129 resultados para Terrestrial ecosystem

em CentAUR: Central Archive University of Reading - UK


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We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) of CO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration, were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving >80% success rate and mean NEE confidence intervals <110 gC m−2 year−1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence intervals on annual NEE increased by 30% when observed data were used instead of synthetic data, reflecting and quantifying the addition of model error. Finally, our analyses indicated that incorporating additional constraints, using data on C pools (wood, soil and fine roots) would help to reduce uncertainties for model parameters poorly served by eddy covariance data.

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Many atmospheric constituents besides carbon dioxide (CO2) contribute to global warming, and it is common to compare their influence on climate in terms of radiative forcing, which measures their impact on the planetary energy budget. A number of recent studies have shown that many radiatively active constituents also have important impacts on the physiological functioning of ecosystems, and thus the ‘ecosystem services’ that humankind relies upon. CO2 increases have most probably increased river runoff and had generally positive impacts on plant growth where nutrients are non-limiting, whereas increases in near-surface ozone (O3) are very detrimental to plant productivity. Atmospheric aerosols increase the fraction of surface diffuse light, which is beneficial for plant growth. To illustrate these differences, we present the impact on net primary productivity and runoff of higher CO2, higher near-surface O3, and lower sulphate aerosols, and for equivalent changes in radiative forcing.We compare this with the impact of climate change alone, arising, for example, from a physiologically inactive gas such as methane (CH4). For equivalent levels of change in radiative forcing, we show that the combined climate and physiological impacts of these individual agents vary markedly and in some cases actually differ in sign. This study highlights the need to develop more informative metrics of the impact of changing atmospheric constituents that go beyond simple radiative forcing.

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Targets for stabilizing climate change are often based on considerations of the impacts of different levels of global warming, usually assessing the time of reaching a particular level of warming. However, some aspects of the Earth system, such as global mean temperatures1 and sea level rise due to thermal expansion2 or the melting of large ice sheets3, continue to respond long after the stabilization of radiative forcing. Here we use a coupled climate–vegetation model to show that in turn the terrestrial biosphere shows significant inertia in its response to climate change. We demonstrate that the global terrestrial biosphere can continue to change for decades after climate stabilization. We suggest that ecosystems can be committed to long-term change long before any response is observable: for example, we find that the risk of significant loss of forest cover in Amazonia rises rapidly for a global mean temperature rise above 2 °C. We conclude that such committed ecosystem changes must be considered in the definition of dangerous climate change, and subsequent policy development to avoid it.

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A dead mammal (i.e. cadaver) is a high quality resource (narrow carbon:nitrogen ratio, high water content) that releases an intense, localised pulse of carbon and nutrients into the soil upon decomposition. Despite the fact that as much as 5,000 kg of cadaver can be introduced to a square kilometre of terrestrial ecosystem each year, cadaver decomposition remains a neglected microsere. Here we review the processes associated with the introduction of cadaver-derived carbon and nutrients into soil from forensic and ecological settings to show that cadaver decomposition can have a greater, albeit localised, effect on belowground ecology than plant and faecal resources. Cadaveric materials are rapidly introduced to belowground floral and faunal communities, which results in the formation of a highly concentrated island of fertility, or cadaver decomposition island (CDI). CDIs are associated with increased soil microbial biomass, microbial activity (C mineralisation) and nematode abundance. Each CDI is an ephemeral natural disturbance that, in addition to releasing energy and nutrients to the wider ecosystem, acts as a hub by receiving these materials in the form of dead insects, exuvia and puparia, faecal matter (from scavengers, grazers and predators) and feathers (from avian scavengers and predators). As such, CDIs contribute to landscape heterogeneity. Furthermore, CDIs are a specialised habitat for a number of flies, beetles and pioneer vegetation, which enhances biodiversity in terrestrial ecosystems.

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This paper discusses the risks of a shutdown of the thermohaline circulation (THC) for the climate system, for ecosystems in and around the North Atlantic as well as for fisheries and agriculture by way of an Integrated Assessment. The climate model simulations are based on greenhouse gas scenarios for the 21st century and beyond. A shutdown of the THC, complete by 2150, is triggered if increased freshwater input from inland ice melt or enhanced runoff is assumed. The shutdown retards the greenhouse gas-induced atmospheric warming trend in the Northern Hemisphere, but does not lead to a persistent net cooling. Due to the simulated THC shutdown the sea level at the North Atlantic shores rises by up to 80 cm by 2150, in addition to the global sea level rise. This could potentially be a serious impact that requires expensive coastal protection measures. A reduction of marine net primary productivity is associated with the impacts of warming rather than a THC shutdown. Regional shifts in the currents in the Nordic Seas could strongly deteriorate survival chances for cod larvae and juveniles. This could lead to cod fisheries becoming unprofitable by the end of the 21st century. While regional socioeconomic impacts might be large, damages would be probably small in relation to the respective gross national products. Terrestrial ecosystem productivity is affected much more by the fertilization from the increasing CO2 concentration than by a THC shutdown. In addition, the level of warming in the 22nd to 24th century favours crop production in northern Europe a lot, no matter whether the THC shuts down or not. CO2 emissions corridors aimed at limiting the risk of a THC breakdown to 10% or less are narrow, requiring departure from business-as-usual in the next few decades. The uncertainty about THC risks is still high. This is seen in model analyses as well as in the experts’ views that were elicited. The overview of results presented here is the outcome of the Integrated Assessment project INTEGRATION.

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We present an approach for dealing with coarse-resolution Earth observations (EO) in terrestrial ecosystem data assimilation schemes. The use of coarse-scale observations in ecological data assimilation schemes is complicated by spatial heterogeneity and nonlinear processes in natural ecosystems. If these complications are not appropriately dealt with, then the data assimilation will produce biased results. The “disaggregation” approach that we describe in this paper combines frequent coarse-resolution observations with temporally sparse fine-resolution measurements. We demonstrate the approach using a demonstration data set based on measurements of an Arctic ecosystem. In this example, normalized difference vegetation index observations are assimilated into a “zero-order” model of leaf area index and carbon uptake. The disaggregation approach conserves key ecosystem characteristics regardless of the observation resolution and estimates the carbon uptake to within 1% of the demonstration data set “truth.” Assimilating the same data in the normal manner, but without the disaggregation approach, results in carbon uptake being underestimated by 58% at an observation resolution of 250 m. The disaggregation method allows the combination of multiresolution EO and improves in spatial resolution if observations are located on a grid that shifts from one observation time to the next. Additionally, the approach is not tied to a particular data assimilation scheme, model, or EO product and can cope with complex observation distributions, as it makes no implicit assumptions of normality.

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Steady state and dynamic models have been developed and applied to the River Kennet system. Annual nitrogen exports from the land surface to the river have been estimated based on land use from the 1930s and the 1990s. Long term modelled trends indicate that there has been a large increase in nitrogen transport into the river system driven by increased fertiliser application associated with increased cereal production, increased population and increased livestock levels. The dynamic model INCA Integrated Nitrogen in Catchments. has been applied to simulate the day-to-day transport of N from the terrestrial ecosystem to the riverine environment. This process-based model generates spatial and temporal data and reproduces the observed instream concentrations. Applying the model to current land use and 1930s land use indicates that there has been a major shift in the short term dynamics since the 1930s, with increased river and groundwater concentrations caused by both non-point source pollution from agriculture and point source discharges. �

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The terrestrial biosphere is subjected to a wide range of natural climatic oscillations. Best known is the El Niño–southern oscillation (ENSO) that exerts globally extensive impacts on crops and natural vegetation. A 50-year time series of ENSO events has been analysed to determine those geographical areas that are reliably impacted by ENSO events. Most areas are impacted by changes in precipitation; however, the Pacific Northwest is warmed by El Niño events. Vegetation gross primary production (GPP) has been simulated for these areas, and tests well against independent satellite observations of the normalized difference vegetation index. Analyses of selected geographical areas indicate that changes in GPP often lead to significant changes in ecosystem structure and dynamics. The Pacific decadal oscillation (PDO) is another climatic oscillation that originates from the Pacific and exerts global impacts that are rather similar to ENSO events. However, the longer period of the PDO provided two phases in the time series with a cool phase from 1951 to 1976 and a warm phase from 1977 to 2002. It was notable that the cool phase of the PDO acted additively with cool ENSO phases to exacerbate drought in the earlier period for the southwest USA. By contrast in India, the cool phase of the PDO appears to reduce the negative impacts of warm ENSO events on crop production.

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Aim Earth observation (EO) products are a valuable alternative to spectral vegetation indices. We discuss the availability of EO products for analysing patterns in macroecology, particularly related to vegetation, on a range of spatial and temporal scales. Location Global. Methods We discuss four groups of EO products: land cover/cover change, vegetation structure and ecosystem productivity, fire detection, and digital elevation models. We address important practical issues arising from their use, such as assumptions underlying product generation, product accuracy and product transferability between spatial scales. We investigate the potential of EO products for analysing terrestrial ecosystems. Results Land cover, productivity and fire products are generated from long-term data using standardized algorithms to improve reliability in detecting change of land surfaces. Their global coverage renders them useful for macroecology. Their spatial resolution (e.g. GLOBCOVER vegetation, 300 m; MODIS vegetation and fire, ≥ 500 m; ASTER digital elevation, 30 m) can be a limiting factor. Canopy structure and productivity products are based on physical approaches and thus are independent of biome-specific calibrations. Active fire locations are provided in near-real time, while burnt area products show actual area burnt by fire. EO products can be assimilated into ecosystem models, and their validation information can be employed to calculate uncertainties during subsequent modelling. Main conclusions Owing to their global coverage and long-term continuity, EO end products can significantly advance the field of macroecology. EO products allow analyses of spatial biodiversity, seasonal dynamics of biomass and productivity, and consequences of disturbances on regional to global scales. Remaining drawbacks include inter-operability between products from different sensors and accuracy issues due to differences between assumptions and models underlying the generation of different EO products. Our review explains the nature of EO products and how they relate to particular ecological variables across scales to encourage their wider use in ecological applications.

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Atmospheric CO2 concentration has varied from minima of 170-200 ppm in glacials to maxima of 280-300 ppm in the recent interglacials. Photosynthesis by C-3 plants is highly sensitive to CO2 concentration variations in this range. Physiological consequences of the CO2 changes should therefore be discernible in palaeodata. Several lines of evidence support this expectation. Reduced terrestrial carbon storage during glacials, indicated by the shift in stable isotope composition of dissolved inorganic carbon in the ocean, cannot be explained by climate or sea-level changes. It is however consistent with predictions of current process-based models that propagate known physiological CO2 effects into net primary production at the ecosystem scale. Restricted forest cover during glacial periods, indicated by pollen assemblages dominated by non-arboreal taxa, cannot be reproduced accurately by palaeoclimate models unless CO2 effects on C-3-C-4 plant competition are also modelled. It follows that methods to reconstruct climate from palaeodata should account for CO2 concentration changes. When they do so, they yield results more consistent with palaeoclimate models. In conclusion, the palaeorecord of the Late Quaternary, interpreted with the help of climate and ecosystem models, provides evidence that CO2 effects at the ecosystem scale are neither trivial nor transient.

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Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based top-down) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory predicts how the average residence time of carbon molecules, total system throughflow (TST), and amount of recycling vary with the body size and temperature of the organisms and with trophic organization. We evaluate the theory by comparing theoretical predictions with outputs of numerical models designed to simulate diverse ecosystem types and with empirical data for real ecosystems. Although residence times within different ecosystems vary by orders of magnitude—from weeks in warm pelagic oceans with minute phytoplankton producers to centuries in cold forests with large tree producers—as predicted, all ecosystems fall along a single line: residence time increases linearly with slope = 1.0 with the ratio of whole-ecosystem biomass to primary productivity (B/P). TST was affected predominantly by primary productivity and recycling by the transfer of energy from microbial decomposers to animal consumers. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere.