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Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate-carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy-covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000-2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r(2) = 0.90) and GPP recovery after a fire disturbance in South Dakota (r(2) = 0.88). Additional analysis of the eddy-covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space.
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Ecossistema , Modelos Biológicos , Fenômenos Fisiológicos Vegetais , Plantas , South DakotaRESUMO
Increased climate variability and extremes are unequivocal with unprecedented impacts on water resources and agriculture production systems. However, little is known about the impacts of climate extremes at the intra-seasonal level which remained largely unexplored. We investigated the coincidence of climate extremes with sensitive crop growth phases of wheat and rice in the Indus, Ganges and Brahmaputra (IGB) river basins of South Asia. We also quantified the related impacts on irrigation water demand (IWD), gross primary production (GPP) and crop yields (CY) simulated by a hydrological-vegetation model (LPJmL) during 1981-2100 using RCP4.5-SSP1 and RCP8.5-SSP3 framework. The climate extremes revealed a higher frequency and intensity during crop growth phases with significant increasing trends in future. Diverse changes in IWD, GPP and CY are projected in future under the influence of crop phase-specific extremes. The crop phase-specific changes in the IWD of wheat and rice will intensify in the future. More than 50 % of the change in future wheat irrigation is caused by warm and dry extremes during the ripening phase. Whereas, increase in IWD for rice is mainly associated with warm extremes only. The crop phase-specific GPP shows a decreasing trend in future for both wheat and rice in the Western part of IGB with the largest decrease during the reproductive phase of wheat (up to 36 %) and vegetative phase of rice (>20 %). This decrease is clearly reflected in seasonal yields i.e., both wheat (20 %) and rice (12 %) showed a decrease in future linked with warm and dry extremes. However, in the Eastern part of IGB, the GPP will mostly increase in future during the three crop phases of wheat and rice. These results can be used to help develop efficient adaptation strategies considering seasonal changes and sensitive crop phases for sustained food and water security in South Asia.
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Imunoglobulinas , Oryza , Rios , Produtos Agrícolas , Mudança Climática , Clima , TriticumRESUMO
⢠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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Dióxido de Carbono/metabolismo , Ecossistema , Plantas/metabolismo , Temperatura , Aclimatação , Dióxido de Carbono/efeitos da radiação , Mudança Climática , Plantas/efeitos da radiação , Chuva , Energia SolarRESUMO
Better insight in the possible range of future N2O emissions can help to construct mitigation and adaptation strategies and to adapt land use planning and management to climate objectives. The Dutch fen meadow landscape is a hotspot of N2O emission due to high nitrogen inputs combined with moist peat soils due to land use change. Socio-economic developments in the area are expected to have major impacts on N2O emission. The goals of this study are to estimate changes in N2O emissions for the period 2006-2040 under three different scenarios for the Dutch fen meadow landscape (rural production, rural fragmentation, and rural multifunctionality) and to quantify the share of different emission sources. Three scenarios were constructed and quantified based on the Story-And-Simulation approach. The rural production and the rural fragmentation scenarios are characterized by globalization and a market-oriented economy; in the rural production scenario dairy farming has a strong competitive position in the study region, while under the rural fragmentation scenario agriculture is declining. Under the rural multifunctionality scenario, the global context is characterized by regionalization and stronger regulation toward environmental issues. The N2O emission decreased between 2006 and 2040 under all scenarios. Under the rural production scenario, the N2O emission decreased by 7%. Due to measures to limit peat mineralization and policies to reduce agricultural emissions, the rural multifunctionality scenario showed the largest decrease in N2O emissions (44%). Under the rural fragmentation scenario, in which the dairy farming sector is diminished, the emission decreased by 33%. Compared to other uncertainties involved in N2O emission estimates, the uncertainty due to possible future land use change is relatively large and assuming a constant emission with time is therefore not appropriate.
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Monitoramento Ambiental , Poluentes Ambientais/análise , Óxido Nitroso/análise , Modelos Teóricos , Países Baixos , Óxido Nitroso/química , IncertezaRESUMO
Climate change is recognized as one of the greatest challenges of 21st century. This study investigated climate and hydrological regimes of the high-altitude Indus basin for the historical period and extreme scenarios of future climate during 21st century. Improved datasets of precipitation and temperature were developed and forced to a fully-distributed physically-based energy-balance Variable Infiltration Capacity (VIC) hydrological model to simulate the water balance at regional and sub-basin scale. Relative to historical baseline, the results revealed highly contrasting signals of climate and hydrological regime changes. Against an increase of 0.6 °C during the last 40 years, the median annual air temperature is projected to increase further between 0.8 and 5.7 °C by the end of 21st century. Similarly, a decline of 11.9% in annual precipitation is recorded, but future projections are highly conflicting and spatially variable. The Karakoram region is anticipated to receive more precipitation, while SW-Hindukush and parts of W-Himalayan region may experience decline in precipitation. The Model for Interdisciplinary Research On Climate version-5 (MIROC5) generally shows increases, while Max Planck Institute Earth System Model at base resolution (MPI-ESM-LR) indicates decreases in precipitation and river inflows under three Representative Concentration Pathways (RCPs) of 2.6, 4.5 and 8.5. Indus-Tarbela inflows are more likely to increase compared to Kabul, Jhelum and Chenab river inflows. Substantial increase in the magnitudes of peak flows and one-month earlier attainment is projected for all river gauges. High flows are anticipated to increase under most scenarios, while low flows may decrease for MPI-ESM-LR in Jhelum, Chenab and Kabul river basins. Hence, hydrological extremes are likely to be intensified. Critical modifications in the strategies and action plans for hydropower generation, construction and operation of storage reservoirs, irrigation withdrawals, flood control and drought management will be required to optimally manage water resources in the basin.
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Flux measurements of carbon dioxide and water vapor above tropical rain forests are often difficult to interpret because the terrain is usually complex. This complexity induces heterogeneity in the surface but also affects lateral movement of carbon dioxide (CO2) not readily detected by the eddy covariance systems. This study describes such variability using measurements of CO2 along vertical profiles and along a toposequence in a tropical rain forest near Manaus, Brazil. Seasonal and diurnal variation was recorded, with atmospheric CO2 concentration maxima around dawn, generally higher CO2 build-up in the dry season and stronger daytime CO2 drawdown in the wet season. This variation was reflected all along the toposequence, but the slope and valley bottom accumulated clearly more CO2 than the plateaus, depending on atmospheric stability. Particularly during stable nights, accumulation was along lines of equal altitude, suggesting that large amounts of CO2 are stored in the valleys of the landscape. Flushing of this store only occurs during mid-morning, when stored CO2 may well be partly transported back to the plateaus. It is clear that, for proper interpretation of tower fluxes in such complex and actively respiring terrain, the horizontal variability of storage needs to be taken into account not only during the night but also during the mornings.
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Movimentos do Ar , Dióxido de Carbono/análise , Ecossistema , Monitoramento Ambiental , Árvores/metabolismo , Brasil , Dióxido de Carbono/metabolismo , Ritmo Circadiano , Geografia , Estações do Ano , Clima TropicalRESUMO
This paper presents data on carbon stocks of tropical tree species along a rainfall gradient. The data was generated from the Sesheke, Namwala, and Kabompo sites in Zambia. Though above-ground data was generated for all these three sites, we uprooted trees to determine below-ground biomass from the Sesheke site only. The vegetation was assessed in all three sites. The data includes tree diameter at breast height (DBH), total tree height, wood density, wood dry weight and root dry weight for large (≥ 5â¯cm DBH) and small (< 5â¯cm DBH) trees. We further presented Root-to-Shoot Ratios of uprooted trees. Data on the importance-value indices of various species for large and small trees are also determined. Below and above-ground carbon stocks of the surveyed tree species are presented per site. This data were used by Ngoma et al. (2018) [1] to develop above and below-ground biomass models and the reader is referred to this study for additional information, interpretation, and reflection on applying this data.
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Scarcity of in-situ observations coupled with high orographic influences has prevented a comprehensive assessment of precipitation distribution in the high-altitude catchments of Indus basin. Available data are generally fragmented and scattered with different organizations and mostly cover the valleys. Here, we combine most of the available station data with the indirect precipitation estimates at the accumulation zones of major glaciers to analyse altitudinal dependency of precipitation in the high-altitude Indus basin. The available observations signified the importance of orography in each sub-hydrological basin but could not infer an accurate distribution of precipitation with altitude. We used Kriging with External Drift (KED) interpolation scheme with elevation as a predictor to appraise spatiotemporal distribution of mean monthly, seasonal and annual precipitation for the period of 1998-2012. The KED-based annual precipitation estimates are verified by the corresponding basin-wide observed specific runoffs, which show good agreement. In contrast to earlier studies, our estimates reveal substantially higher precipitation in most of the sub-basins indicating two distinct rainfall maxima; 1st along southern and lower most slopes of Chenab, Jhelum, Indus main and Swat basins, and 2nd around north-west corner of Shyok basin in the central Karakoram. The study demonstrated that the selected gridded precipitation products covering this region are prone to significant errors. In terms of quantitative estimates, ERA-Interim is relatively close to the observations followed by WFDEI and TRMM, while APHRODITE gives highly underestimated precipitation estimates in the study area. Basin-wide seasonal and annual correction factors introduced for each gridded dataset can be useful for lumped hydrological modelling studies, while the estimated precipitation distribution can serve as a basis for bias correction of any gridded precipitation products for the study area.
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The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra- and interspecific trait variation on ecosystem functioning.
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The satellite-derived normalized difference vegetation index (NDVI), which is used for estimating gross primary production (GPP), often includes contributions from both mosses and vascular plants in boreal ecosystems. For the same NDVI, moss can generate only about one-third of the GPP that vascular plants can because of its much lower photosynthetic capacity. Here, based on eddy covariance measurements, we show that the difference in photosynthetic capacity between these two plant functional types has never been explicitly included when estimating regional GPP in the boreal region, resulting in a substantial overestimation. The magnitude of this overestimation could have important implications regarding a change from a current carbon sink to a carbon source in the boreal region. Moss abundance, associated with ecosystem disturbances, needs to be mapped and incorporated into GPP estimates in order to adequately assess the role of the boreal region in the global carbon cycle.
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Briófitas , Ciclo do Carbono , Ecossistema , Fotossíntese , Taiga , Carbono , Dióxido de Carbono , Modelos Biológicos , PlantasRESUMO
This paper gives a synthesis of this special issue on the sensitivity to climate change of the main bio-physical processes in the Hindukush-Karakoram-Himalayas. It also describes the impacts on the water resources with a special focus on the Ganges. Consequences of changes in water resources and possible adaptation measures for different sectors are discussed.
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Mudança Climática , Camada de Gelo , Recursos Hídricos/estatística & dados numéricos , Abastecimento de Água/estatística & dados numéricos , Conservação dos Recursos Naturais , Política Ambiental , Índia , Estações do AnoRESUMO
To set the stage of this special issue this paper gives a short introduction to the sensitivity to climate change of the main bio-physical processes in the Hindukush-Karakoram-Himalayas. It also describes the socio-economic setting of the Ganges basin in northern India as the main focal point of the impact and adaptation studies in this special issue.
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Mudança Climática , Recursos Hídricos/estatística & dados numéricos , Abastecimento de Água/estatística & dados numéricos , Camada de Gelo , Índia , Chuva , NeveRESUMO
Although several studies show the vulnerability of human health to climate change, a clear comprehensive quantification of the increased health risks attributable to climate change is lacking. Even more complicated are assessments of adaptation measures for this sector. We discuss the impact of climate change on diarrhoea as a representative of a waterborne infectious disease affecting human health in the Ganges basin of northern India. A conceptual framework is presented for climate exposure response relationships based on studies from different countries, as empirical studies and appropriate epidemiological data sets for India are lacking. Four climate variables are included: temperature, increased/extreme precipitation, decreased precipitation/droughts and relative humidity. Applying the conceptual framework to the latest regional climate projections for northern India shows increases between present and future (2040s), varying spatially from no change to an increase of 21% in diarrhoea incidences, with 13.1% increase on average for the Ganges basin. We discuss three types of measures against diarrhoeal disease: reactive actions, preventive actions and national policy options. Preventive actions have the potential to counterbalance this expected increase. However, given the limited progress in reducing incidences over the past decade consorted actions and effective implementation and integration of existing policies are needed.
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Mudança Climática , Doenças Transmissíveis/epidemiologia , Diarreia/epidemiologia , Microbiologia da Água , Humanos , Índia , Abastecimento de Água/estatística & dados numéricosRESUMO
Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes.
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Mudança Climática , Clima , Modelos Teóricos , Recursos Hídricos/estatística & dados numéricos , Abastecimento de Água/estatística & dados numéricos , Agricultura , Conservação dos Recursos Naturais , Meio Ambiente , Previsões , Índia , Estações do Ano , TemperaturaRESUMO
We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an 'extra' day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands.