A Framework for Evaluating the Effects of Human Factors on Wildlife Habitat: the Case of Giant Pandas

Abstract: To address the complex interactions between humans and wildlife habitat, we developed a conceptual framework that links human factors with forested landscapes and wildlife habitat. All the components in the framework are integrated into systems models that analyze the effects of human factors and project how wildlife habitat would change under different policy scenarios. As a case study, we applied this framework to the Wolong Nature Reserve in Sichuan Province (southwestern China), the largest home of the giant panda ( Ailuropoda melanoleuca ). We collected ecological and socioeconomic data with a combination of various methods ( field observations, aerial photographs, government documents and statistics, interviews, and household surveys) and employed geographic information systems and systems modeling to analyze and integrate the data sources. Human population size has increased by 66% and the number of households in the reserve has increased by 115% since 1975, when the reserve was established. During the same period, the quality and quantity of the giant panda habitat dramatically decreased because of increasing human activities such as fuelwood collection. Systems modeling predicted that under the status quo, human population in the reserve would continue to grow and cause more destruction of the remaining panda habitat, whereas reducing human birth rates and increasing human emigration rates would lower human population size and alleviate human impacts on the panda habitat. Furthermore, our simulations and surveys suggested that policies encouraging the emigration of young people would be more effective and feasible than relocating older people in reducing human population size and conserving giant panda habitat in the reserve.     

An analysis of the problems of developing environmental education in Brazilian Federal protected areas

This paper describes the problems encountered in developing environmental education in Federal protected areas in Brazil. Results of a survey on the current status of environmental education in four categories of Federal protected areas; namely national parks, biological reserves, ecological stations and environmental protection areas, are described and discussed. The study suggests that the development of environmental education in protected areas in the country has several limitations: financial resources, lack of training, material resources and a lack of policy on environmental education. It also identifies that some of these problems seem to be inter-related with those of the National System of Conservation Units of the country which may result in a retarding of the development of environmental education in such areas.     

Ownership property size,landscape structure,and spatial relationships in the Edwards Plateau of Texas (USA): landscape scale habitat management implications

The present research focused on using spatial analysis to determine relationships among land ownership property sizes and landscape structure, with a focus on conservation management implications. Indices and metrics of ownership property sizes and landscape structure were calculated for 20 km buffer areas around 31 North American Breeding Bird Survey transects, 12 located within the Edwards Plateau ecoregion and 18 in contiguous ecoregions. The number of bird species observed at each transect provided a measure of avian species richness associated with land cover classes for each respective transect (González in Urban influence on diversity of avifauna in the Edwards Plateau of Texas: effect of property sizes on rural landscape structure, Texas A&M University, 2005). Spatial correlations were calculated between each pair of the landscape indices. Spatial analysis identified a “threshold of habitat fragmentation” for the 500 acre (ac) ownership property size. Significant spatial correlations among variables showed that property sizes lower than 500 ac produced habitat fragmentation represented by a decrease in mean patch size (MN) and proximity among habitat patches (Index PROX). Spatial analysis also made possible the prioritization of ecological sub-regions of the Edwards Plateau for conservation or restoration. The Live Oak-Mesquite Savannah showed the highest average ownership property size (7305 ac) and the highest values of patch richness. Based on the results, management in the Live Oak-Mesquite Savannah sub-region should focus on the conservation of land mosaic diversity to assure native avian species turnover (Whittaker 1972). In Balcones Canyon Lands, 64 % of land was covered by farms smaller than 500 ac and the overall average ownership property size was above the threshold of fragmentation (1440 ac), implying that management policies there should focus both on habitat conservation and on restoration. In contrast, 71 % of land in the Lampasas Cut Plains was covered by farms smaller than 500 ac, and average ownership property size was very close to the fragmentation threshold (625 ac). Consequently, the results indicate that management in the Lampasas Cut Plains sub-region should focus on habitat restoration (e.g., corridors that connect isolated habitat patches). In general, the threshold of ownership property size, 500 ac, is important for conservation planning because below that threshold of property size, habitat patch size begins to decrease and the distance between equivalent patches of habitat increases. Isolated patches act as islands within a sea of less suitable habitat which produce negative effects on biodiversity. Identifying the spatial characteristics indicative of habitat fragmentation, or the likelihood thereof, is an important issue for conservation planning in places with urban sprawl influence.     

Direct and indirect land-use change as prospective climate change indicators for peri-urban development transitions

With urban areas responsible for a significant share of total anthropogenic emissions, greenhouse gas (GHG) emissions due to land-use change (LUC) induced by peri-urban (PU) development have the potential to be considerable. Despite this, there is little research into the transition from PU cropland to housing in terms of contribution to global warming. This paper presents a cross-sectoral integrative method for prospective climate change evaluation of PU LUC. Specifically, direct LUC (dLUC) GHG emissions from converting PU cropland to greenfield housing were examined. Additionally, GHG emissions due to displaced crop production inducing indirect LUC (iLUC) elsewhere were assessed. GHG impacts of dLUC and iLUC were each determined to be approximately 8 per cent of total GHG emissions due to a greenfield housing development displacing PU cropland. This magnitude of dLUC and iLUC emissions suggests that both have importance in future land-use decision making with respect to PU environments.     

Modeled response of ozone to electricity generation emissions in the northeastern United States using three sensitivity techniques

Electrical generation units (EGUs) are important sources of nitrogen oxides (NO_x) that contribute to ozone air pollution. A dynamic management system can anticipate high ozone and dispatch EGU generation on a daily basis to attempt to avoid violations, temporarily scaling back or shutting down EGUs that most influence the high ozone while compensating for that generation elsewhere. Here we investigate the contributions of NO_x from individual EGUs to high daily ozone, with the goal of informing the design of a dynamic management system. In particular, we illustrate the use of three sensitivity techniques in air quality models—brute force, decoupled direct method (DDM), and higher-order DDM—to quantify the sensitivity of high ozone to NO_x emissions from 80 individual EGUs. We model two episodes with high ozone in the region around Pittsburgh, PA, on August 4 and 13, 2005, showing that the contribution of 80 EGUs to 8-hr daily maximum ozone ranges from 1 to >5 ppb at particular locations. At these locations and on the two high ozone days, shutting down power plants roughly 1.5 days before the 8-hr ozone violation causes greater ozone reductions than 1 full day before; however, the benefits of shutting down roughly 2 days before the high ozone are modest compared with 1.5 days. Using DDM, we find that six EGUs are responsible for >65% of the total EGU ozone contribution at locations of interest; in some locations, a single EGU is responsible for most of the contribution. Considering ozone sensitivities for all 80 EGUs, DDM performs well compared with a brute-force simulation with a small normalized mean bias (–0.20), while this bias is reduced when using the higher-order DDM (–0.10).

Implications: Dynamic management of electrical generation has the potential to meet daily ozone air quality standards at low cost. We show that dynamic management can be effective at reducing ozone, as EGU contributions are important and as the number of EGUs that contribute to high ozone in a given location is small (<6). For two high ozone days and seven geographic regions, EGUs would best be shut down or their production scaled back roughly 1.5 days before the forecasted exceedance. Including online sensitivity techniques in an air quality forecasting model can provide timely and useful information on which EGUs would be most beneficial to shut down or scale back temporarily.     

The air quality forecast rote: Recent changes and future challenges

Air quality forecasting is a recent development, with most programs initiated only in the last 20 years. During the last decade, forecast preparation procedure—the forecast rote—has changed dramatically. This paper summarizes the unique challenges posed by air quality forecasting, details the current forecast rote, and analyzes prospects for future improvements. Because air quality forecasts must diagnose and predict several pollutants and their precursors in addition to standard meteorological variables, it is, compared with weather forecasts, a higher-uncertainty forecast. Forecasters seek to contain the uncertainty by “anchoring” the forecast, using an a priori field, and then “adjusting” the forecast using additional information. The air quality a priori, or first guess, field is a blend of past, current, and near-term future observations of the pollutants of interest, on both local and regional scales, and is typically coupled with predicted air parcel trajectories. Until recently, statistical methods, based on long-term training data sets, were used to adjust the first guess. However, reductions in precursor emissions in the United States, beginning in the late 1990s and continuing to the present, eroded the stationarity assumption for the training data sets and degraded forecast skill. Beginning in the mid-2000s, output from modified numerical air quality prediction (NAQP) models, originally developed to test pollution control strategies, became available in near real time for forecast support. The current adjustment process begins with the analyses and postprocessing of individual NAQP models and their ad hoc ensembles, often in concert with new statistical techniques. The final adjustment step uses forecaster expertise to assess the impact of mesoscale features not resolved by the NAQP models. It is expected that advances in model resolution, chemical data assimilation, and the formulation of emissions fields will improve mesoscale predictions by NAQP models and drive future changes in the forecast rote.

Implications: Routine air quality forecasts are now issued for nearly all the major U.S. metropolitan areas. Methods of forecast preparation—the forecast rote—have changed significantly in the last decade. Numerical air quality models have matured and are now an indispensable part of the forecasting process. All forecasting methods, particularly statistically based models, must be continually calibrated to account for ongoing local- and regional-scale emission reductions.     

Evaluation of a Soil‐Based System to Dissipate Multiple Pesticides

Pesticide contaminated wastewater resulting from leftover mixes, equipment cleaning, and container disposal are problems related to pesticide use. This study reports on the effectiveness of a soil‐based bioreactor (SBBR) to dissipate pesticides of differing concentrations and mixtures. In order to accomplish this study, soil columns were used to simulate the SBBR. A mixture of five herbicides and two insecticides from seven different chemical families (atrazine, dicamba, fluometuron, metolachlor, sulfentrazone, chlopyrifus, and λ‐cyhalothrin) were added to the SBBR‐simulated system as formulated products in three concentrations each: 0 part per million (control), 10 ppm, and 100 ppm. Additionally a 1,000 ppm treatment was added that included just the five herbicides to investigate how the system would respond to heavy loading. The system was run for 90 days with samples taken at day 4 (just prior to loading the columns), then at 30, 60, and 90 days. At low pesticide concentrations (10 and 100 ppm), there was significant dissipation (p < 0.05) of all pesticides in the columns except sulfentrazone. At 1,000 ppm, fluometuron, in addition to sulfentrazone, did not show significant dissipation. Overall, the system performed as expected and could be considered practical for use on farms or nurseries. ©2015 Wiley Periodicals, Inc.     

Lessons Learned from an Industry,Government and University Collaboration to Restore Stream Habitats and Mitigate Effects

Environmental Management - Restoration ecologists conduct both basic and applied research using a diversity of funding and collaborative models. Over the last 17 years we have assessed the...     

Managing tricky decentralised competencies: case study of a participatory modelling experiment on land use in the Lake Guiers area in Northern Senegal

We describe an action-research project whose objective was to help stakeholders at different organisational levels achieve sustainable land management by developing mediation models and tools. We chose to test a specific approach called companion modelling in the framework of a multidisciplinary research partnership and a formal local partnership (a ‘users committee’) involving an array of stakeholders at different organisational levels. The study area covers 10,000 km² of agro-pastoral land around Lake Guiers in northern Senegal. We conducted studies to update the knowledge base of the area and organised six field workshops that clearly revealed three important tool functions to support decision-making on land use at different scales, i.e. understanding maps, monitoring and evaluating land tenure, and foreseeing changes in land use. We found that a toolbox approach was the best way to implement the three functions and overcome the constraints faced by the research team and those linked to the timing of the project. Therefore, we produced five simple complementary tools aimed at various users: a farm-level optimisation model (for researchers and technical services), a database for land allocations and a discussion tool to assess the impact of land allocation decisions (for the rural council), a paper atlas (for local players) and a regional land use change simulation model (for regional and national planners). Participants were able to work with paper maps, to interpret computer-generated simulations of land use change and understand the strengths and limitations of each. Self-assessment of the research process emphasised the importance of the context and the critical role played by social capital at both the research and the field level, which, in turn, emphasised the need for major improvements in the design and implementation of a quality process for participatory modelling. It turns out that action-research may be an effective way to undertake sustainability science.