| 1. |
- Haverd, V., et al.
(författare)
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Coupling carbon allocation with leaf and root phenology predicts tree–grass partitioning along a savanna rainfall gradient
- 2016
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 13:3, s. 761-779
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Tidskriftsartikel (refereegranskat)abstract
- The relative complexity of the mechanisms underlying savanna ecosystem dynamics, in comparison to other biomes such as temperate and tropical forests, challenges the representation of such dynamics in ecosystem and Earth system models. A realistic representation of processes governing carbon allocation and phenology for the two defining elements of savanna vegetation (namely trees and grasses) may be a key to understanding variations in tree–grass partitioning in time and space across the savanna biome worldwide. Here we present a new approach for modelling coupled phenology and carbon allocation, applied to competing tree and grass plant functional types. The approach accounts for a temporal shift between assimilation and growth, mediated by a labile carbohydrate store. This is combined with a method to maximize long-term net primary production (NPP) by optimally partitioning plant growth between fine roots and (leaves + stem). The computational efficiency of the analytic method used here allows it to be uniquely and readily applied at regional scale, as required, for example, within the framework of a global biogeochemical model. We demonstrate the approach by encoding it in a new simple carbon–water cycle model that we call HAVANA (Hydrology and Vegetation-dynamics Algorithm for Northern Australia), coupled to the existing POP (Population Orders Physiology) model for tree demography and disturbance-mediated heterogeneity. HAVANA-POP is calibrated using monthly remotely sensed fraction of absorbed photosynthetically active radiation (fPAR) and eddy-covariance-based estimates of carbon and water fluxes at five tower sites along the North Australian Tropical Transect (NATT), which is characterized by large gradients in rainfall and wildfire disturbance. The calibrated model replicates observed gradients of fPAR, tree leaf area index, basal area, and foliage projective cover along the NATT. The model behaviour emerges from complex feedbacks between the plant physiology and vegetation dynamics, mediated by shifting above- versus below-ground resources, and not from imposed hypotheses about the controls on tree–grass co-existence. Results support the hypothesis that resource limitation is a stronger determinant of tree cover than disturbance in Australian savannas.
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| 2. |
- Lin, Yan-Shih, et al.
(författare)
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Optimal stomatal behaviour around the world
- 2015
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Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Stomatal conductance (gs) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycle changes, a globalscale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. Here,we present a database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model1 and the leaf and wood economics spectrum2,3.We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of gs across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.
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| 3. |
- Lin, Yan-Shih, et al.
(författare)
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Optimal stomatal behaviour around the world
- 2015
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Ingår i: Nature Climate Change. - 1758-6798 .- 1758-678X. ; 5:5, s. 459-464
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Tidskriftsartikel (refereegranskat)abstract
- Stomatal conductance (g(s)) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g(s) in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g(s) that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g(s) obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model(1) and the leaf and wood economics spectrum(2,3). We also demonstrate a global relationship with climate. These findin g(s) provide a robust theoretical framework for understanding and predicting the behaviour of g(s) across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.
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| 4. |
- Yi, Chuixiang, et al.
(författare)
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Climate control of terrestrial carbon exchange across biomes and continents
- 2010
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 5:3
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Tidskriftsartikel (refereegranskat)abstract
- Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate-carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid-and high-latitudes, (2) a strong function of dryness at mid-and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45 degrees N). The sensitivity of NEE to mean annual temperature breaks down at similar to 16 degrees C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence.
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| 5. |
- Whitley, Rhys, et al.
(författare)
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A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas
- 2016
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 13:11, s. 3245-3265
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Tidskriftsartikel (refereegranskat)abstract
- The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough, enabling the extraction of deep soil-water stores to maintain photosynthesis and transpiration during the dry season. Second, models must treat grasses as a co-dominant interface for water and carbon exchange rather than a secondary one to trees. Third, models need a dynamic representation of LAI that encompasses the dynamic phenology of savanna vegetation and its response to rainfall interannual variability. We believe that this study is the first to assess how well TBMs simulate savanna ecosystems and that these results will be used to improve the representation of savannas ecosystems in future global climate model studies.
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| 6. |
- Whitley, Rhys, et al.
(författare)
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Challenges and opportunities in land surface modelling of savanna ecosystems
- 2017
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:20, s. 4711-4732
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Tidskriftsartikel (refereegranskat)abstract
- The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs), which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not) represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model benchmarking and intercomparison frameworks to diagnose the performance of TBMs in this environment and formulate road maps for future development. Our investigation reveals that many TBMs systematically misrepresent phenology, the effects of fire and root-water access (if they are considered at all) and that these should be critical areas for future development. Furthermore, such processes must not be static (i.e. prescribed behaviour) but be capable of responding to the changing environmental conditions in order to emulate the dynamic behaviour of savannas. Without such developments, however, TBMs will have limited predictive capability in making the critical projections needed to understand how savannas will respond to future global change.
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