Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought

Climate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale...

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Main Author: Taofeek O. Muraina
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/12/19/7837
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spelling doaj-5d903d311a7349ff81fc534a9cf8aab52020-11-25T01:29:00ZengMDPI AGSustainability2071-10502020-09-01127837783710.3390/su12197837Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme DroughtTaofeek O. Muraina0National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaClimate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale pattern of grasslands’ sensitivity to any ED event remains unresolved. Here, frameworks were built to predict the sensitivity patterns of above-ground net primary productivity (ANPP) spanning the global precipitation gradient under ED. The frameworks particularly present three sensitivity patterns that could manipulate (weaken, strengthen, or erode) the orthodox positive precipitation–productivity relationship which exists under non-drought (ambient) condition. First, the slope of the relationship could become steeper via higher sensitivity at xeric sites than mesic and hydric ones. Second, if the sensitivity emerges highest in hydric, followed by mesic, then xeric, a weakened slope, flat line, or negative slope would emerge. Lastly, if the sensitivity emerges unexpectedly similar across the precipitation gradient, the slope of the relationship would remain similar to that of the ambient condition. Overall, the frameworks provide background knowledge on possible differences or similarities in responses of grasslands to forecast ED, and could stimulate increase in conduct of experiments to unravel the impacts of ED on grasslands. More importantly, the frameworks indicate the need for reconciliation of conflicting hypotheses of grasslands’ sensitivity to ED through global-scale experiments.https://www.mdpi.com/2071-1050/12/19/7837ANPPclimate extremediversityecosystemglobal changehistorical drought
collection DOAJ
language English
format Article
sources DOAJ
author Taofeek O. Muraina
spellingShingle Taofeek O. Muraina
Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
Sustainability
ANPP
climate extreme
diversity
ecosystem
global change
historical drought
author_facet Taofeek O. Muraina
author_sort Taofeek O. Muraina
title Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
title_short Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
title_full Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
title_fullStr Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
title_full_unstemmed Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought
title_sort frameworks on patterns of grasslands’ sensitivity to forecast extreme drought
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2020-09-01
description Climate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale pattern of grasslands’ sensitivity to any ED event remains unresolved. Here, frameworks were built to predict the sensitivity patterns of above-ground net primary productivity (ANPP) spanning the global precipitation gradient under ED. The frameworks particularly present three sensitivity patterns that could manipulate (weaken, strengthen, or erode) the orthodox positive precipitation–productivity relationship which exists under non-drought (ambient) condition. First, the slope of the relationship could become steeper via higher sensitivity at xeric sites than mesic and hydric ones. Second, if the sensitivity emerges highest in hydric, followed by mesic, then xeric, a weakened slope, flat line, or negative slope would emerge. Lastly, if the sensitivity emerges unexpectedly similar across the precipitation gradient, the slope of the relationship would remain similar to that of the ambient condition. Overall, the frameworks provide background knowledge on possible differences or similarities in responses of grasslands to forecast ED, and could stimulate increase in conduct of experiments to unravel the impacts of ED on grasslands. More importantly, the frameworks indicate the need for reconciliation of conflicting hypotheses of grasslands’ sensitivity to ED through global-scale experiments.
topic ANPP
climate extreme
diversity
ecosystem
global change
historical drought
url https://www.mdpi.com/2071-1050/12/19/7837
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