Fine-Scale Evaluation of Giant Panda Habitats and Countermeasures
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sustainability Article Fine-Scale Evaluation of Giant Panda Habitats and Countermeasures against the Future Impacts of Climate Change and Human Disturbance (2015–2050): A Case Study in Ya’an, China Jing Zhen 1,2, Xinyuan Wang 1, Qingkai Meng 3, Jingwei Song 4, Ying Liao 5, Bo Xiang 1, Huadong Guo 1, Chuansheng Liu 1, Ruixia Yang 1 and Lei Luo 1,* 1 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; [email protected] (J.Z.); [email protected] (X.W.); [email protected] (B.X.); [email protected] (H.G.); [email protected] (C.L.); [email protected] (R.Y.) 2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China 3 State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China; [email protected] 4 Centre for Autonomous Systems, University of Technology Sydney, Ultimo, NSW 2007, Australia; [email protected] 5 Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; [email protected] * Correspondence: [email protected]; Tel.: +86-10-8217-8128 Received: 22 March 2018; Accepted: 3 April 2018; Published: 4 April 2018 Abstract: The accelerating impact of climate change on giant panda (Ailuropoda melanoleuca) habitats have become an international research topic. Recently, many studies have also focused on medium-sized mountain ranges or entire giant panda habitats to predict how habitats will change as the climate warms, but few say in detail what to do or where to focus efforts. To fill this gap, this paper presents a new method to take comprehensive, fine-scale evaluations incorporating climate change, human disturbance, and current conservation networks and translate them into practical countermeasures in order to help decision-makers set priority regions for conservation. This study looked at the core area of the Sichuan Giant Panda Sanctuaries United Nations Educational, Scientific and Cultural Organisation (UNESCO) World Natural Heritage site, namely Ya’an Prefecture, as a case study. The research employs the Maximum Entropy (MaxEnt) modeling algorithm to analyze how climate change will affect the habitats by 2050 under two scenarios: only considering the influence of climate change, and thinking about the coupled influence of climate change and human disturbance together. The results showed the following: (1) only considering climate change, the overall habitat that can be used by giant pandas in this region will increase, which differs from most of the previous results showing a decrease; (2) the new suitable habitat will shift westward, northward and eastward in this region; (3) conversely, the suitable habitat will be significantly reduced (about 58.56%) and fragmentized when taking into account human disturbance factors; (4) at present, the three small nature reserves are far from each other and cannot cover the present habitat well nor protect the potentially suitable habitats. Based on the comprehensive analysis of habitat shifts and our two field investigations, we suggest two regions that can be expanded into the conservation network to contain more potentially suitable habitats in the future. Furthermore, we used a geographical information system to incorporate high-resolution remote-sensing images from the GF-1 satellite, land-cover maps, and a digital elevation model (DEM) to verify the possibility of our two suggested regions. Keywords: climate change; habitat evaluation; MaxEnt; geographic information system; giant panda; species distribution modeling Sustainability 2018, 10, 1081; doi:10.3390/su10041081 www.mdpi.com/journal/sustainability Sustainability 2018, 10, 1081 2 of 19 1. Introduction Rapid climate change is threatening global ecosystems and biodiversity by affecting certain species and the surrounding environments they depend on [1–3]. Climate change together with other stressors adversely affects habitats which, in turn, can lead to changes in species distribution, community composition, phenology and ecosystem functions [4,5], particularly for species characterized by a limited habitat, small population, low reproductivity, and weak migration ability. These species have poor tolerance to environmental changes and face the risk of extinction [6,7]. Unfortunately, it has been reported that the risk of extinction will be accelerated by future global warming. It was estimated that, in the current situation, one in four mammalian species are threatened with extinction and one in two is declining globally [8]. The giant panda (Ailuropoda melanoleuca) is one of the most widely recognized threatened mammals and was categorized as Endangered on the International Union for Conservation of Nature (IUCN) Red List in 1988 [9,10]. The species was once widespread throughout southern China, as far north as Beijing and south into south-east Asia during the 16th to 19th centuries, but in the past several hundred years the population and distribution range have both decreased dramatically due to the combined adverse effects of climate change, geological vicissitudes and human activities [11]. The rapid growth of the human population and climate warming over the past 300 years have resulted in much of the under-forest bamboo, which is the panda’s principal source of food, being replaced by farmland. Consequently, the giant panda is now confined to six isolated mountains located in Sichuan, Shaanxi and Gansu provinces in south-central China [12,13]. High mountain ecosystems are considered to react sensitively to climate warming and express profound impacts [14,15]. In addition, the living situation of the giant panda became even worse because of its biological constraints, including dietary specialization (99% of the food comes from bamboo) [16], low reproductive rates, and restricted gene flow [17]. At the same time, habitat fragmentation has worsened. For example, giant panda populations were divided into about 24 local populations in the early 1990s [18], but now this number has increased to 33, of which 24 face a high risk of extinction (including 233 giant pandas, accounting for about 12% of the total population) [19,20]. Furthermore, it has long been recognized that despite the slow and gradual climate variability, rapid climate changes might be expected, since the climate system is in an unstable equilibrium. In this context, Varotsos et al. (2014) found that the increase in sea-surface temperature over 30◦ S–60◦ N from 1900 to 2012 did not occur slowly and gradually, but abruptly in 1925/1926 and 1987/1988 with events time-separated by 62 years, i.e., an interval reminiscent of the well-established quasi 60-year natural cycle [21]. Evidence for the quasi 60-year oscillation has also been found by Zhen-Shan and Xian (2007) and has been shown to be among the most prominent climate variability components of the annual mean temperature in China, the Northern Hemisphere, and globally in the period from 1881 to 2002 [22]. Meanwhile, under-forest bamboo, the main food for giant pandas, has also shown a reproduction cycle of 50–100 years through mass flowering. For example, the Fargesia spathacea mass flowering from 1975–1976 in Minshan Mountain caused the death of nearly 150 giant pandas [23]. All these factors mean the giant panda faces severe challenges to its survival. Detailed and reliable information about the adverse effect of future climate change on giant panda habitats is necessary and urgent. Therefore, the responses of habitats to climate change attract substantial attention from researchers. However, most efforts are at medium or large scales. e.g., the studies have focused on the whole distribution range [24,25] or on mountain ranges, such as the Qinling Mountains [26–28], the Minshan Mountains [16,29] and the Daxiangling Mountains [30]. This is problematic because the results are difficult to translate into viable decisions. In addition, previous studies have often predicted the direction of habitat shifts in the context of a changing climate, and calculated the change rate [7,27]. However, there is a lack of work focusing on local regions putting forward possible specific measures based on current protection networks, which is among the most compelling challenges to conservation efforts in protecting species’ persistence [16]. At the same time, data in previous studies associating the giant panda’s presence with environmental issues have often Sustainability 2018, 10, 1081 3 of 19 been based on the results of the Third National Giant Panda Survey (1999–2003), which was completed more than 10 years ago and needs to be updated with the most recent survey data. To address these issues and, considering our group’s previous research work [31], we chose the case study of the giant panda in the core area of the Sichuan Giant Panda Sanctuaries United Nations Educational, Scientific and Cultural Organisation (UNESCO) World Natural Heritage site, in Ya’an Prefecture located in the middle of Sichuan Province, China. We used a maximum entropy (MaxEnt) model together with the latest ground survey data, i.e., the Fourth National Giant Panda Survey (2011–2014) and the most recent Intergovernmental Panel on Climate Change–Coupled Model Intercomparison Project Phase 5 (IPCC–CMIP5) climate scenarios to forecast the probability of changes in the distribution and quality of giant panda habitats by 2050. Shifting geographic ranges are likely to have profound consequences for the effectiveness of the protected area networks. Therefore, we also incorporated the distribution shift’s results with the current conservation network to clarify key areas and strategies for future conservation planning. Through this new analytical method, we aimed to provide a reference for conservation management of this species. Meanwhile, we expect this approach to be promising in predicting the potential distribution of other similar species confined elsewhere in fringe ecological patches. 2. Study Area Ya’an is regarded as the “hometown of giant pandas” because this is where the first giant panda was found by French Jesuit Armand David in 1869 [32].