Interactive effects of natural and human disturbances on vegetation dynamics across landscapes

Locally dispersing populations in heterogeneous dynamic landscapes with spatiotemporal correlations. I. Block disturbance

Locally dispersing populations are generally favorably affected by increasing the scale of habitat heterogeneity because they can exploit contiguous patches of suitable habitat. Increasing the spatial scale of landscape disturbances (such as by applying a pesticide to control an unwanted species) drives down population density because of reasons including dispersal-limited recolonization and the resulting increase in temporal variability. Here, we examine how population density changes as the spatial scale of landscape disturbance increases: does it increase due to increases in spatial correlations in landscape habitat type, or does it decrease due to the various spatial and temporal effects of larger-scale disturbances? We use simulations, mean field approximations, pair approximations, landscape-improved pair approximations (LIPA), and block probabilities to investigate a model of a locally dispersing species on a dynamic landscape with spatiotemporally structured heterogeneous habitat. Pesticide is applied at a given spatial scale, leaving habitat unsuitable for some time before dissipating and allowing the habitat to revert to a suitable state. We found that increasing the spatial scale of disturbances (while keeping the overall disturbance rate fixed) can increase population density, but generally only when landscape turnover is slow relative to population dynamics and when the population is somewhat close to its extinction threshold. Applying control measures at larger spatial scales may allow them to be more effective with the same overall treatment rate. The optimal spatial strategy for applying disturbances depends on both habitat availability as well as the turnover rate of the control measure being used. For the large-scale habitat dynamics in our model, it is possible to analytically calculate spatial correlations in habitat types over arbitrary scales. However, including exact habitat correlations at the triplet scale but approximating population correlations at that scale still neglects information needed to accurately predict simulation results, showing that larger-scale correlations in the population distribution have an important effect on dynamics.

Habitat Use and Selection by Giant Pandas

Animals make choices about where to spend their time in complex and dynamic landscapes, choices that reveal information about their biology that in turn can be used to guide their conservation. Using GPS collars, we conducted a novel individual-based analysis of habitat use and selection by the elusive and endangered giant pandas (Ailuropoda melanoleuca). We constructed spatial autoregressive resource utilization functions (RUF) to model the relationship between the pandas' utilization distributions and various habitat characteristics over a continuous space across seasons. Results reveal several new insights, including use of a broader range of habitat characteristics than previously understood for the species, particularly steep slopes and non-forest areas. We also used compositional analysis to analyze habitat selection (use with respect to availability of habitat types) at two selection levels. Pandas selected against low terrain position and against the highest clumped forest at the at-home range level, but no significant factors were identified at the within-home range level. Our results have implications for modeling and managing the habitat of this endangered species by illustrating how individual pandas relate to habitat and make choices that differ from assumptions made in broad scale models. Our study also highlights the value of using a spatial autoregressive RUF approach on animal species for which a complete picture of individual-level habitat use and selection across space is otherwise lacking.

Comparison of microhabitats and foraging strategies between the captive-born Zhangxiang and wild giant pandas: implications for future reintroduction

The female giant panda Zhangxiang (pedigree number 826) was born on August 20, 2011 in Wolong Nature Reserve, China. On November 6, 2013, Zhangxiang was transported into the acclimatization enclosure in the Liziping Nature Reserve. Before Zhangxiang left the enclosure into the wild, we conducted the first study to compare microhabitats and foraging strategies between Zhangxiang in the enclosure and giant pandas in the wild. Compared with the latter, microhabitats of Zhangxiang in the enclosure are characteristic of gentler slope, more trees, higher canopy, smaller tree DBH, and lower density of living bamboos. Diet composition and foraging behaviors significantly differed between Zhangxiang and wild giant pandas, perhaps reflecting the combined consequence of environmental conditions (e.g., bamboo species) and individual status (e.g., age, mastication ability, etc.). The difference in microhabitats and foraging strategies between Zhangxiang and wild giant pandas implied that after being released into the natural habitat in the reserve, Zhangxiang will have to adapt to the environmental conditions once again. For future reintroduction, the enclosure can be extended to the Bashania spanostachya forest in the reserve, and captive giant pandas for release can thus normally transit into the wild without human intervention during acclimatization period. For other acclimatization enclosures to be constructed in the future, ecological environment inside, including topography, forests, and bamboos as well, should as possible as can match the habitat that the giant panda to-be-reinforced populations inhabit.

A Landscape-based model for predicting Mycobacterium ulcerans infection (Buruli Ulcer disease) presence in Benin, West Africa

Mycobacterium ulcerans infection (Buruli ulcer [BU] disease) is an emerging tropical disease that causes severe morbidity in many communities, especially those in close proximity to aquatic environments. Research and control efforts are severely hampered by the paucity of data regarding the ecology of this disease; for example, the vectors and modes of transmission remain unknown. It is hypothesized that BU presence is associated with altered landscapes that perturb aquatic ecosystems; however, this has yet to be quantified over large spatial scales. We quantified relationships between land use/land cover (LULC) characteristics surrounding individual villages and BU presence in Benin, West Africa. We also examined the effects of other village-level characteristics which we hypothesized to affect BU presence, such as village distance to the nearest river. We found that as the percent urban land use in a 50-km buffer surrounding a village increased, the probability of BU presence decreased. Conversely, as the percent agricultural land use in a 20-km buffer surrounding a village increased, the probability of BU presence increased. Landscape-based models had predictive ability when predicting BU presence using validation data sets from Benin and Ghana, West Africa. Our analyses suggest that relatively small amounts of urbanization are associated with a decrease in the probability of BU presence, and we hypothesize that this is due to the increased availability of pumped water in urban environments. Our models provide an initial approach to predicting the probability of BU presence over large spatial scales in Benin and Ghana, using readily available land use data.

Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions

Cross-site comparisons of case studies have been identified as an important priority by the land-use science community. From an empirical perspective, such comparisons potentially allow generalizations that may contribute to production of global-scale land-use and land-cover change projections. From a theoretical perspective, such comparisons can inform development of a theory of land-use science by identifying potential hypotheses and supporting or refuting evidence. This paper undertakes a structured comparison of four case studies of land-use change in frontier regions that follow an agent-based modeling approach. Our hypothesis is that each case study represents a particular manifestation of a common process. Given differences in initial conditions among sites and the time at which the process is observed, actual mechanisms and outcomes are anticipated to differ substantially between sites. Our goal is to reveal both commonalities and differences among research sites, model implementations, and ultimately, conclusions derived from the modeling process.