Browsing by Subject "protected area"

This dissertation consists of four chapters. The first three chapters examine protected areas (or parks) from multiple perspectives. Parks are the first, and often only, line of defense in efforts to conserve biodiversity. Understanding of their promise and problems is necessary to achieve conservation outcomes. Chapter One determines vegetation patterns in and around parks of differing management categories across the Amazon, Congo, South American Atlantic Coast, and West African forests. Within these forests, protected areas are the principle defense against forest loss and species extinctions. In the Amazon and Congo, parks are generally large and retain high levels of forest cover, as do their surroundings. In contrast, parks in the Atlantic Coast forest and West Africa show sharp boundaries in forest cover at their edges. This effective protection of forest cover is partially offset by their very small size: little area is deep inside park boundaries. Compared to West Africa, areas outside parks in the Atlantic Coast forest are unusually fragmented.

Chapter Two addresses a human dimension of protected areas. Given certain characteristics, parks areas may either attract or repel human settlement. Disproportionate increases in population growth near park boundaries may threaten their ability to conserve biodiversity. Using decadal population datasets, we analyze population growth across 45 countries and 304 parks. We find no evidence for population growth near parks to be greater than growth of rural areas in the same country. Furthermore, we argue that what growth does occur near parks likely results from a general expansion of nearby population centers. Parks may experience unusual population pressures near their edges; indeed, individual case studies provide examples. There is no evidence, however, of a general pattern of disproportionate population growth near their boundaries.

Chapter Three provides a review of common approaches to evaluating protection's impact on deforestation, identifies three hurdles to empirical evaluation, and notes that matching techniques from economic impact evaluation address those hurdles. The central hurdle derives from the fact that protected areas are distributed non-randomly across landscapes. Matching controls for landscape characteristics when inferring the impact of protection. Applications of matching have revealed considerably lower impact estimates of forest protection than produced by other methods. These results indicate the importance of variation across locations in how much impact protection could possibly have on rates of deforestation.

Chapter Four departs from the focus of protected areas and instead addresses a more theoretical aspect of community ecology. Ecological theories suggest that food webs might consist of groups of species forming blocks, compartments or guilds. Chapter Four considers ecological networks (subsets of complete food webs) involving species at adjacent trophic levels. Reciprocal specializations occur when (say) a pollinator (or group of pollinators) specializes on a particular flower species (or group of such species) and vice versa. We characterize the level of reciprocal specialization for various classes of networks. Our analyses include both antagonistic interactions (particularly parasitoids and their hosts), and mutualistic ones (such as insects and the flowers that they pollinate). We also examine whether trophic patterns might be palimpsests. That is, there might be reciprocal specialization within taxonomically related species within a network, but these might be obscured when these relationships are combined. Reciprocal specializations are rare in all these systems even when tested using the most conservative null model.

China is one of the most biodiverse countries in the world, harboring more than 10% of the species in the world. Among them, 11% of the vertebrate genera and 7% plant genera are endemic to China. During its rapid social and economic development, increasing habitat loss and fragmentation have occurred. However, it wakes up to the threats of biodiversity in recent years. Protected areas, as an essential conservation tool to reduce habitat loss and species extinction have expanded dramatically in China. Protected areas with various other concepts such as umbrella species and payment for ecosystem services have been promoted to conserve the biodiversity. However, questions remain that whether they work, how they work and how we could do better. It is crucial to answer these questions with the data and technology that are more available to us now.

Thus, my dissertation divides into four chapters and tackles the following four questions. 1) Where do the most of the endemic species concentrate in China? Do umbrellas species such as giant pandas effectively protect other species? 2) With the increasing of tree plantation and available remote sensing data, how does it change the available habitat for forest species, their threat levels and priority setting? 3) Within the conservation priority areas, new threats that are hardly detected by traditional evaluation index such as forest cover emerge. How does a prevalent human disturbance - livestock grazing impact the conservation of giant pandas? What are the socio-economic drivers and solutions to this issue? 4) To better monitor the population and evaluate conservation efforts, new techniques need to be added. Can we use footprints from wild pandas to identify individuals and provide a cost-effective alternative to the current methods?

In Chapter 1, I first used detailed data on geographical ranges for endemic forest species to identify patterns of species richness. After refining each species' range by its known elevational range and remaining forest habitats as determined from remote sensing, I identified the top 5% richest areas as the centers of endemism. Over 96% of the panda habitat overlapped the endemic centers. Thus, investing in almost any panda habitats will benefit many other endemics. Existing panda national nature reserves cover all but one of the endemic species that overlap with the panda’s distribution. For whole China, of particular interest are 14 mammal, 20 bird, and 82 amphibian species that are inadequately protected. Most of these the IUCN currently deems threatened. But 7 mammal, 3 bird, and 20 amphibian species are currently non-threatened, yet their geographical ranges are <20,000 km2 which is the threshold for IUCN to consider it as threatened. There is a high concentration of these species in the east Daxiang and Xiaoxiang Mountains of Sichuan where pandas are absent and where there are no national nature reserves. The others concentrate in Yunnan, Nan Mountains and Hainan. Here, ten prefectures might establish new protected areas or upgrade local nature reserves to national status.

In Chapter 2, I used remote sensing data to differentiate oil palm and rubber plantation from natural forests in Southeast Asia and reevaluated the threat level of endemic forest species identified by IUCN. Tropical, mainland Southeast Asia is under exceptional threat, yet relatively poorly known. This region contains over 122, 183, and 214 endemic mammals, birds, and amphibians, respectively, of which the IUCN considers 37, 21, and 37 threatened. When corrected for the amount of remaining natural habitats, the average sizes of species ranges shrink to <40% of their published ranges and more than 42 percent of species face a much higher risk of extinction from habitat loss than previously thought. Moreover, these species are not better protected by the existing network of protected areas than are species that IUCN accepts as threatened. Furthermore, incorporating remote sensing data showing where habitat loss is prevalent changes the locations of conservation priorities.

Chapter three focuses on a specific threat - livestock grazing in the endemic center that I identified in the first chapter. With the Natural Forest Conservation Program and Grain to Green programs, the deforestation that was once the biggest threat to pandas has been halted. However, a previously unrecognized threat is emerging. Livestock grazing has become the most prevalent human disturbance throughout panda habitats. I applied field sign survey, vegetation survey, GPS collar tracking, and species distribution modeling to study how the livestock grazing impacts the habitat use of giant pandas. This study shows that livestock grazing especially from horses has caused a dramatic decline in bamboos and reduced its regeneration. In the past 15 years, pandas have changed its habitat use and are driven out of areas that are heavily used by livestock. 49% of panda habitat has been lost especially in the lower elevation areas from 2004 till now due to impacts of livestock. Loss of income because of the policies Natural Forest Conservation Project and Grain for Green projects, reduced tourists because of dam construction and earthquake, encouraged horse riding practice during the development of ICDP have contributed to the increasing dependence on livestock sector. Livestock ban with payment for ecosystem services or feedlot operation could be possible solutions for this issue.

Chapter four explores the innovative technique to identify giant panda individuals to facilitate better conservation. Two methods have been used previously to identify individuals and population for giant pandas, fecal bamboo bite size combined with home range analysis and microsatellite analysis of fecal DNA. However, the first one suffers from the lack of accuracy and the latter one is limited by the freshness of the fecal sample and high cost. I developed the footprint identification technique in JMP based on two multivariate methods: discriminant analysis and the canonical centroid plot method using the anatomy measurements of footprints. I used 30 captive pandas to develop the algorithm and 11 individuals for validation. The overall accuracy of FIT for individual identification is 90% and sex discrimination is 85%. This technique is embedded in FIT as an add-in and free for conservation practitioners now.

In summary, this dissertation includes the following four papers.

Chapter 1, Li and Pimm. 2016. China's endemic vertebrates sheltering under the protective umbrella of the giant panda. Conservation Biology 30:329-339.

Chapter 2, Li et al., 2016. Remotely sensed data informs Red List evaluations and conservation priorities in Southeast Asia. PloS one, 11(8), e0160566.

Chapter 3, Li et al., Emerging threat from livestock on giant panda conservation

Chapter 4, Li et al., Identifying individual and sex of giant pandas through Footprint Identification Technique.

With supporting information from the following publication during my Ph.D.:

Li, B. et al. 2014. Effects of feral cats on the evolution of anti-predator behaviours in island reptiles: insights from an ancient introduction. Proc. R. Soc. B 281: 20140339.

Ocampo-Peñuela, N., Jenkins, C. N, Vijay, V., Li, B.V., & Pimm., S.L. 2016. Incorporating explicit geospatial data shows more species at risk of extinction than the current Red List. Science Advances, 2(11), e1601367.

Pimm, S.L., Harris, G., Jenkins, C.N., Ocampo-Peñuela, N. & Li, B.V. 2016 Unfulfilled promise of data-driven approaches: response to Peterson et al. Conservation Biology, In press.

Deforestation and forest degradation in developing countries are leading causes of environmental problems such as soil erosion, biodiversity loss, and climate change. As a result, policies aimed at slowing down or reversing the trend of deforestation and forest degradation have attracted considerable attention. This dissertation consists of three essays on evaluating forest conservation programs in developing countries. Although the focus of each essay differs, they all use rigorous econometric methods to provide insights on impacts of historical forest conservation programs and assist stakeholders in modifying existing policies and making future ones more efficient and effective.

I begin by assessing the nutritional impact of payments for ecosystem services (PES) in the context of rural China (i.e., Chapter 2). PES is a special type of conditional cash transfer (CCT) in which the conditionality is explicitly attached with conservation practices. In this chapter I develop a stylized household-farm model to show that when households participate in a land-diversion PES program, they would settle for lower levels of food consumption if they lack market access. Exploiting panel data from the China Health and Nutrition Survey (CHNS), I use a triple difference (TD) model to examine the impact of China’s Sloping Land Conversion Program (SLCP), one of the largest PES programs in the world, on the nutrient intake of farming households. My findings suggest that the SLCP had a significant negative impact, though small, on calorie intake and this effect was likely driven by missing market in areas that implemented the SLCP. This essay demonstrates that land-diversion PES, which is a dual conservation and development tool, could affect food consumption and nutrition in ways very different from other conservation programs such as protected areas (PAs) as well as regular CCT programs that only aim for poverty reduction.

I then shift the focus from PES to PAs by implementing innovative evaluation methods to assess the effectiveness of mangrove protection in Southeast and South Asia (i.e., Chapter 3 and Chapter 4). Economists typically estimate the average treatment effect on the treated (ATT) when evaluating government programs. The welfare interpretation of the ATT can be ambiguous when program outcomes are measured in purely physical terms, as they often are in evaluations of environmental programs (e.g., avoided deforestation). In Chapter 3, my co-authors and I present an approach for inferring welfare impacts from physical outcomes when the ATT is estimated using propensity-score matching. We employ the discrete-choice Roy model of selection into treatment to show that the ex post net social value of a forest conservation program can be proxied as a weighted ATT, with the weights being utility measures derived from the propensity of being treated. We apply this new metric to mangrove forest conservation in Thailand during 1987–2000. Wefind that the Thai government’s conservation program protected approximately 30% of the social welfare that would have been lost if all the protected mangrove area had been deforested. This magnitude is very similar to the magnitude of a conventional ATT that measures avoided deforestation, but we show that the potential range of the welfare-based ATT extends from barely a quarter of the conventional physical measure to nearly twice as large as it.

While Chapter 3 adopts an indirect approach to infer the welfare impact of PAs, Chapter 4 exploits the same idea in a direct approach. In Chapter 4, my co-authors and I exploit rich data on carbon stock and land values in India toestimate and predict spatial heterogeneity in the benefit (i.e., carbon sequestration) and cost (i.e., forgone land value) of mangrove conservation. We combine this information with satellite-based data on India’s mangrove coverage in 1990– 2010 to construct a net land value, and then estimate the causal impact of PAs on the net land value. This new approach allows us to account for spatial heterogeneity in the net economic benefit of conservation. Our results show that incorporating the economics of conservation into evaluation could detect impact of PAs that would not be detected under the conventional approach that focuses only on avoided deforestation. Estimates from our heterogeneity treatment effect model suggest that the level and direction of PA’s impact is associated with the road proximity of mangrove sites and differs between the short run and the long run.

The three essays in my dissertation examine the heterogeneity in effects of forest conservation programs in one way or another. They highlight that the efficiency and effectiveness of conservation programs depend on local contexts. When designing and implementing future conservation programs, policymakers should assess local contexts and adjust program features accordingly.