980 resultados para Global Change


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It is increasingly apparent that sea-level data (e.g. microfossil transfer functions, dated coral microatolls and direct observations from satellite and tidal gauges) vary temporally and spatially at regional to local scales, thus limiting our ability to model future sea-level rise for many regions. Understanding sealevel response at ‘far-field’ locations at regional scales is fundamental for formulating more relevant sea-level rise susceptibility models within these regions under future global change projections. Fossil corals and reefs in particular are valuable tools for reconstructing past sea levels and possible environmental phase shifts beyond the temporal constraints of instrumental records. This study used abundant surface geochronological data based on in situ subfossil corals and precise elevation surveys to determine previous sea level in Moreton Bay, eastern Australia, a far-field site. A total of 64 U-Th dates show that relative sea level was at least 1.1 m above modern lowest astronomical tide (LAT) from at least ˜6600 cal. yr BP. Furthermore, a rapid synchronous demise in coral reef growth occurred in Moreton Bay ˜5800 cal. yr BP, coinciding with reported reef hiatus periods in other areas around the Indo-Pacific region. Evaluating past reef growth patterns and phases allows for a better interpretation of anthropogenic forcing versus natural environmental/climatic cycles that effect reef formation and demise at all scales and may allow better prediction of reef response to future global change.

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A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.

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Studies of experimental grassland communities have demonstrated that plant diversity can stabilize productivity through species asynchrony, in which decreases in the biomass of some species are compensated for by increases in others. However, it remains unknown whether these findings are relevant to natural ecosystems, especially those for which species diversity is threatened by anthropogenic global change. Here we analyse diversity-stability relationships from 41 grasslands on five continents and examine how these relationships are affected by chronic fertilization, one of the strongest drivers of species loss globally. Unmanipulated communities with more species had greater species asynchrony, resulting in more stable biomass production, generalizing a result from biodiversity experiments to real-world grasslands. However, fertilization weakened the positive effect of diversity on stability. Contrary to expectations, this was not due to species loss after eutrophication but rather to an increase in the temporal variation of productivity in combination with a decrease in species asynchrony in diverse communities. Our results demonstrate separate and synergistic effects of diversity and eutrophication on stability, emphasizing the need to understand how drivers of global change interactively affect the reliable provisioning of ecosystem services in real-world systems.

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Since the revisions to the International Health Regulations (IHR) in 2005, much attention has turned to how states, particularly developing states, will address core capacity requirements attached to the revised IHR. Primarily, how will states strengthen their capacity to identify and verify public health emergencies of international concern (PHEIC)? Another important but under-examined aspect of the revised IHR is the empowerment of the World Health Organization (WHO) to act upon non-governmental reports of disease outbreaks. The revised IHR potentially marks a new chapter in the powers of ‘disease intelligence’ and how the WHO may press states to verify an outbreak event. This article seeks to understand whether internet surveillance response programs (ISRPs) are effective in ‘naming and shaming’ states into reporting disease outbreaks.

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In his sweeping survey of the Australian study of international relations, Martin Indyk1 claimed that ‘a common set of assumptions tends to underpin the work of almost all Australian scholars in the discipline’. If that assertion could have been plausibly extended to the whole region one generation ago, it certainly cannot now. The International Relations scholarship emanating from the Oceanic region regales in a diversity of theoretical, methodological and ethical assumptions. This diversity certainly emerged before the first Oceanic Conference on International Studies (OCIS) was convened in Canberra in 2004, however, subsequent conferences in Melbourne (2006) and Brisbane (2008) have galvanised and enriched that diversity. The state of the discipline in the region is as strong and healthy now as it has ever been, as is its integration into the global discipline, something we believe is reflected in the contributions collected in this Special Issue of Global Change, Peace and Security....

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Land use and agricultural practices can result in important contributions to the global source strength of atmospheric nitrous oxide (N2O) and methane (CH4). However, knowledge of gas flux from irrigated agriculture is very limited. From April 2005 to October 2006, a study was conducted in the Aral Sea Basin, Uzbekistan, to quantify and compare emissions of N2O and CH4 in various annual and perennial land-use systems: irrigated cotton, winter wheat and rice crops, a poplar plantation and a natural Tugai (floodplain) forest. In the annual systems, average N2O emissions ranged from 10 to 150 μg N2O-N m−2 h−1 with highest N2O emissions in the cotton fields, covering a similar range of previous studies from irrigated cropping systems. Emission factors (uncorrected for background emission), used to determine the fertilizer-induced N2O emission as a percentage of N fertilizer applied, ranged from 0.2% to 2.6%. Seasonal variations in N2O emissions were principally controlled by fertilization and irrigation management. Pulses of N2O emissions occurred after concomitant N-fertilizer application and irrigation. The unfertilized poplar plantation showed high N2O emissions over the entire study period (30 μg N2O-N m−2 h−1), whereas only negligible fluxes of N2O (<2 μg N2O-N m−2 h−1) occurred in the Tugai. Significant CH4 fluxes only were determined from the flooded rice field: Fluxes were low with mean flux rates of 32 mg CH4 m−2 day−1 and a low seasonal total of 35.2 kg CH4 ha−1. The global warming potential (GWP) of the N2O and CH4 fluxes was highest under rice and cotton, with seasonal changes between 500 and 3000 kg CO2 eq. ha−1. The biennial cotton–wheat–rice crop rotation commonly practiced in the region would average a GWP of 2500 kg CO2 eq. ha−1 yr−1. The analyses point out opportunities for reducing the GWP of these irrigated agricultural systems by (i) optimization of fertilization and irrigation practices and (ii) conversion of annual cropping systems into perennial forest plantations, especially on less profitable, marginal lands.

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This paper discusses the following key messages. Taxonomy is (and taxonomists are) more important than ever in times of global change. Taxonomic endeavour is not occurring fast enough: in 250 years since the creation of the Linnean Systema Naturae, only about 20% of Earth's species have been named. We need fundamental changes to the taxonomic process and paradigm to increase taxonomic productivity by orders of magnitude. Currently, taxonomic productivity is limited principally by the rate at which we capture and manage morphological information to enable species discovery. Many recent (and welcomed) initiatives in managing and delivering biodiversity information and accelerating the taxonomic process do not address this bottleneck. Development of computational image analysis and feature extraction methods is a crucial missing capacity needed to enable taxonomists to overcome the taxonomic impediment in a meaningful time frame. Copyright © 2009 Magnolia Press.

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The temperature sensitivity of decomposition of different soil organic matter (SOM) fractions was studied with laboratory incubations using 13C and 14C isotopes to differentiate between SOM of different age. The quality of SOM and the functionality and composition of microbial communities in soils formed under different climatic conditions were also studied. Transferring of organic layers from a colder to a warmer climate was used to assess how changing climate, litter input and soil biology will affect soil respiration and its temperature sensitivity. Together, these studies gave a consistent picture on how warming climate will affect the decomposition of different SOM fractions in Finnish forest soils: the most labile C was least temperature sensitive, indicating that it is utilized irrespective of temperature. The decomposition of intermediate C, with mean residence times from some years to decades, was found to be highly temperature sensitive. Even older, centennially cycling C was again less temperature sensitive, indicating that different stabilizing mechanisms were limiting its decomposition even at higher temperatures. Because the highly temperature sensitive, decadally cycling C, forms a major part of SOM stock in the organic layers of the studied forest soils, these results mean that these soils could lose more carbon during the coming years and decades than estimated earlier. SOM decomposition in boreal forest soils is likely to increase more in response to climate warming, compared to temperate or tropical soils, also because the Q10 is temperature dependent. In the northern soils the warming will occur at a lower temperature range, where Q10 is higher, and a similar increase in temperature causes a higher relative increase in respiration rates. The Q10 at low temperatures was found to be inversely related to SOM quality. At higher temperatures respiration was increasingly limited by low substrate availability.

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Fire is a major driver of ecosystem change and can disproportionately affect the cycling of different nutrients. Thus, a stoichiometric approach to investigate the relationships between nutrient availability and microbial resource use during decomposition is likely to provide insight into the effects of fire on ecosystem functioning. We conducted a field litter bag experiment to investigate the long-term impact of repeated fire on the stoichiometry of leaf litter C, N and P pools, and nutrient-acquiring enzyme activities during decomposition in a wet sclerophyll eucalypt forest in Queensland, Australia. Fire frequency treatments have been maintained since 1972, including burning every two years (2yrB), burning every four years (4yrB) and no burning (NB). C:N ratios in freshly fallen litter were 29-42% higher and C:P ratios were 6-25% lower for 2yrB than NB during decomposition, with correspondingly lower 2yrB N:P ratios (27-32) than for NB (34-49). Trends in litter soluble and microbial N:P ratios were similar to the overall litter N:P ratios across fire treatments. Consistent with these, the ratio of activities for N-acquiring to P-acquiring enzymes in litter was higher for 2yrB than NB while 4yrB was generally intermediate between 2yrB and NB. Decomposition rates of freshly fallen litter were significantly lower for 2yrB (72±2% mass remaining at the end of experiment) than for 4yrB (59±3%) and NB (62±3%), a difference that may be related to effects of N limitation, lower moisture content, and/or litter C quality. Results for older mixed-age litter were similar to those for freshly fallen litter although treatment differences were less pronounced. Overall, these findings show that frequent fire (2yrB) decoupled N and P cycling, as manifested in litter C:N:P stoichiometry and in microbial biomass N:P ratio and enzymatic activities. These data indicate that fire induced a transient shift to N-limited ecosystem conditions during the post-fire recovery phase. This article is protected by copyright. All rights reserved.

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The structure and function of northern ecosystems are strongly influenced by climate change and variability and by human-induced disturbances. The projected global change is likely to have a pronounced effect on the distribution and productivity of different species, generating large changes in the equilibrium at the tree-line. In turn, movement of the tree-line and the redistribution of species produce feedback to both the local and the regional climate. This research was initiated with the objective of examining the influence of natural conditions on the small-scale spatial variation of climate in Finnish Lapland, and to study the interaction and feedback mechanisms in the climate-disturbances-vegetation system near the climatological border of boreal forest. The high (1 km) resolution spatial variation of climate parameters over northern Finland was determined by applying the Kriging interpolation method that takes into account the effect of external forcing variables, i.e., geographical coordinates, elevation, sea and lake coverage. Of all the natural factors shaping the climate, the geographical position, local topography and altitude proved to be the determining ones. Spatial analyses of temperature- and precipitation-derived parameters based on a 30-year dataset (1971-2000) provide a detailed description of the local climate. Maps of the mean, maximum and minimum temperatures, the frost-free period and the growing season indicate that the most favourable thermal conditions exist in the south-western part of Lapland, around large water bodies and in the Kemijoki basin, while the coldest regions are in highland and fell Lapland. The distribution of precipitation is predominantly longitudinally dependent but with the definite influence of local features. The impact of human-induced disturbances, i.e., forest fires, on local climate and its implication for forest recovery near the northern timberline was evaluated in the Tuntsa area of eastern Lapland, damaged by a widespread forest fire in 1960 and suffering repeatedly-failed vegetation recovery since that. Direct measurements of the local climate and simulated heat and water fluxes indicated the development of a more severe climate and physical conditions on the fire-disturbed site. Removal of the original, predominantly Norway spruce and downy birch vegetation and its substitution by tundra vegetation has generated increased wind velocity and reduced snow accumulation, associated with a large variation in soil temperature and moisture and deep soil frost. The changed structural parameters of the canopy have determined changes in energy fluxes by reducing the latter over the tundra vegetation. The altered surface and soil conditions, as well as the evolved severe local climate, have negatively affected seedling growth and survival, leading to more unfavourable conditions for the reproduction of boreal vegetation and thereby causing deviations in the regional position of the timberline. However it should be noted that other factors, such as an inadequate seed source or seedbed, the poor quality of the soil and the intensive logging of damaged trees could also exacerbate the poor tree regeneration. In spite of the failed forest recovery at Tunsta, the position and composition of the timberline and tree-line in Finnish Lapland may also benefit from present and future changes in climate. The already-observed and the projected increase in temperature, the prolonged growing season, as well as changes in the precipitation regime foster tree growth and new regeneration, resulting in an advance of the timberline and tree-line northward and upward. This shift in the distribution of vegetation might be decelerated or even halted by local topoclimatic conditions and by the expected increase in the frequency of disturbances.

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Remote sensing provides methods to infer land cover information over large geographical areas at a variety of spatial and temporal resolutions. Land cover is input data for a range of environmental models and information on land cover dynamics is required for monitoring the implications of global change. Such data are also essential in support of environmental management and policymaking. Boreal forests are a key component of the global climate and a major sink of carbon. The northern latitudes are expected to experience a disproportionate and rapid warming, which can have a major impact on vegetation at forest limits. This thesis examines the use of optical remote sensing for estimating aboveground biomass, leaf area index (LAI), tree cover and tree height in the boreal forests and tundra taiga transition zone in Finland. The continuous fields of forest attributes are required, for example, to improve the mapping of forest extent. The thesis focus on studying the feasibility of satellite data at multiple spatial resolutions, assessing the potential of multispectral, -angular and -temporal information, and provides regional evaluation for global land cover data. Preprocessed ASTER, MISR and MODIS products are the principal satellite data. The reference data consist of field measurements, forest inventory data and fine resolution land cover maps. Fine resolution studies demonstrate how statistical relationships between biomass and satellite data are relatively strong in single species and low biomass mountain birch forests in comparison to higher biomass coniferous stands. The combination of forest stand data and fine resolution ASTER images provides a method for biomass estimation using medium resolution MODIS data. The multiangular data improve the accuracy of land cover mapping in the sparsely forested tundra taiga transition zone, particularly in mires. Similarly, multitemporal data improve the accuracy of coarse resolution tree cover estimates in comparison to single date data. Furthermore, the peak of the growing season is not necessarily the optimal time for land cover mapping in the northern boreal regions. The evaluated coarse resolution land cover data sets have considerable shortcomings in northernmost Finland and should be used with caution in similar regions. The quantitative reference data and upscaling methods for integrating multiresolution data are required for calibration of statistical models and evaluation of land cover data sets. The preprocessed image products have potential for wider use as they can considerably reduce the time and effort used for data processing.

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Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here we consider how changes in climate and atmospheric carbon dioxide (CO2) concentrations will affect drought ET frequencies in sorghum and wheat systems of Northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat. This article is protected by copyright. All rights reserved.