Dynamic global vegetation models (DGVMs) are powerful tools to project past, current and future vegetation patterns and associated biogeochemical cycles. However, most models are limited by how they ...define vegetation and by their simplistic representation of competition.
We discuss how concepts from community assembly theory and coexistence theory can help to improve vegetation models. We further present a trait- and individual-based vegetation model (aDGVM2) that allows individual plants to adopt a unique combination of trait values. These traits define how individual plants grow and compete. A genetic optimization algorithm is used to simulate trait inheritance and reproductive isolation between individuals. These model properties allow the assembly of plant communities that are adapted to a site's biotic and abiotic conditions.
The aDGVM2 simulates how environmental conditions influence the trait spectra of plant communities; that fire selects for traits that enhance fire protection and reduces trait diversity; and the emergence of life-history strategies that are suggestive of colonization–competition trade-offs.
The aDGVM2 deals with functional diversity and competition fundamentally differently from current DGVMs. This approach may yield novel insights as to how vegetation may respond to climate change and we believe it could foster collaborations between functional plant biologists and vegetation modellers.
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.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Recent IPCC projections suggest that Africa will be subject to particularly severe changes in atmospheric conditions. How the vegetation of Africa and particularly the grassland-savanna-forest ...complex will respond to these changes has rarely been investigated. Most studies on global carbon cycles use vegetation models that do not adequately account for the complexity of the interactions that shape the distribution of tropical grasslands, savannas and forests. This casts doubt on their ability to reliably simulate the future vegetation of Africa. We present a new vegetation model, the adaptive dynamic global vegetation model (aDGVM) that was specifically developed for tropical vegetation. The aDGVM combines established components from existing DGVMs with novel process-based and adaptive modules for phenology, carbon allocation and fire within an individual-based framework. Thus, the model allows vegetation to adapt phenology, allocation and physiology to changing environmental conditions and disturbances in a way not possible in models based on fixed functional types. We used the model to simulate the current vegetation patterns of Africa and found good agreement between model projections and vegetation maps. We simulated vegetation in absence of fire and found that fire suppression strongly influences tree dominance at the regional scale while at a continental scale fire suppression increases biomass in vegetation by a more modest 13%. Simulations under elevated temperature and atmospheric CO₂ concentrations predicted longer growing periods, higher allocation to roots, higher fecundity, more biomass and a dramatic shift toward tree dominated biomes. Our analyses suggest that the CO₂ fertilization effect is not saturated at ambient CO₂ levels and will strongly increase in response to further increases in CO₂ levels. The model provides a general and flexible framework for describing vegetation response to the interactive effects of climate and disturbances.
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.
In this study, we explored how rainfall manipulation influenced competitive interactions between grasses and juvenile trees (small nonreproductive trees capable of resprouting) in savanna. To do ...this, we manipulated rainfall amount in the field using an incomplete factorial experiment that determined the effects of rainfall reduction, no manipulation, rainfall addition, and competition between grasses and trees on grass and tree growth. As response variables, we focused on several measures of tree growth and Disc Pasture Meter settling height as an estimate of grass aboveground biomass. We conducted the study over four years, at two sites in the Kruger National Park, South Africa. Our results show that rainfall manipulation did not have substantial effects on any of the measures of tree growth we considered. However, trees at plots where grasses had been removed grew on average 15 cm more in height and 1.3-1.7 times more in basal area per year than those in plots with grasses. Grass biomass was not influenced by the presence of trees but was significantly and positively influenced by rainfall addition. These findings were not fundamentally influenced by soil type or by prevailing precipitation, suggesting applicability of our results to a wide range of savannas. Our results suggest that, in savannas, increasing rainfall serves to increase the competitive pressure exerted by grasses on trees. The implication is that recruitment into the adult tree stage from the juvenile stage is most likely in drought years when there is little competition from grass for resources and grass fuel loads are low.
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.
Climate change and elevated CO2 are expected to drive vegetation changes in Africa. We used an ensemble of dynamic vegetation model simulations to assess the impacts of these drivers on carbon stocks and biomes until 2099. Climate change and elevated CO2 led to an 18% to 61% increase in carbon stocks, which was primarily driven by CO2 fertilization. Associated biome changes are likely across Africa, especially changes from savanna to forest. Disabling CO2 fertilization resulted in a −22% to +11% change in carbons stocks. These large uncertainties in future projections imply that adaptation strategies need to be flexible.
Aim It remains poorly understood why the position of the forest–savanna biome boundary, in a domain defined by precipitation and temperature, differs in South America, Africa and Australia. Process ...based Dynamic Global Vegetation Models (DGVMs) are a valuable tool to investigate the determinants of vegetation distributions; however, many DGVMs fail to predict the spatial distribution or indeed presence of the South American savanna biome. Evidence suggests that fire plays a significant role in mediating forest–savanna biome boundaries; however, fire alone appears to be insufficient to predict these boundaries in South America. We hypothesize that interactions between precipitation, constraints on tree rooting depth and fire affect the probability of savanna occurrence and the position of the savanna–forest boundary. Location Tropical forest and savanna sites in Brazil and Venezuela north of 23°S. Methods We tested our hypotheses using a novel DGVM, aDGVM2, which allows plant trait spectra, constrained by trade-offs between traits, to evolve in response to abiotic and biotic conditions. Plant hydraulics is represented by the cohesion–tension theory, this allowed us to explore how soil and plant hydraulics control biome distributions and plant traits. The resulting community trait distributions are emergent properties of model dynamics. Results We showed that across much of South America the biome state is not determined by climate alone. Interactions between plant rooting depth, fire and precipitation affected the probability of observing a given biome state and the emergent traits of plant communities. Simulations where plant rooting depth varied in space provided the best match to satellite derived biomass estimates and generated biome distributions that reproduced contemporary biome maps well. Main conclusions Our findings support the contention that areas where multiple vegetation states are possible are widespread and highlight the importance of considering the influence of fire and constraints on plant rooting depth for predicting biome boundaries.
Ecologists have long sought to understand the factors controlling the structure of savanna vegetation. Using data from 2154 sites in savannas across Africa, Australia, and South America, we found ...that increasing moisture availability drives increases in fire and tree basal area, whereas fire reduces tree basal area. However, among continents, the magnitude of these effects varied substantially, so that a single model cannot adequately represent savanna woody biomass across these regions. Historical and environmental differences drive the regional variation in the functional relationships between woody vegetation, fire, and climate. These same differences will determine the regional responses of vegetation to future climates, with implications for global carbon stocks.
Ecosystem Assembly Higgins, Steven I.
Ecosystems (New York),
01/2017, Letnik:
20, Številka:
1
Journal Article
Recenzirano
Organisms not only respond to their environment but also influence the availability of resources and change environmental conditions. Hence, the impacts of organisms on their environment shape the ...selective regimes that drive, on ecological time scales, the assembly of ecological communities and, on evolutionary time scales, diversification. Recent studies have drawn attention to the fact that feedbacks between organisms and the environment can prevent or induce catastrophic transitions in ecosystem states and argue that climate change increases the likelihood of such catastrophic regime shifts. Ecologists have very limited ability to predict the likelihood of such regime shifts or the properties of the ecosystems that assemble after such collapses. This is because ecology does not have a theory of ecosystem assembly, nor does it have an established way of translating such a theory into models capable of predicting future ecosystem states. Without knowing these potential endpoints, we cannot develop strategies for coercing ecosystems into desired states, severely constraining our capacity to mitigate climate change and climate change impacts. This paper outlines a roadmap for developing a theory of terrestrial ecosystem assembly. Recent progress in dynamic global vegetation modelling and community assembly provides a useful foundation for a theory of ecosystem assembly. Environmental filtering and limiting similarity are key principles, but to be useful, they need to be linked to resource consumption and environmental modulation, and be more strongly constrained by biophysics and the trade-offs defined by biophysical principles. Such a theory recognises that ecological and evolutionary history ensures that many different ecosystem assemblies are possible at any given point in space and time.
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