SDG15: Life on Land

Assessment of giant panda habitat fragmentation(2019)

Scale: Local
Study area: Giant Panda Habitat, China
The fourth national giant panda survey report indicates that China has 1,864 wild giant pandas (Ailuropoda melanoleuca). The adult giant panda populations have increased since past surveys. As a result, the IUCN downgraded the status of the giant panda from “endangered” to “vulnerable” in 2016. However, many domestic and foreign conservationists have doubts about the validity of this downgradation. Currently, the determination of whether a species is endangered depends on its population size but neglects changes in habitat quality and quantity.
Target 15.5: By 2020, take urgent action to reduce the degradation of natural habitats, halt the loss of biodiversity, and protect and prevent the extinction of threatened species.

Indicator 15.5.1: Red List Index.

Data collection methods, analyses, and the sample area for the four national giant panda surveys are inconsistent, which makes comparisons difficult. This method attempts to provide comparable estimates for different surveys by using the same geographical area. The area contains 56 counties in Sichuan, Shaanxi, and Gansu provinces. The method is consistent for habitat extent and quality determination in conjunction with years of field investigations, and GIS and remote sensing data. This method is intended to produce a comprehensive analysis of giant panda habitats.
The giant panda habitats were evaluated using a model that combines elevation, slope, and forest cover. Elevation and slope data were obtained from a DEM with a 90-meter pixel resolution. Forest cover was assessed using 52 Landsat MSS/ TM images from the CAS scientific database (http:// www.csdb. cn/) and the China Remote Sensing Satellite Ground Station.
The fragmentation of panda habitats was evaluated using Fragstats 3.3 to estimate the number of isolated habitat units and the mean patch size. The number of isolated habitat units reflects the integrated effects of isolation by natural processes and human activities. The panda habitats were overlaid with isolation factors (e.g., major rivers, permanent snow cover, and major roads) to analyze the variation for habitat isolation in different periods. These factors represent major barriers to panda migration.
Several metrics were used to assess the effects of different biophysical and socioeconomic drivers. These include wetness indexes, elevation, human population, road density, and the number of nature reserves at the county level. These variables were then used to develop multiple general linear regression models to analyze the contribution of relevant factors.
Data used in this case

The remote sensing dataset consisted of Landsat MSS/TM images from 1976, 1988, 2001, and 2013. Other data included DEM data from SRTM, river data from the national geographic information center, road data from the transportation department, population data, economic data, and nature reserve boundary data.
Results and Analysis

Results from the assessment of giant panda habitats revealed that the habitat area had increased by 0.4% between 2001 and 2013. Moreover, the mean patch size of each habitat also increased by 1.8%, despite the devastating 2008 Wenchuan earthquake. This indicates that the implementation of ecological protection and restoration projects had resulted in an increase in giant panda habitat area since 2001 (Figure 1). These projects included the construction of nature reserves, natural forest conservation programs, and the Grain-to-Green program.
Figure1. Change in giant panda habitats between 1976 and 2013.
Figure 2. Change in road networks and panda habitat areas from 2001 to 2013.
However, the past 40 years have witnessed long-term commercial logging, rapid road construction, and natural disasters such as earthquakes and debris flows. Consequently, panda habitats have shrunk in area and become more fragmented in 2013 than when the giant pandas were still listed as endangered in 1976 and 1988. The amount of isolated panda habitats in 2013 was three times higher than in 1976 (Figure 2), implying that communication barriers between panda populations have greatly increased.
Research suggests that the downgradation of giant pandas from endangered to vulnerable is reasonable in terms of population size. However, this change is not valid in terms of habitat change. Giant panda habitats may have increased in size since 2001. However, these habitats shrank and were more fragmented in 2013 than in 1988 when the species was listed as endangered. Currently, giant pandas are still facing many threats and challenges, and the downgradation is unreasonable. Future assessment of a species' endangered level should consider both their population and habitat.
 Figure 3. Panda habitat in Sichuan Wolong Nature Reserve.


Although the panda population increased from 1976 to 2013, the habitat area was observed to be smaller and more fragmented in 2013 than in 1988. It is unreasonable to reduce the panda's status from endangered to vulnerable solely based on the population. An assessment of a species1 endangered level requires considering both their population and habitat.


The method presented in this case enables a more reasonable evaluation of panda habitat dynamics, and provides a powerful tool and data support for future conservation work.
This case approach can be applied to assess the habitats of other endangered species around the world, and analyze fragmentation status and other influential factors. Furthermore, this case study supports the implementation of SDG 15.5, which represents the need to “take urgent action to reduce the degradation of natural habitats, halt the loss of biodiversity, and protect and prevent the extinction of threatened species by 2020”.


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