How vulnerable are ecosystems in the Limpopo province to climate change?

Scheiter, Simon; Gaillard, Camille; Martens, Carola; Erasmus, Barend; Pfeiffer, Mirjam

doi:10.1016/j.sajb.2018.02.394

Cited by 23 publications

(25 citation statements)

References 57 publications

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“…Projected biome changes towards woody vegetation under eCO 2 are consistent with results from previous studies on regional (Doherty et al., 2010) and continental scale (Conradi et al, 2020; Gonzalez et al., 2010; Higgins & Scheiter, 2012; Niang et al., 2014; Scholze et al., 2006; Sitch et al., 2008). The transition of grassland and savanna biomes, that is, C 4 ‐dominated biomes, to more woody biomes, that is, C 3 ‐dominated biomes, in eCO 2 simulations corroborates findings that savannas and grasslands are particularly vulnerable to biome changes under eCO 2 (Higgins & Scheiter, 2012; Osborne et al., 2018; Scheiter et al., 2018). Woody encroachment into grasslands and savannas in Africa is a major threat to their biodiversity (Bond, 2016).…”

Section: Discussionsupporting

confidence: 74%

“…As opposed to Scheiter et al. (2018), the use of daily climate input data for our simulations helped to avoid the generation of daily climate time series with the aDGVM and thus removed the associated stochasticity. In addition, the high spatial resolution of our simulations effectively acts as a replication in space with smooth simulation patterns in space indicating low aDGVM‐caused variability in the simulation.…”

Section: Methodsmentioning

confidence: 99%

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Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

Martens

Hickler

Davis-Reddy

et al. 2020

Global Change Biology

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Anthropogenic climate change is expected to impact ecosystem structure, biodiversity and ecosystem services in Africa profoundly. We used the adaptive Dynamic Global Vegetation Model (aDGVM), which was originally developed and tested for Africa, to quantify sources of uncertainties in simulated African potential natural vegetation towards the end of the 21st century. We forced the aDGVM with regionally downscaled high‐resolution climate scenarios based on an ensemble of six general circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). Our study assessed the direct effects of climate change and elevated CO2 on vegetation change and its plant‐physiological drivers. Total increase in carbon in aboveground biomass in Africa until the end of the century was between 18% to 43% (RCP4.5) and 37% to 61% (RCP8.5) and was associated with woody encroachment into grasslands and increased woody cover in savannas. When direct effects of CO2 on plants were omitted, woody encroachment was muted and carbon in aboveground vegetation changed between –8 to 11% (RCP 4.5) and –22 to –6% (RCP8.5). Simulated biome changes lacked consistent large‐scale geographical patterns of change across scenarios. In Ethiopia and the Sahara/Sahel transition zone, the biome changes forecast by the aDGVM were consistent across GCMs and RCPs. Direct effects from elevated CO2 were associated with substantial increases in water use efficiency, primarily driven by photosynthesis enhancement, which may relieve soil moisture limitations to plant productivity. At the ecosystem level, interactions between fire and woody plant demography further promoted woody encroachment. We conclude that substantial future biome changes due to climate and CO2 changes are likely across Africa. Because of the large uncertainties in future projections, adaptation strategies must be highly flexible. Focused research on CO2 effects, and improved model representations of these effects will be necessary to reduce these uncertainties.

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Section: Discussionsupporting

confidence: 74%

Section: Methodsmentioning

confidence: 99%

Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

Martens

Hickler

Davis-Reddy

et al. 2020

Global Change Biology

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show abstract

“…The aDGVM is individual-based and simulates state variables such as biomass, height and photosynthetic rates of individual plants. This approach allows us to model how herbivores , fire (Scheiter and Higgins, 2009) and land use (Scheiter and Savadogo, 2016;Scheiter et al, 2019) impact individual plants as a function of plant traits. Grasses are simulated by two super-individuals, representing grasses beneath or between tree canopies.…”

Section: Model Descriptionmentioning

confidence: 99%

African biomes are most sensitive to changes in CO2 under recent and near-future CO2 conditions

et al. 2020

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Abstract. Current rates of climate and atmospheric change are likely higher than during the last millions of years. Even higher rates of change are projected in CMIP5 climate model ensemble runs for some Representative Concentration Pathway (RCP) scenarios. The speed of ecological processes such as leaf physiology, demography or migration can differ from the speed of changes in environmental conditions. Such mismatches imply lags between the actual vegetation state and the vegetation state expected under prevailing environmental conditions. Here, we used a dynamic vegetation model, the adaptive Dynamic Global Vegetation Model (aDGVM), to study lags between actual and expected vegetation in Africa under a changing atmospheric CO2 mixing ratio. We hypothesized that lag size increases with a more rapidly changing CO2 mixing ratio as opposed to slower changes in CO2 and that disturbance by fire further increases lag size. Our model results confirm these hypotheses, revealing lags between vegetation state and environmental conditions and enhanced lags in fire-driven systems. Biome states, carbon stored in vegetation and tree cover in Africa are most sensitive to changes in CO2 under recent and near-future levels. When averaged across all biomes and simulations with and without fire, times to reach an equilibrium vegetation state increase from approximately 242 years for 200 ppm to 898 years for 1000 ppm. These results have important implications for vegetation modellers and for policy making. Lag effects imply that vegetation will undergo substantial changes in distribution patterns, structure and carbon sequestration even if emissions of fossils fuels and other greenhouse gasses are reduced and the climate system stabilizes. We conclude that modelers need to account for lag effects in models and in data used for model testing. Policy makers need to consider lagged responses and committed changes in the biosphere when developing adaptation and mitigation strategies.

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“…In addition, we only considered changes in CO 2 in this study whereas changes in other key variables influencing vegetation, particularly precipitation and temperature, were ignored. Previous aDGVM studies show that change in CO 2 is the main driver of simulated future vegetation change due to strong CO 2 fertilization effects (Scheiter and Higgins, 2009;Scheiter et al, 2015Scheiter et al, , 2018. We therefore expect that using time series of both CO 2 and climatic drivers following RCP scenarios will not change the fundamental results of our study.…”

Section: Implications For Vegetation Modelingmentioning

confidence: 81%

African biomes are most sensitive to changes in CO2 under recent and near-future CO2 conditions

Scheiter¹,

Moncrieff²,

Pfeiffer³

et al. 2019

Preprint

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Abstract. Current rates of climate and atmospheric change are likely higher than during the last millions of years. Even higher rates of change are projected in CMIP5 climate model ensemble runs for some RCP scenarios. Mismatches between the speed of ecological processes such as physiological adaptation, demographic shifts or migration, and the speed of changes in en- vironmental conditions imply lags between the transient vegetation state and the vegetation state expected under prevailing environmental conditions. Here, we used a dynamic vegetation model, the aDGVM, to study lags between transient and committed vegetation in Africa under changing atmospheric CO2 mixing ratio. We hypothesized that lag size increases with more rapidly changing CO2 mixing ratio as opposed to slower changes in CO2, and that disturbance by fire further increases these lags. Our model results confirm these hypotheses, revealing lags between vegetation state and environmental conditions and enhanced lags in fire-driven systems. Biome states, carbon stored in vegetation and tree cover in Africa are most sensitive to changes in the CO2 mixing ratio under recent and near-future levels, between approximately 300 and 500&#8201;ppm. These results have important implications for vegetation modellers as well as for management and policy making. Lag effects implicate that vegetation will undergo substantial changes in distribution patterns, structure and carbon sequestration even if emissions of fossils fuels and other greenhouse gasses are reduced and the climate system stabilizes. We conclude that modelers need to account for lags in models and data used for model testing and that policy makers need to consider lagged responses and committed changes in the biosphere when developing adaptation and mitigation strategies.

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How vulnerable are ecosystems in the Limpopo province to climate change?

Cited by 23 publications

References 57 publications

Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

African biomes are most sensitive to changes in CO<sub>2</sub> under recent and near-future CO<sub>2</sub> conditions

African biomes are most sensitive to changes in CO<sub>2</sub> under recent and near-future CO<sub>2</sub> conditions

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How vulnerable are ecosystems in the Limpopo province to climate change?

Cited by 23 publications

References 57 publications

Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

African biomes are most sensitive to changes in CO&lt;sub&gt;2&lt;/sub&gt; under recent and near-future CO&lt;sub&gt;2&lt;/sub&gt; conditions

African biomes are most sensitive to changes in CO&lt;sub&gt;2&lt;/sub&gt; under recent and near-future CO&lt;sub&gt;2&lt;/sub&gt; conditions

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African biomes are most sensitive to changes in CO<sub>2</sub> under recent and near-future CO<sub>2</sub> conditions

African biomes are most sensitive to changes in CO<sub>2</sub> under recent and near-future CO<sub>2</sub> conditions