961 resultados para Global Change
Resumo:
The extent to which climate change might diminish the efficacy of protected areas is one of the most pressing conservation questions. Many projections suggest that climate-driven species distribution shifts will leave protected areas impoverished and species inadequately protected while other evidence suggests that intact ecosystems within protected areas will be resilient to change. Here, we tackle this problem empirically. We show how recent changes in distribution of 139 Tanzanian savannah bird species are linked to climate change, protected area status and land degradation. We provide the first evidence of climate-driven range shifts for an African bird community. Our results suggest that the continued maintenance of existing protected areas is an appropriate conservation response to the challenge of climate and environmental change.
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Climate change is expected to have an impact on plant communities as increased temperatures are expected to drive individual species' distributions polewards. The results of a revisitation study after c. 34years of 89 coastal sites in Scotland, UK, were examined to assess the degree of shifts in species composition that could be accounted for by climate change. There was little evidence for either species retreat northwards or for plots to become more dominated by species with a more southern distribution. At a few sites where significant change occurred, the changes were accounted for by the invasion, or in one instance the removal, of woody species. Also, the vegetation types that showed the most sensitivity to change were all early successional types and changes were primarily the result of succession rather than climate-driven changes. Dune vegetation appears resistant to climate change impacts on the vegetation, either as the vegetation is inherently resistant to change, management prevents increased dominance of more southerly species or because of dispersal limitation to geographically isolated sites.
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Recent changes in the seasonal timing (phenology) of familiar biological events have been one of the most conspicuous signs of climate change. However, the lack of a standardised approach to analysing change has hampered assessment of consistency in such changes among different taxa and trophic levels and across freshwater, terrestrial and marine environments. We present a standardised assessment of 25 532 rates of phenological change for 726 UK terrestrial, freshwater and marine taxa. The majority of spring and summer events have advanced, and more rapidly than previously documented. Such consistency is indicative of shared large-scale drivers. Furthermore, average rates of change have accelerated in a way that is consistent with observed warming trends. Less coherent patterns in some groups of organisms point to the agency of more local scale processes and multiple drivers. For the first time we show a broad scale signal of differential phenological change among trophic levels; across environments advances in timing were slowest for secondary consumers, thus heightening the potential risk of temporal mismatch in key trophic interactions. If current patterns and rates of phenological change are indicative of future trends, future climate warming may exacerbate trophic mismatching, further disrupting the functioning, persistence and resilience of many ecosystems and having a major impact on ecosystem services
Resumo:
A distinctive period of global change occurred during the PUocene between the warm Miocene and subsequent Quaternary cooling. Samples from Ocean Drilling Project Site 11 79 (-5586 mbsl, 41°4'N, 159°57'E), Site 881 (-5765 mbsl, 47°6.133'N, 161°29.490'E) and Site 882 (-3255 mbsl, 50°22'N, 167°36'E) were studied to determine the magnitude and composition ofterrigenous flux to the western mid-latitude North Pacific and its relation to climate change in East Asia since the mid-Pliocene. Dust-sized particles (including pollen), sourced from the arid regions and loess plateaus in East Asia are entrained by prevailing westerly winds and transported to the midlatitude northwest North Pacific Ocean. This is recorded by peaks in the total concentration of pollen and spores, as well as the mean grain size of allochthonous and autochthonous silicate material in abyssal marine sediments. Aridification of the Asian interior due to the phased uplift of the Himalayan-Tibetan Plateau created the modem East Asian Monsoon system dominated by a strengthening of the winter monsoon. The winter monsoon is further enhanced during glacials due to the expansion of desert and steppe environments at the expense ofwoodlands and forests recorded by the composition of palynological assemblages. The late Pliocene-Pleistocene glacials at ODP Sites 1 179, 881, and 882 are characterized by increases in grain size, magnetic susceptibility, pollen and spore concentrations around 3.5-3.3, 2.6-2.4, 1.7-1.6, and 0.9-0.7 Ma (ages based on magnetostratigraphic and biostratigraphic datums). The peaks during these times are relatively rich in pollen taxa derived primarily from steppe and boreal vegetation zones, recording cool, dry climates. The overall size increase of sediment and abundance of terrestrial palynomorphs record enhanced wind strength. The increase in magnitude of pollen and spore concentrations as well as grain size record global cooling and Northern Hemisphere glaciation. The peaks in grain size as well as pollen and spore abundance in marine sediments correlate with the mean grain size of loess in East Asia, consistent with the deflation of unarmoured surfaces during glacials. The transport of limiting nutrients to marine environments enhanced sea surface productivity and increased the rate of sediment accumulation.
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The cumulative effects of global change, including climate change, increased population density and domestic waste disposal, effluent discharges from industrial processes, agriculture and aquaculture will likely continue and increases the process of eutrophication in estuarine environments. Eutrophication is one of the leading causes of degraded water quality, water column hypoxia/anoxia, harmful algal bloom (HAB) and loss of habitat and species diversity in the estuarine environment. The present study attempts to characterize the trophic condition of coastal estuary using a simple tool; trophic index (TRIX) based on a linear combination of the log of four state variables with supplementary index Efficiency Coefficient (Eff. Coeff.) as a discriminating tool. Numerically, the index TRIX is scaled from 0 to10, covering a wide range of trophic conditions from oligotrophic to eutrophic. Study area Kodungallur-Azhikode Estuary (KAE) was comparatively shallow in nature with average depth of 3.6±0.2 m. Dissolve oxygen regime in the water column was ranged from 4.7±1.3 mgL−1 in Station I to 5.9±1.4 mgL−1 in Station IV. The average nitrate-nitrogen (NO3-N) of KAE water was 470 mg m−3; values ranged from Av. 364.4 mg m−3 at Station II to Av. 626.6 mg m−3at Station VII. The mean ammonium-nitrogen (NH4 +-N) varied from 54.1 mg m−3 at Station VII to 101 mg m−3 at Station III. The average Chl-a for the seven stations of KAE was 6.42±3.91 mg m−3. Comparisons over different spatial and temporal scales in the KAE and study observed that, estuary experiencing high productivity by the influence of high degree of eutrophication; an annual average of 6.91 TRIX was noticed in the KAE and seasonal highest was observed during pre monsoon period (7.15) and lowest during post monsoon period (6.51). In the spatial scale station V showed high value 7.37 and comparatively low values in the station VI (6.93) and station VII (6.96) and which indicates eutrophication was predominant in land cover area with comparatively high water residence time. Eff. Coeff. values in the KAE ranges from −2.74 during monsoon period to the lowest of −1.98 in pre monsoon period. Present study revealed that trophic state of the estuary under severe stress and the restriction of autochthonous and allochthonous nutrient loading should be keystone in mitigate from eutrophication process
Resumo:
Landwirtschaft spielt eine zentrale Rolle im Erdsystem. Sie trägt durch die Emission von CO2, CH4 und N2O zum Treibhauseffekt bei, kann Bodendegradation und Eutrophierung verursachen, regionale Wasserkreisläufe verändern und wird außerdem stark vom Klimawandel betroffen sein. Da all diese Prozesse durch die zugrunde liegenden Nährstoff- und Wasserflüsse eng miteinander verknüpft sind, sollten sie in einem konsistenten Modellansatz betrachtet werden. Dennoch haben Datenmangel und ungenügendes Prozessverständnis dies bis vor kurzem auf der globalen Skala verhindert. In dieser Arbeit wird die erste Version eines solchen konsistenten globalen Modellansatzes präsentiert, wobei der Schwerpunkt auf der Simulation landwirtschaftlicher Erträge und den resultierenden N2O-Emissionen liegt. Der Grund für diese Schwerpunktsetzung liegt darin, dass die korrekte Abbildung des Pflanzenwachstums eine essentielle Voraussetzung für die Simulation aller anderen Prozesse ist. Des weiteren sind aktuelle und potentielle landwirtschaftliche Erträge wichtige treibende Kräfte für Landnutzungsänderungen und werden stark vom Klimawandel betroffen sein. Den zweiten Schwerpunkt bildet die Abschätzung landwirtschaftlicher N2O-Emissionen, da bislang kein prozessbasiertes N2O-Modell auf der globalen Skala eingesetzt wurde. Als Grundlage für die globale Modellierung wurde das bestehende Agrarökosystemmodell Daycent gewählt. Neben der Schaffung der Simulationsumgebung wurden zunächst die benötigten globalen Datensätze für Bodenparameter, Klima und landwirtschaftliche Bewirtschaftung zusammengestellt. Da für Pflanzzeitpunkte bislang keine globale Datenbasis zur Verfügung steht, und diese sich mit dem Klimawandel ändern werden, wurde eine Routine zur Berechnung von Pflanzzeitpunkten entwickelt. Die Ergebnisse zeigen eine gute Übereinstimmung mit Anbaukalendern der FAO, die für einige Feldfrüchte und Länder verfügbar sind. Danach wurde das Daycent-Modell für die Ertragsberechnung von Weizen, Reis, Mais, Soja, Hirse, Hülsenfrüchten, Kartoffel, Cassava und Baumwolle parametrisiert und kalibriert. Die Simulationsergebnisse zeigen, dass Daycent die wichtigsten Klima-, Boden- und Bewirtschaftungseffekte auf die Ertragsbildung korrekt abbildet. Berechnete Länderdurchschnitte stimmen gut mit Daten der FAO überein (R2 = 0.66 für Weizen, Reis und Mais; R2 = 0.32 für Soja), und räumliche Ertragsmuster entsprechen weitgehend der beobachteten Verteilung von Feldfrüchten und subnationalen Statistiken. Vor der Modellierung landwirtschaftlicher N2O-Emissionen mit dem Daycent-Modell stand eine statistische Analyse von N2O-und NO-Emissionsmessungen aus natürlichen und landwirtschaftlichen Ökosystemen. Die als signifikant identifizierten Parameter für N2O (Düngemenge, Bodenkohlenstoffgehalt, Boden-pH, Textur, Feldfrucht, Düngersorte) und NO (Düngemenge, Bodenstickstoffgehalt, Klima) entsprechen weitgehend den Ergebnissen einer früheren Analyse. Für Emissionen aus Böden unter natürlicher Vegetation, für die es bislang keine solche statistische Untersuchung gab, haben Bodenkohlenstoffgehalt, Boden-pH, Lagerungsdichte, Drainierung und Vegetationstyp einen signifikanten Einfluss auf die N2O-Emissionen, während NO-Emissionen signifikant von Bodenkohlenstoffgehalt und Vegetationstyp abhängen. Basierend auf den daraus entwickelten statistischen Modellen betragen die globalen Emissionen aus Ackerböden 3.3 Tg N/y für N2O, und 1.4 Tg N/y für NO. Solche statistischen Modelle sind nützlich, um Abschätzungen und Unsicherheitsbereiche von N2O- und NO-Emissionen basierend auf einer Vielzahl von Messungen zu berechnen. Die Dynamik des Bodenstickstoffs, insbesondere beeinflusst durch Pflanzenwachstum, Klimawandel und Landnutzungsänderung, kann allerdings nur durch die Anwendung von prozessorientierten Modellen berücksichtigt werden. Zur Modellierung von N2O-Emissionen mit dem Daycent-Modell wurde zunächst dessen Spurengasmodul durch eine detailliertere Berechnung von Nitrifikation und Denitrifikation und die Berücksichtigung von Frost-Auftau-Emissionen weiterentwickelt. Diese überarbeitete Modellversion wurde dann an N2O-Emissionsmessungen unter verschiedenen Klimaten und Feldfrüchten getestet. Sowohl die Dynamik als auch die Gesamtsummen der N2O-Emissionen werden befriedigend abgebildet, wobei die Modelleffizienz für monatliche Mittelwerte zwischen 0.1 und 0.66 für die meisten Standorte liegt. Basierend auf der überarbeiteten Modellversion wurden die N2O-Emissionen für die zuvor parametrisierten Feldfrüchte berechnet. Emissionsraten und feldfruchtspezifische Unterschiede stimmen weitgehend mit Literaturangaben überein. Düngemittelinduzierte Emissionen, die momentan vom IPCC mit 1.25 +/- 1% der eingesetzten Düngemenge abgeschätzt werden, reichen von 0.77% (Reis) bis 2.76% (Mais). Die Summe der berechneten Emissionen aus landwirtschaftlichen Böden beträgt für die Mitte der 1990er Jahre 2.1 Tg N2O-N/y, was mit den Abschätzungen aus anderen Studien übereinstimmt.
Resumo:
De allí, que sea necesario analizar por qué las enfermedades infecciosas pueden constituir una amenaza a la seguridad desde un concepto más amplio como lo es el de la seguridad humana. Esta perspectiva permite ir más allá de la amenaza pura del bioterrorismo para dar cabida a los riesgos naturales
Resumo:
Shelf and coastal seas are regions of exceptionally high biological productivity, high rates of biogeochemical cycling and immense socio-economic importance. They are, however, poorly represented by the present generation of Earth system models, both in terms of resolution and process representation. Hence, these models cannot be used to elucidate the role of the coastal ocean in global biogeochemical cycles and the effects global change (both direct anthropogenic and climatic) are having on them. Here, we present a system for simulating all the coastal regions around the world (the Global Coastal Ocean Modelling System) in a systematic and practical fashion. It is based on automatically generating multiple nested model domains, using the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled to the European Regional Seas Ecosystem Model. Preliminary results from the system are presented. These demonstrate the viability of the concept, and we discuss the prospects for using the system to explore key areas of global change in shelf seas, such as their role in the carbon cycle and climate change effects on fisheries.
Resumo:
Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.
Resumo:
Global change may substantially affect biodiversity and ecosystem functioning but little is known about its effects on essential biotic interactions. Since different environmental drivers rarely act in isolation it is important to consider interactive effects. Here, we focus on how two key drivers of anthropogenic environmental change, climate change and the introduction of alien species, affect plant–pollinator interactions. Based on a literature survey we identify climatically sensitive aspects of species interactions, assess potential effects of climate change on these mechanisms, and derive hypotheses that may form the basis of future research. We find that both climate change and alien species will ultimately lead to the creation of novel communities. In these communities certain interactions may no longer occur while there will also be potential for the emergence of new relationships. Alien species can both partly compensate for the often negative effects of climate change but also amplify them in some cases. Since potential positive effects are often restricted to generalist interactions among species, climate change and alien species in combination can result in significant threats to more specialist interactions involving native species.
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The chapter provides an overview of major climate change impacts, at the regional scale.
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The vulnerability of smallholder farmers to climate change and variability is increasingly rising. As agriculture is the only source of income for most of them, agricultural adaptation with respect to climate change is vital for their sustenance and to ensure food security. In order to develop appropriate strategies and institutional responses, it is necessary to have a clear understanding of the farmers’ perception of climate change, actual adaptations at farm-level and what factors drive and constrain their decision to adapt. Thus, this study investigates the farm-level adaptation to climate change based on the case of a farming community in Sri Lanka. The findings revealed that farmers’ perceived the ongoing climate change based on their experiences. Majority of them adopted measures to address climate change and variability. These adaptation measures can be categorised into five groups, such as crop management, land management, irrigation management, income diversification, and rituals. The results showed that management of non-climatic factors was an important strategy to enhance farmers’ adaptation, particularly in a resource-constrained smallholder farming context. The results of regression analysis indicated that human cognition was an important determinant of climate change adaptation. Social networks were also found to significantly influence adaptation. The study also revealed that social barriers, such as cognitive and normative factors, are equally important as other economic barriers to adaptation. While formulating and implementing the adaptation strategies, this study underscored the importance of understanding socio-economic, cognitive and normative aspects of the local communities.