We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.
Native to Asia, the spotted lanternfly, Lycorma delicatula (White), is an emerging pest of many commercially important plants in Korea, Japan, and the United States. Determining its potential distribution is important for proactive measures to protect commercially important commodities. The objective of this study was to assess the establishment risk of L. delicatula globally and in the United States using the ecological niche model MAXENT, with a focus on Washington State (WA), where large fruit industries exist. The MAXENT model predicted highly suitable areas for L. delicatula in Asia, Oceania, South America, North America, Africa, and Europe, but also predicted that tropical habitats are not suitable for its establishment, contrary to published information. Within the United States, the MAXENT model predicted that L. delicatula can establish in most of New England and the mid-Atlantic states, the central United States and the Pacific Coast states, including WA. If introduced, L. delicatula is likely to establish in fruit-growing regions of the Pacific Northwest. The most important environmental variables for predicting the potential distribution of L. delicatula were mean temperature of driest quarter, elevation, degree-days with a lower developmental threshold value of 11°C, isothermality, and precipitation of coldest quarter. Results of this study can be used by regulatory agencies to guide L. delicatula surveys and prioritize management interventions for this pest.
National Parks are hallmarks of ecosystem preservation in the United States. The introduction of alien invasive plant species threatens protection of these areas. Bromus tectorum L. (commonly called downy brome or cheatgrass), which is found in Rocky Mountain National Park (hereafter, the Park), Colorado, USA, has been implicated in early spring competition with native grasses, decreased soil nitrogen, altered nutrient and hydrologic regimes, and increased fire intensity. We estimated the potential distribution of B. tectorum in the Park based on occurrence records (n = 211), current and future climate, and distance to roads and trails. An ensemble of six future climate scenarios indicated the habitable area of B. tectorum may increase from approximately 5.5% currently to 20.4% of the Park by the year 2050. Using ordination methods we evaluated the climatic space occupied by B. tectorum in the Park and how this space may shift given future climate change. Modeling climate change at a small extent (1,076 km2) and at a fine spatial resolution (90 m) is a novel approach in species distribution modeling, and may provide inference for microclimates not captured in coarse-scale models. Maps from our models serve as high-resolution hypotheses that can be improved over time by land managers to set priorities for surveys and removal of invasive species such as B. tectorum.
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