Modeling the Effects of Habitat Fragmentation on the Movements of the Mongolian Gazelle in the Eastern Mongolian Steppe

The Mongolian gazelle, Procapra gutturosa, resides in the immense and dynamic ecosystem of the Eastern Mongolian Steppe. The Mongolian Steppe ecosystem dynamics, including vegetation availability, change rapidly and dramatically due to unpredictable precipitation patterns. The Mongolian gazelle has adapted to this unpredictable vegetation availability by making long range nomadic movements. However, predicting these movements is challenging and requires a complex model. An accurate model of gazelle movements is needed, as rampant habitat fragmentation due to human development projects - which inhibit gazelles from obtaining essential resources - increasingly threaten this nomadic species. We created a novel model using an Individual-based Neural Network Genetic Algorithm (ING) to predict how habitat fragmentation affects animal movement, using the Mongolian Steppe as a model ecosystem. We used Global Positioning System (GPS) collar data from real gazelles to “train” our model to emulate characteristic patterns of Mongolian gazelle movement behavior. These patterns are: preferred vegetation resources (NDVI), displacement over certain time lags, and proximity to human areas. With this trained model, we then explored how potential scenarios of habitat fragmentation may affect gazelle movement. This model can be used to predict how fragmentation of the Mongolian Steppe may affect the Mongolian gazelle. In addition, this model is novel in that it can be applied to other ecological scenarios, since we designed it in modules that are easily interchanged.

AN EXAMINATION OF HYDROXYL RADICAL: OUR CURRENT UNDERSTANDING OF THE OXIDATIVE CAPACITY OF THE TROPOSPHERE THROUGH EMPIRICAL, BOX, AND GLOBAL MODELING APPROACHES

Hydroxyl radical (OH) is the primary oxidant in the troposphere, initiating the removal of numerous atmospheric species including greenhouse gases, pollutants that are detrimental to human health, and ozone-depleting substances. Because of the complexity of OH chemistry, models vary widely in their OH chemistry schemes and resulting methane (CH4) lifetimes. The current state of knowledge concerning global OH abundances is often contradictory. This body of work encompasses three projects that investigate tropospheric OH from a modeling perspective, with the goal of improving the tropospheric community’s knowledge of the atmospheric lifetime of CH4. First, measurements taken during the airborne CONvective TRansport of Active Species in the Tropics (CONTRAST) field campaign are used to evaluate OH in global models. A box model constrained to measured variables is utilized to infer concentrations of OH along the flight track. Results are used to evaluate global model performance, suggest against the existence of a proposed “OH Hole” in the tropical Western Pacific, and investigate implications of high O3/low H2O filaments on chemical transport to the stratosphere. While methyl chloroform-based estimates of global mean OH suggest that models are overestimating OH, we report evidence that these models are actually underestimating OH in the tropical Western Pacific. The second project examines OH within global models to diagnose differences in CH4 lifetime. I developed an approach to quantify the roles of OH precursor field differences (O3, H2O, CO, NOx, etc.) using a neural network method. This technique enables us to approximate the change in CH4 lifetime resulting from variations in individual precursor fields. The dominant factors driving CH4 lifetime differences between models are O3, CO, and J(O3-O1D). My third project evaluates the effect of climate change on global fields of OH using an empirical model. Observations of H2O and O3 from satellite instruments are combined with a simulation of tropical expansion to derive changes in global mean OH over the past 25 years. We find that increasing H2O and increasing width of the tropics tend to increase global mean OH, countering the increasing CH4 sink and resulting in well-buffered global tropospheric OH concentrations.