Two prominent limitations of species distribution models (SDMs) are spatial biases in existing occurrence data and a lack of spatially explicit predictor variables to fully capture habitat characteristics of species. Can existing and emerging remote sensing technologies meet these challenges and improve futureSDMs? We believe so. Novel products derived from multispectral and hyperspectral sensors, as well as future Light Detection and Ranging (LiDAR) and RADAR missions, may play a key role in improving model performance. In this perspective piece, we demonstrate how modern sensors onboard satellites, planes and unmanned aerial vehicles are revolutionizing the way we can detect and monitor both plant and animal species in terrestrial and aquatic ecosystems as well as allowing the emergence of novel predictor variables appropriate for species distribution modeling. We hope this interdisciplinary perspective will motivate ecologists, remote sensing experts and modelers to work together for developing a more refinedSDMframework in the near future.

Vegetation mapping based on niche theory has proven useful in understanding the rules governing species assembly at various spatial scales. Remote-sensing derived distribution maps depicting occurrences of target species are frequently based on biophysical and biochemical properties of species. However, environmental conditions, such as climatic variables, also affect spectral signals simultaneously. Further, climatic variables are the major drivers of species distribution at macroscales. Therefore, the objective of this study is to determine if species distribution can be modeled using an indirect link to climate and remote sensing data (MODIS NDVI time series). We used plant occurrence data in the US states of North Carolina and South Carolina and 19 climatic variables to generate floristic and climatic gradients using principal component analysis, then we further modeled the correlations between floristic gradients and NDVI using Partial Least Square regression. We found strong statistical relationship between species distribution and NDVI time series in a region where clear floristic and climatic gradients exist. If this precondition is given, the use of niche-based proxies may be suitable for predictive modeling of species distributions at regional scales. This indirect estimation of vegetation patterns may be a viable alternative to mapping approaches using biochemistry-driven spectral signature of species.

Alligatorweed (Alternanthera philoxeroides (Mart.) Griseb.) is an invasive species indigenous to South America. With its rapid invasion of southeastern US waterways, understanding the invasiveness of this plant species is critical for providing possible mechanisms of prevention for resource managers. The aim of this project is to use a matrix model to study the invasion dynamics of alligatorweed under both terrestrial and aquatic environments. The use of this model allows for a deeper understanding of the invasiveness and life history–stage structure of alligatorweed. In particular, matrix analysis can further test the hypothesis that certain life stages of alligatorweed might be more sensitive to control and management. A greenhouse experiment was conducted to study the spread of alligatorweed under both aquatic and terrestrial environments. Utilizing the growth data obtained during the summer of 2010, matrix analysis was used to model the growth of alligatorweed for six different treatments. Transition matrices were generated based on plant measurements taken at different life stages defined by the number of leaves or nodes. These matrices are population projection models whose eigenvalues represent the growth rate of alligatorweed. A high growth rate is a key feature of successful invaders. Residuals were calculated and sensitivity analysis was performed to test the accuracy of the model and importance of each life stage over the entire life cycle of alligatorweed. The results of this study indicate that in the aquatic habitat, plants at their early life cycle stage are most sensitive to potential control measures. Conversely, in the terrestrial habitat, the most sensitive stage of alligatorweed is at its late life cycle stage, characterized with large-sized plants, thus suggesting the best timing for management and eradication of this invasive species.