| 1. |
- Boke-Olén, Niklas, et al.
(författare)
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Analyzing savannah vegetation phenology with remotely sensed data, lagged time-series models and phenopictures
- 2016
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Konferensbidrag (refereegranskat)abstract
- It is predicted that savannah regions will see changes in precipitation patterns due to current climate change pro-jections. The change will most likely affect leaf phenology which controls net primary production. It is thereforeimportant to; 1) study those changes and its drivers, 2) to be able to correctly model the changes to vegetationphenology due to climate change. To our knowledge there is no existing global savannah phenology model thatcan capture both the phenological events and the vegetation state between the events. We therefore, investigate howday length, mean annual precipitation and soil moisture affects and controls the vegetation phenology of savannahs(using MODIS NDVI as a proxy for phenological state) with a lagged time series model for global application. Wefurthermore use phenological pictures (phenopictures) to investigate savannah tree and grass phenology. Phenopic-tures are pictures taken with a digital time-lapse camera with the purpose of recording and studying phenologicalevents. We used climate data from 15 flux towers sites located in 4 continents together with normalized differencevegetation index from MODIS for the model development. Two of the sites located in Africa were further ana-lyzed using phenopictures. The developed model identified all three considered variables as usable for modellingof savannah leaf phenology but showed some inconsistent result for some of the sites indicating the difficultiesin creating a simple common model that works equally well across sites. We attribute some of these difficultiesto site specific differences (e.g. grazing or tree and grass ratio) that the simplified model did not consider. Butwe expect it to on average give the cross-validated result (r2= 0.6, RMSE = 0.1) when applied to other savannahareas. The preliminary analysis of the phenological pictures with respect to tree and grass to some extent supportthis by showing differences in the start of the leaves development in the beginning of the season. However, thisdiffered between the two studied sites which further highlights the difficulties in creating a common model thatworks equally well for individual sites.
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| 2. |
- Boke-Olén, Niklas, et al.
(författare)
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Estimating and analyzing savannah phenology with a lagged time series model
- 2016
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:4
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Tidskriftsartikel (refereegranskat)abstract
- Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.
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| 3. |
- 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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| 4. |
- Lundberg, Angela, et al.
(författare)
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Albedo and snowmelt rates across a tundra-to-forest transition
- 2005
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Ingår i: Proceedings of the 15 northern research basins international symposium and workshop. - Lund : Department of Water Resources Engineering, Lund University. ; , s. 1-10
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Konferensbidrag (refereegranskat)abstract
- Arctic ecosystems play an important role in the functioning of the earth system because they occupy a large area, are sensitive to climate changes and could feedback to affect regional and global climate, Albedo and melt rates measured at a tundra, shrub and forest site at Council (ca 64 54N) and at a tundra site at Ivotuk (ca 68 29N) in Alaska during the snowmelt period in year 2000 showed that the difference in the timing of snowmelt was greater between vegetation types (13 days between shrub and tundra) than between the two sites of different latitude (7days between the two tundra sites with 3.6 difference in latitude). Hence any increase in the abundance and distribution of shrubs and forest could result in earlier spring melt. That the absorption of radiation used for snowmelt was greater for the shrub site than for the other sites was confirmed by degree-index simulations where the shrub site (8.2 mm C۫- 1day-1) required a much larger degree-index than the other sites (forest 3.44 mm C۫-1day-1and 4.1 tundra mm C۫-1day-1) i۫n order to correctly simulate the melt rate. The impacts of changes in snowmelt are not restricted to impacts on surface fluxes but potentially also on hydrological process, regional climate, nutrient and pollutant fluxes.
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| 5. |
- Mallick, Kaniska, et al.
(författare)
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A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes
- 2014
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 141:5, s. 243-261
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Tidskriftsartikel (refereegranskat)abstract
- The use of Penman-Monteith (PM) equation in thermal remote sensing based surface energy balance modeling is not prevalent due to the unavailability of any direct method to integrate thermal data into the PM equation and due to the lack of physical models expressing the surface (or stomatal) and boundary layer conductances (g(S) and g(B)) as a function of surface temperature. Here we demonstrate a new method that physically integrates the radiometric surface temperature (T-S) into the PM equation for estimating the terrestrial surface energy balance fluxes (sensible heat, H and latent heat, lambda E). The method combines satellite T-S data with standard energy balance closure models in order to derive a hybrid closure that does not require the specification of surface to atmosphere conductance terms. We call this the Surface Temperature Initiated Closure (STIC), which is formed by the simultaneous solution of four state equations. Taking advantage of the psychrometric relationship between temperature and vapor pressure, the present method also estimates the near surface moisture availability (M) from T-S, air temperature (T-A) and relative humidity (R-H), thereby being capable of decomposing lambda E into evaporation (lambda E-E) and transpiration (lambda E-T). STIC is driven with T-S, T-A, R-H, net radiation (R-N), and ground heat flux (G). T-S measurements from both MODIS Terra (MOD11A2) and Aqua (MYD11A2) were used in conjunction with FLUXNET R-N, G, T-A, R-H, lambda E and H measurements corresponding to the MODIS equatorial crossing time. The performance of STIC has been evaluated in comparison to the eddy covariance measurements of lambda E and H at 30 sites that cover a broad range of biomes and climates. We found a RMSE of 37.79 (11%) (with MODIS Terra T-S) and 44.27 W m(-2) (15%) (with MODIS Aqua T-S) in lambda E estimates, while the RMSE was 37.74(9%) (with Terra) and 44.72 W m(-2) (8%) (with Aqua) in H. STIC could efficiently capture the lambda E dynamics during the dry down period in the semi-arid landscapes where lambda E is strongly governed by the subsurface soil moisture and where the majority of other lambda E models generally show poor results. Sensitivity analysis revealed a high sensitivity of both the fluxes to the uncertainties in T-S. A realistic response and modest relationship was also found when partitioned lambda E components (lambda E-E and lambda E-T) were compared to the observed soil moisture and rainfall. This is the first study to report the physical integration of T-S into the PM equation and finding analytical solution of the physical (g(B)) and physiological conductances (g(S)). The performance of STIC over diverse biomes and climates points to its potential to benefit future NASA and NOAA missions having thermal sensors, such as HyspIRI, GeoSTAR and GOES-R for mapping multi-scale lambda E and drought. (C) 2013 Elsevier Inc. All rights reserved.
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| 6. |
- Niu, Shuli, et al.
(författare)
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Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms.
- 2012
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Ingår i: New Phytologist. - : Wiley. - 1469-8137 .- 0028-646X. ; 194:3, s. 775-783
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Tidskriftsartikel (refereegranskat)abstract
- • It is well established that individual organisms can acclimate and adapt to temperature to optimize their functioning. However, thermal optimization of ecosystems, as an assemblage of organisms, has not been examined at broad spatial and temporal scales. • Here, we compiled data from 169 globally distributed sites of eddy covariance and quantified the temperature response functions of net ecosystem exchange (NEE), an ecosystem-level property, to determine whether NEE shows thermal optimality and to explore the underlying mechanisms. • We found that the temperature response of NEE followed a peak curve, with the optimum temperature (corresponding to the maximum magnitude of NEE) being positively correlated with annual mean temperature over years and across sites. Shifts of the optimum temperature of NEE were mostly a result of temperature acclimation of gross primary productivity (upward shift of optimum temperature) rather than changes in the temperature sensitivity of ecosystem respiration. • Ecosystem-level thermal optimality is a newly revealed ecosystem property, presumably reflecting associated evolutionary adaptation of organisms within ecosystems, and has the potential to significantly regulate ecosystem-climate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.
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| 7. |
- Oehri, Jacqueline, et al.
(författare)
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Vegetation type is an important predictor of the arctic summer land surface energy budget
- 2022
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.
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| 8. |
- 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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| 9. |
- 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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| 10. |
- Yao, Yunjun, et al.
(författare)
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Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method
- 2017
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Ingår i: Journal of Hydrology. - : Elsevier BV. - 0022-1694. ; 553, s. 508-526
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Tidskriftsartikel (refereegranskat)abstract
- Estimation of high-resolution terrestrial evapotranspiration (ET) from Landsat data is important in many climatic, hydrologic, and agricultural applications, as it can help bridging the gap between existing coarse-resolution ET products and point-based field measurements. However, there is large uncertainty among existing ET products from Landsat that limit their application. This study presents a simple Taylor skill fusion (STS) method that merges five Landsat-based ET products and directly measured ET from eddy covariance (EC) to improve the global estimation of terrestrial ET. The STS method uses a weighted average of the individual ET products and weights are determined by their Taylor skill scores (S). The validation with site-scale measurements at 206 EC flux towers showed large differences and uncertainties among the five ET products. The merged ET product exhibited the best performance with a decrease in the averaged root-mean-square error (RMSE) by 2–5 W/m2 when compared to the individual products. To evaluate the reliability of the STS method at the regional scale, the weights of the STS method for these five ET products were determined using EC ground-measurements. An example of regional ET mapping demonstrates that the STS-merged ET can effectively integrate the individual Landsat ET products. Our proposed method provides an improved high-resolution ET product for identifying agricultural crop water consumption and providing a diagnostic assessment for global land surface models.
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