their own acoustic classifiers.