Shiqiang Zhou

Distribution of Economic Benefits from Ecotourism: A Case Study of Wolong Nature Reserve for Giant Pandas in China

Ecotourism is widely promoted as a conservation tool and actively practiced in protected areas worldwide. Theoretically, support for conservation from the various types of stakeholder inside and outside protected areas is maximized if stakeholders benefit proportionally to the opportunity costs they bear. The disproportional benefit distribution among stakeholders can erode their support for or lead to the failure of ecotourism and conservation. Using Wolong Nature Reserve for Giant Pandas (China) as an example, we demonstrate two types of uneven distribution of economic benefits among four major groups of stakeholders. First, a significant inequality exists between the local rural residents and the other types of stakeholder. The rural residents are the primary bearers of the cost of conservation, but the majority of economic benefits (investment, employment, and goods) in three key ecotourism sectors (infrastructural construction, hotels/restaurants, and souvenir sales) go to other stakeholders. Second, results show that the distribution of economic benefits is unequal among the rural residents inside the reserve. Most rural households that benefit from ecotourism are located near the main road and potentially have less impact on panda habitat than households far from the road and closer to panda habitats. This distribution gap is likely to discourage conservation support from the latter households, whose activities are the main forces degrading panda habitats. We suggest that the unequal distribution of the benefits from ecotourism can be lessened by enhancing local participation, increasing the use of local goods, and encouraging relocation of rural households closer to ecotourism facilities.

Simulating demographic and socioeconomic processes on household level and implications for giant panda habitats

Human activities have significantly affected wildlife habitats. Although the ecological effects of human impacts have been demonstrated in many studies, the socioeconomic drivers underlying these human impacts have seldom been studied. We developed a household-based, stochastic, and dynamic model that simulates the impacts of household demographic and socioeconomic interactions on fuelwood use, a key factor affecting the quantity and quality of habitats for the giant pandas (Ailuropoda melanoleuca). Using Wolong Nature Reserve (China) as a case study, this model mimics household production and consumption processes and integrates various demographic and socioeconomic factors. Household interviews conducted in 1998 within the Reserve provided the data for parameterization. The simulation results fit well with both the data used in constructing the model and with a set of independent data. Age structure and cropland area were found to be the most sensitive factors in terms of fuelwood consumption, and thus deserve more attention in panda habitat conservation. This model could help reserve managers to understand the interrelationships among local economy, local cultural traditions, and habitat degradation, facilitating more scientific and economically efficient policymaking.

A synthesis of giant panda habitat selection

Abstract The giant panda (Ailuropoda melanoleuca) is a global conservation icon, but its habitat selection patterns are poorly understood. We synthesized previous studies on giant panda habitat selection. We confirmed that pandas generally selected forests with moderate to high bamboo densities, mid-elevations, both primary and secondary forests, and areas more distant from human activities. Pandas did not select steep slopes. We also highlighted the interactive effects among different habitat components, such as weaker selection for gentle slope and large patch size in disturbed secondary forests compared with primary forests. Pandas selected for land cover and disturbance at the level of the geographic range and selected for variables such as slope and bamboo density at the level of the home range. Furthermore, selection for higher bamboo cover did not change with bamboo availability, but selection against secondary forest declined as availability of this forest type increased. Our results have implications for the conservation of pandas, particularly the need for inclusion of areas previously seen as less suitable (e.g., moderate slopes and secondary forest) in protected area and habitat restoration planning.

Space use by endangered giant pandas

Studies on animal space use can reveal insights into how animals interact with one another and their environment. Research on the space use patterns of the endangered giant panda (Ailuropoda melanoleuca) in China has nevertheless lagged behind that of many other species, as a government moratorium prevented telemetry data collection on pandas from 1995 to 2006. We studied 5 giant pandas using GPS telemetry and estimated home ranges, core areas, and space use using model-based approaches. Home range 95% area was 6 km2 for the single male studied and averaged 4.4 ± 1.2 (± SD) km2 for the 4 females. Pandas occupied several small core areas that they revisited after time lags of up to several months. Pandas also displayed significant space use interactions, especially among the male and 2 different females across several weeks during a fall season, a time of year not previously thought to involve extensive inter-panda interaction.

Beyond population size: Examining intricate interactions among population structure, land use, and environment in wolong nature reserve, China

Land use decisions by farming families provide a key context for examining the dynamic interactions between people and the environment and are at the core of our research project in the Amazon Basin. Throughout our work in this area, we have focused on the decision-making processes of farm households, how these processes affect land use, and then on how the changes in land use (a social concept) are linked to changes in land cover (an environmental concept). When we began our research in this area, studies examining the causes of deforestation often neglected the dynamic interactions between the human population and the environment, and few studies had paid attention to the role of micro-level decision-making processes, particularly regarding reproductive and migration behavior, underlying regional patterns in population and environmental change. Since then, other teams of researchers, some represented in this volume, have also taken up this challenge. This body of work shows that when only looking . at aggregate total population as a cause, the process of deforestation tends to be simplified. To get at the causes of deforestation, we need to examine how households make constrained decisions within their regional context, the land tenure system in place, the opportunities available to households to use their resources, the needs of a given household shaped by age and gender structure, and how members of households understand and make use of their physical environment. This chapter documents the evolution of a project that has made use of a broad array of theories, methodologies, and conceptualizations linking

Activity patterns of the giant panda (Ailuropoda melanoleuca)

One of the most fundamental questions in animal ecology concerns the activity patterns of animals and the environmental and intrinsic factors that influence such dynamics. Activity patterns of the elusive and endangered giant panda (Ailuropoda melanoleuca) are not well understood. Using GPS collars equipped with dual-axis accelerometers on captive and wild giant pandas for the first time, we investigated the impact of day, season, and weather on wild panda activity in Wolong Nature Reserve, Sichuan, China. Most pandas were not crepuscular as previously reported but had 3 apparent activity peaks, in the morning, afternoon, and around midnight. We found a peak in panda activity in June, then an apparent decrease in August and September, followed by an increase again from November to March of the following year. Activity patterns roughly corresponded to mean daily movement distances across seasons and movement behavior in a GPS-collared captive panda (studied to establish a baseline for interpreting collar-recorded activity of wild pandas). There was greater activity in times of higher solar radiation throughout every season, especially under cold conditions. This result suggests the potential for climate change to impact panda behavior in ways not previously reported. Our analysis also suggests that pandas may be constrained by tight energy budgets from their low-nutrient diet and may adjust their energy budgets by modifying their activity time and level across seasons. Our study has implications for understanding animal activity patterns across species, particularly relationships among forage, weather, and energy expenditure over time.

Modeling activity patterns of wildlife using time-series analysis

Abstract The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency‐based time‐series analysis, with high‐resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda (Ailuropoda melanoleuca). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant pandas mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24‐hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high‐resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.

Giant panda foraging and movement patterns in response to bamboo shoot growth

Diet plays a pivotal role in dictating behavioral patterns of herbivorous animals, particularly specialist species. The giant panda (Ailuropoda melanoleuca) is well-known as a bamboo specialist. In the present study, the response of giant pandas to spatiotemporal variation of bamboo shoots was explored using field surveys and GPS collar tracking. Results show the dynamics in panda-bamboo space-time relationships that have not been previously articulated. For instance, we found a higher bamboo stump height of foraged bamboo with increasing elevation, places where pandas foraged later in spring when bamboo shoots become more fibrous and woody. The time required for shoots to reach optimum height for foraging was significantly delayed as elevation increased, a pattern which corresponded with panda elevational migration patterns beginning from the lower elevational end of Fargesia robusta distribution and gradually shifting upward until the end of the shooting season. These results indicate that giant pandas can respond to spatiotemporal variation of bamboo resources, such as available shoots. Anthropogenic interference of low-elevation F. robusta habitat should be mitigated, and conservation attention and increased monitoring should be given to F. robusta areas at the low- and mid-elevation ranges, particularly in the spring shooting season.