Literature DB >> 32675246

High plant diversity and slow assembly of old-growth grasslands.

Ashish N Nerlekar1, Joseph W Veldman1.   

Abstract

Earth's ancient grasslands and savannas-hereafter old-growth grasslands-have long been viewed by scientists and environmental policymakers as early successional plant communities of low conservation value. Challenging this view, emerging research suggests that old-growth grasslands support substantial biodiversity and are slow to recover if destroyed by human land uses (e.g., tillage agriculture, plantation forestry). But despite growing interest in grassland conservation, there has been no global test of whether old-growth grasslands support greater plant species diversity than secondary grasslands (i.e., herbaceous communities that assemble after destruction of old-growth grasslands). Our synthesis of 31 studies, including 92 timepoints on six continents, found that secondary grasslands supported 37% fewer plant species than old-growth grasslands (log response ratio = -0.46) and that secondary grasslands typically require at least a century, and more often millennia (projected mean 1,400 y), to recover their former richness. Young (<29 y) secondary grasslands were composed of weedy species, and even as their richness increased over decades to centuries, secondary grasslands were still missing characteristic old-growth grassland species (e.g., long-lived perennials). In light of these results, the view that all grasslands are weedy communities, trapped by fire and large herbivores in a state of arrested succession, is untenable. Moving forward, we suggest that ecologists should explicitly consider grassland assembly time and endogenous disturbance regimes in studies of plant community structure and function. We encourage environmental policymakers to prioritize old-growth grassland conservation and work to elevate the status of old-growth grasslands, alongside old-growth forests, in the public consciousness.

Entities:  

Keywords:  biodiversity; disturbance; land-use change; meta-analysis; succession

Mesh:

Year:  2020        PMID: 32675246      PMCID: PMC7414179          DOI: 10.1073/pnas.1922266117

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


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