Will trees or grasses profit from changing rainfall regimes in savannas?

Increasing rainfall variability is widely expected under future climate change scenarios. How will savanna trees and grasses be affected by growing season dry spells and altered seasonality and how tightly coupled are tree-grass phenologies with rainfall? We measured tree and grass responses to growing season dry spells and dry season rainfall. We also tested whether the phenologies of 17 deciduous woody species and the Soil Adjusted Vegetation Index of grasses were related to rainfall between 2019 and 2023. Tree and grass growth was significantly reduced during growing season dry spells. Tree growth was strongly related to growing season soil water potentials and limited to the wet season. Grasses can rapidly recover after growing season dry spells and grass evapotranspiration was significantly related to soil water potentials in both the wet and dry seasons. Tree leaf flushing commenced before the rainfall onset date with little subsequent leaf flushing. Grasses grew when moisture became available regardless of season. Our findings suggest that increased dry spell length and frequency in the growing season may slow down tree growth in some savannas, which together with longer growing seasons may allow grasses an advantage over C3 plants that are advantaged by rising CO2 levels.

Reassessing the alternative ecosystem states proposition in the African savanna-forest domain.

Ecologists are being challenged to predict how ecosystems will respond to climate changes. According to the Multi-Colored World (MCW) hypothesis, climate impacts may not manifest because consumers such as fire and herbivory can override the influence of climate on ecosystem state. One MCW interpretation is that climate determinism fails because alternative ecosystem states (AES) are possible at some locations in climate space. We evaluated theoretical and empirical evidence for the proposition that forest and savanna are AES in Africa. We found that maps which infer where AES zones are located were contradictory. Moreover, data from longitudinal and experimental studies provide inconclusive evidence for AES. That is, although the forest-savanna AES proposition is theoretically sound, the existing evidence is not yet convincing. We conclude by making the case that the AES proposition has such fundamental consequences for designing management actions to mitigate and adapt to climate change in the savanna-forest domain that it needs a more robust evidence base before it is used to prescribe management actions.

The eco-evolutionary significance of rainfall constancy for facultative CAM photosynthesis.

A flexible use of the crassulacean acid metabolism (CAM) has been hypothesised to represent an intermediate stage along a C3 to full CAM evolutionary continuum, when relative contributions of C3 vs CAM metabolism are co-determined by evolutionary history and prevailing environmental constraints. However, evidence for such eco-evolutionary interdependencies is lacking. We studied these interdependencies for the leaf-succulent genus Drosanthemum (Aizoaceae, Southern African Succulent Karoo) by testing for relationships between leaf δ13 C diagnostic for CAM dependence (i.e. contribution of C3 and CAM to net carbon gain), and climatic variables related to temperature and precipitation and their temporal variation. We further quantified the effects of shared phylogenetic ancestry on CAM dependence and its relation to climate. CAM dependence is predicted by rainfall and its temporal variation, with high predictive power of rainfall constancy (temporal entropy). The predictive power of rainfall seasonality and temperature-related variables was negligible. Evolutionary history of the tested clades significantly affected the relationship between rainfall constancy and CAM dependence. We argue that higher CAM dependence might provide an adaptive advantage in increasingly unpredictable rainfall environments when the anatomic exaptation (succulence) is already present. These observations might shed light on the evolution of full CAM.

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

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.

An operational definition of the biome for global change research.

Biomes are constructs for organising knowledge on the structure and functioning of the world's ecosystems, and serve as useful units for monitoring how the biosphere responds to anthropogenic drivers, including climate change. The current practice of delimiting biomes relies on expert knowledge. Recent studies have questioned the value of such biome maps for comparative ecology and global-change research, partly due to their subjective origin. Here we propose a flexible method for developing biome maps objectively. The method uses range modelling of several thousands of plant species to reveal spatial attractors for different growth-form assemblages that define biomes. The workflow is illustrated using distribution data from 23 500 African plant species. In an example application, we create a biome map for Africa and use the fitted species models to project biome shifts. In a second example, we map gradients of growth-form suitability that can be used to identify sites for comparative ecology. This method provides a flexible framework that (1) allows a range of biome types to be defined according to user needs and (2) enables projections of biome changes that emerge purely from the individualistic responses of plant species to environmental changes.

Atmospheric CO2 forces abrupt vegetation shifts locally, but not globally.

It is possible that anthropogenic climate change will drive the Earth system into a qualitatively different state. Although different types of uncertainty limit our capacity to assess this risk, Earth system scientists are particularly concerned about tipping elements, large-scale components of the Earth system that can be switched into qualitatively different states by small perturbations. Despite growing evidence that tipping elements exist in the climate system, whether large-scale vegetation systems can tip into alternative states is poorly understood. Here we show that tropical grassland, savanna and forest ecosystems, areas large enough to have powerful impacts on the Earth system, are likely to shift to alternative states. Specifically, we show that increasing atmospheric CO2 concentration will force transitions to vegetation states characterized by higher biomass and/or woody-plant dominance. The timing of these critical transitions varies as a result of between-site variance in the rate of temperature increase, as well as a dependence on stochastic variation in fire severity and rainfall. We further show that the locations of bistable vegetation zones (zones where alternative vegetation states can exist) will shift as climate changes. We conclude that even though large-scale directional regime shifts in terrestrial ecosystems are likely, asynchrony in the timing of these shifts may serve to dampen, but not nullify, the shock that these changes may represent to the Earth system.

Allometric equations for integrating remote sensing imagery into forest monitoring programmes.

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed - specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.

Invasive plants have broader physiological niches.

Invasive species cost the global economy billions of dollars each year, but ecologists have struggled to predict the risk of an introduced species naturalizing and invading. Although carefully designed experiments are needed to fully elucidate what makes some species invasive, much can be learned from unintentional experiments involving the introduction of species beyond their native ranges. Here, we assess invasion risk by linking a physiologically based species distribution model with data on the invasive success of 749 Australian acacia and eucalypt tree species that have, over more than a century, been introduced around the world. The model correctly predicts 92% of occurrences observed outside of Australia from an independent dataset. We found that invasiveness is positively associated with the projection of physiological niche volume in geographic space, thereby illustrating that species tolerant of a broader range of environmental conditions are more likely to be invasive. Species achieve this broader tolerance in different ways, meaning that the traits that define invasive success are context-specific. Hence, our study reconciles studies that have failed to identify the traits that define invasive success with the urgent and pragmatic need to predict invasive success.

Defining functional biomes and monitoring their change globally.

Biomes are important constructs for organizing understanding of how the worlds' major terrestrial ecosystems differ from one another and for monitoring change in these ecosystems. Yet existing biome classification schemes have been criticized for being overly subjective and for explicitly or implicitly invoking climate. We propose a new biome map and classification scheme that uses information on (i) an index of vegetation productivity, (ii) whether the minimum of vegetation activity is in the driest or coldest part of the year, and (iii) vegetation height. Although biomes produced on the basis of this classification show a strong spatial coherence, they show little congruence with existing biome classification schemes. Our biome map provides an alternative classification scheme for comparing the biogeochemical rates of terrestrial ecosystems. We use this new biome classification scheme to analyse the patterns of biome change observed over recent decades. Overall, 13% to 14% of analysed pixels shifted in biome state over the 30-year study period. A wide range of biome transitions were observed. For example, biomes with tall vegetation and minimum vegetation activity in the cold season shifted to higher productivity biome states. Biomes with short vegetation and low seasonality shifted to seasonally moisture-limited biome states. Our findings and method provide a new source of data for rigorously monitoring global vegetation change, analysing drivers of vegetation change and for benchmarking models of terrestrial ecosystem function.

Climate change and long-term fire management impacts on Australian savannas.

Tropical savannas cover a large proportion of the Earth's land surface and many people are dependent on the ecosystem services that savannas supply. Their sustainable management is crucial. Owing to the complexity of savanna vegetation dynamics, climate change and land use impacts on savannas are highly uncertain. We used a dynamic vegetation model, the adaptive dynamic global vegetation model (aDGVM), to project how climate change and fire management might influence future vegetation in northern Australian savannas. Under future climate conditions, vegetation can store more carbon than under ambient conditions. Changes in rainfall seasonality influence future carbon storage but do not turn vegetation into a carbon source, suggesting that CO2 fertilization is the main driver of vegetation change. The application of prescribed fires with varying return intervals and burning season influences vegetation and fire impacts. Carbon sequestration is maximized with early dry season fires and long fire return intervals, while grass productivity is maximized with late dry season fires and intermediate fire return intervals. The study has implications for management policy across Australian savannas because it identifies how fire management strategies may influence grazing yield, carbon sequestration and greenhouse gas emissions. This knowledge is crucial to maintaining important ecosystem services of Australian savannas.