Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p <0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p <0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management

Distinguishing Land Change from Natural Variability and Uncertainty in Central Mexico with MODIS EVI, TRMM Precipitation, and MODIS LST Data

Precipitation and temperature enact variable influences on vegetation, impacting the type and condition of land cover, as well as the assessment of change over broad landscapes. Separating the influence of vegetative variability independent and discrete land cover change remains a major challenge to landscape change assessments. The heterogeneous Lerma-Chapala-Santiago watershed of central Mexico exemplifies both natural and anthropogenic forces enacting variability and change on the landscape. This study employed a time series of Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectoradiometer (MODIS) for 2001–2007 and per-pixel multiple linear regressions in order to model changes in EVI as a function of precipitation, temperature, and elevation. Over the seven-year period, 59.1% of the variability in EVI was explained by variability in the independent variables, with highest model performance among changing and heterogeneous land cover types, while intact forest cover demonstrated the greatest resistance to changes in temperature and precipitation. Model results were compared to an independent change uncertainty assessment, and selected regional samples of change confusion and natural variability give insight to common problems afflicting land change analyses

Integrated basin modeling

Simulation models / Irrigation management / Water balance / Groundwater / River basins / Hydrology / Flow / Evapotranspiration / Precipitation / Soils / Turkey / Gediz Basin

THE BIG PICTURE - SATELLITE REMOTE SENSING APPLICATIONS IN RANGELAND ASSESSMENT AND CROP INSURANCE

Livestock Production/Industries, Risk and Uncertainty,

IMPACTS OF ENVIRONMENTAL VARIABLES ON DEER MOUSE SURVIVAL IN THE SOUTHWESTERN UNITED STATES

North American deer mice (Peromyscus maniculatus) are the primary reservoir for Sin Nombre orthohantavirus, and they play a significant role in the maintenance and transmission of disease across the landscape. Vital rates, such as survival, are a key component to understanding how disease spreads in a population. Understanding environmental factors that influence survival may allow for development of a predictive model that can assess disease risk in deer mice and, thus, a corresponding increased disease risk for humans. Our work explored the relationship between deer mouse survival and environmental variables at three long-term small mammal trapping sites in the United States Southwest. Using Bayesian variable selection, we assessed support for normalized difference vegetation index, precipitation, temperature minima and maxima, and snow-water equivalent at various time lags. From the selection process we formulated a robust-design capture-mark-recapture model in a Bayesian framework to quantify the effect of the selected variables on deer mouse survival. We found that survival varied by location and no one set of variables best explained survival across all sites. Consistencies between sites indicate that survival of deer mice follows a seasonal trend and does not vary by sex. Some of our results contrast previous work focused on use of environmental variables to predict deer mouse abundance and did not provide a consistent finding around which to formulate a predictive model. Future modeling efforts should focus on assessing both survival and reproduction as well as consideration of a more place-specific approach that includes additional variables that influence survival in different ecological contexts

Evaluating the spatial ecology of anthrax in North America: examining epidemiological components across multiple geographic scales using a GIS-based approach

This dissertation explores the spatial ecology and potential pathways of infection of anthrax, Bacillus anthracis, in North America. A multi-scale approach was used to evaluate the components required for disease agent survival in the environment, interactions with wildlife, and the potential role that vectors play in anthrax transmission. First, ecological niche modeling with the Genetic Algorithm for Rule-set Production (GARP) was used to predict the geographic distribution of anthrax in the continental U.S. using case data from outbreaks between 1957 and 2005. These results were then used to produce the first quantitative, continental scale predictions of anthrax in Mexico. At the meso-scale, the route of transmission in white-tailed deer is unknown, despite a large number of outbreaks in wild deer in Texas in recent years (2001 – 2005). To determine the interactions between deer and potential anthrax sources, two pilot studies were conducted on 1) the distribution of biting flies in relation to anthrax cases to evaluate the potential role of hematophagous flies as vectors, and 2) the summer home ranges of deer in relation to fly densities and carcass locations. The results of the GARP studies support the use of the technique for modeling the niche of this disease and suggest a central corridor of anthrax habitat from southwest Texas to the Canadian border, with disjunct areas in the Pacific Northwest and California. Mexico’s predicted areas were extensions of the Texas and California ranges. The deer study suggests that deer interactions with spores occur within a limited home range in Texas and long-distance movement of spores is unlikely by individual deer. Biting fly densities were highest in areas of known anthrax infection and lowest in areas where case-positive deer have not been identified, suggesting that flies may play a role in disease transmission, either through mechanical transmission or through increased nuisance that leads to immuno-suppression in deer. This dissertation presents the first continental-scale predictions for the geographic distribution of anthrax in the U.S. and Mexico. Additionally, this is the first known study to evaluate spatial patterns between known cases, fly densities, and animal movements

Afforestation and Reforestation: Drivers, Dynamics, and Impacts

Afforestation/reforestation (or forestation) has been implemented worldwide as an effective measure towards sustainable ecosystem services and addresses global environmental problems such as climate change. The conversion of grasslands, croplands, shrublands, or bare lands to forests can dramatically alter forest water, energy, and carbon cycles and, thus, ecosystem services (e.g., carbon sequestration, soil erosion control, and water quality improvement). Large-scale afforestation/reforestation is typically driven by policies and, in turn, can also have substantial socioeconomic impacts. To enable success, forestation endeavors require novel approaches that involve a series of complex processes and interdisciplinary sciences. For example, exotic or fast-growing tree species are often used to improve soil conditions of degraded lands or maximize productivity, and it often takes a long time to understand and quantify the consequences of such practices at watershed or regional scales. Maintaining the sustainability of man-made forests is becoming increasingly challenging under a changing environment and disturbance regime changes such as wildland fires, urbanization, drought, air pollution, climate change, and socioeconomic change. Therefore, this Special Issue focuses on case studies of the drivers, dynamics, and impacts of afforestation/reforestation at regional, national, or global scales. These new studies provide an update on the scientific advances related to forestation. This information is urgently needed by land managers and policy makers to better manage forest resources in today’s rapidly changing environments