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Forecasting semi‐arid biome shifts in the Anthropocene.

Authors :
Kulmatiski, Andrew
Yu, Kailiang
Mackay, D. Scott
Holdrege, Martin C.
Staver, Ann Carla
Parolari, Anthony J.
Liu, Yanlan
Majumder, Sabiha
Trugman, Anna T.
Source :
New Phytologist. Apr2020, Vol. 226 Issue 2, p351-361. 11p. 1 Color Photograph, 3 Diagrams, 7 Graphs.
Publication Year :
2020

Abstract

Summary: Shrub encroachment, forest decline and wildfires have caused large‐scale changes in semi‐arid vegetation over the past 50 years. Climate is a primary determinant of plant growth in semi‐arid ecosystems, yet it remains difficult to forecast large‐scale vegetation shifts (i.e. biome shifts) in response to climate change. We highlight recent advances from four conceptual perspectives that are improving forecasts of semi‐arid biome shifts. Moving from small to large scales, first, tree‐level models that simulate the carbon costs of drought‐induced plant hydraulic failure are improving predictions of delayed‐mortality responses to drought. Second, tracer‐informed water flow models are improving predictions of species coexistence as a function of climate. Third, new applications of ecohydrological models are beginning to simulate small‐scale water movement processes at large scales. Fourth, remotely‐sensed measurements of plant traits such as relative canopy moisture are providing early‐warning signals that predict forest mortality more than a year in advance. We suggest that a community of researchers using modeling approaches (e.g. machine learning) that can integrate these perspectives will rapidly improve forecasts of semi‐arid biome shifts. Better forecasts can be expected to help prevent catastrophic changes in vegetation states by identifying improved monitoring approaches and by prioritizing high‐risk areas for management. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0028646X
Volume :
226
Issue :
2
Database :
Academic Search Index
Journal :
New Phytologist
Publication Type :
Academic Journal
Accession number :
142291091
Full Text :
https://doi.org/10.1111/nph.16381