Literature DB >> 26833671

Grassland responses to increased rainfall depend on the timescale of forcing.

Martin J P Sullivan1, Meredith A Thomsen2, K B Suttle3.   

Abstract

Forecasting impacts of future climate change is an important challenge to biologists, both for understanding the consequences of different emissions trajectories and for developing adaptation measures that will minimize biodiversity loss. Existing variation provides a window into the effects of climate on species and ecosystems, but in many places does not encompass the levels or timeframes of forcing expected under directional climatic change. Experiments help us to fill in these uncertainties, simulating directional shifts to examine outcomes of new levels and sustained changes in conditions. Here, we explore the translation between short-term responses to climate variability and longer-term trajectories that emerge under directional climatic change. In a decade-long experiment, we compare effects of short-term and long-term forcings across three trophic levels in grassland plots subjected to natural and experimental variation in precipitation. For some biological responses (plant productivity), responses to long-term extension of the rainy season were consistent with short-term responses, while for others (plant species richness, abundance of invertebrate herbivores and predators), there was pronounced divergence of long-term trajectories from short-term responses. These differences between biological responses mean that sustained directional changes in climate can restructure ecological relationships characterizing a system. Importantly, a positive relationship between plant diversity and productivity turned negative under one scenario of climate change, with a similar change in the relationship between plant productivity and consumer biomass. Inferences from experiments such as this form an important part of wider efforts to understand the complexities of climate change responses.
© 2016 John Wiley & Sons Ltd.

Keywords:  climate change; context; correlation; extrapolation; precipitation; prediction; time series; trophic level

Mesh:

Year:  2016        PMID: 26833671     DOI: 10.1111/gcb.13206

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


  6 in total

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Authors:  Xuejun Yang; Zhenying Huang; Ming Dong; Xuehua Ye; Guofang Liu; Dandan Hu; Indree Tuvshintogtokh; Tsogtsaikhan Tumenjargal; J Hans C Cornelissen
Journal:  Ann Bot       Date:  2019-10-18       Impact factor: 4.357

2.  Species interactions modulate the response of saltmarsh plants to flooding.

Authors:  Ryan S Edge; Martin J P Sullivan; Scott M Pedley; Hannah L Mossman
Journal:  Ann Bot       Date:  2020-02-03       Impact factor: 4.357

3.  Relative importance of climate changes at different time scales on net primary productivity-a case study of the Karst area of northwest Guangxi, China.

Authors:  Huiyu Liu; Mingyang Zhang; Zhenshan Lin
Journal:  Environ Monit Assess       Date:  2017-10-05       Impact factor: 2.513

4.  Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

Authors:  Phillip P A Staniczenko; Prabu Sivasubramaniam; K Blake Suttle; Richard G Pearson
Journal:  Ecol Lett       Date:  2017-04-21       Impact factor: 9.492

5.  Soil bacterial populations are shaped by recombination and gene-specific selection across a grassland meadow.

Authors:  Alexander Crits-Christoph; Matthew R Olm; Spencer Diamond; Keith Bouma-Gregson; Jillian F Banfield
Journal:  ISME J       Date:  2020-04-23       Impact factor: 10.302

6.  Negative biotic interactions drive predictions of distributions for species from a grassland community.

Authors:  Phillip P A Staniczenko; K Blake Suttle; Richard G Pearson
Journal:  Biol Lett       Date:  2018-11-14       Impact factor: 3.703

  6 in total

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