|Title||Harnessing the power of AI technologies for ecology: Grass recovery in shrub dominated landscapes|
|Publication Type||Conference Paper|
|Year of Publication||2020|
|Authors||Burruss DN, Peters DC|
|Conference Name||Ecological Society of America|
|Conference Location||Virtual Conference|
|ARIS Log Number||378842|
Many drylands of the world have experienced dramatic changes in vegetation from perennial grasslands to woody plant dominance over the past several centuries. These states are thought to be very stable under current climate as a result of feedbacks between woody plants and soil properties such that grass recovery rarely occurs, and restoration is difficult. When grass recovery occurs, spatiotemporal heterogeneity in recovery patterns at multiple scales makes it challenging to identify the drivers and processes governing those dynamics. New technologies that link big data analytics with computer vision and image processing are promising approaches that can move restoration ecology forward.