957 resultados para Climate variables
Resumo:
Diatom data of 192 surface sediment samples from the marginal seas in the western Pacific together with modern summer and winter sea surface temperature and salinity data were analyzed. The results of canonical correspondence analysis show that summer sea-surface salinity (SSS) is highly positively correlated with winter SSS and so is summer sea-surface temperature (SST) with winter SST. The correlations between SSSs and SSTs are less positively correlated, which may be due to interactions of regional current pattern and monsoon climate. The correlations between diatom species, sample sites and environmental variables concur with known diatom ecology and regional oceanographic characters. The results of forward selection of the environmental variables and associated Monte Carlo permutation tests of the statistical significance of each variable suggest that summer SSS and winter SST are the main environmental factors affecting the diatom distribution in the area and therefore preserved diatom data from down core could be used for reconstructions of summer SSS and winter SST in the region.
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Nations around the world are considering strategies to mitigate the severe impacts of climate change predicted to occur in the twenty-first century. Many countries, however, lack the wealth, technology, and government institutions to effectively cope with climate change. This study investigates the varying degrees to which developing and developed nations will be exposed to changes in three key variables: temperature, precipitation, and runoff. We use Geographic Information Systems (GIS) analysis to compare current and future climate model predictions on a country level. We then compare our calculations of climate change exposure for each nation to several metrics of political and economic well-being. Our results indicate that the impacts of changes in precipitation and runoff are distributed relatively equally between developed and developing nations. In contrast, we confirm research suggesting that developing nations will be affected far more severely by changes in temperature than developed nations. Our results also suggest that this unequal impact will persist throughout the twenty-first century. Our analysis further indicates that the most significant temperature changes will occur in politically unstable countries, creating an additional motivation for developed countries to actively engage with developing nations on climate mitigation strategies. © 2011, Mary Ann Liebert, Inc.
Resumo:
The Miyun Reservoir, the only surface water source for Beijing city, has experienced water supply decline in recent decades. Previous studies suggest that both land use change and climate contribute to the changes of water supply in this critical watershed. However, the specific causes of the decline in the Miyun Reservoir are debatable under a non-stationary climate in the past 4 decades. The central objective of this study was to quantify the separate and collective contributions of land use change and climate variability to the decreasing inflow into the Miyun Reservoir during 1961–2008. Different from previous studies on this watershed, we used a comprehensive approach to quantify the timing of changes in hydrology and associated environmental variables using the long-term historical hydrometeorology and remote-sensing-based land use records. To effectively quantify the different impacts of the climate variation and land use change on streamflow during different sub-periods, an annual water balance model (AWB), the climate elasticity model (CEM), and a rainfall–runoff model (RRM) were employed to conduct attribution analysis synthetically. We found a significant (p < 0.01) decrease in annual streamflow, a significant positive trend in annual potential evapotranspiration (p < 0.01), and an insignificant (p > 0.1) negative trend in annual precipitation during 1961–2008. We identified two streamflow breakpoints, 1983 and 1999, by the sequential Mann–Kendall test and double-mass curve. Climate variability alone did not explain the decrease in inflow to the Miyun Reservoir. Reduction of water yield was closely related to increase in actual evapotranspiration due to the expansion of forestland and reduction in cropland and grassland, and was likely exacerbated by increased water consumption for domestic and industrial uses in the basin. The contribution to the observed streamflow decline from land use change fell from 64–92 % during 1984–1999 to 36–58 % during 2000–2008, whereas the contribution from climate variation climbed from 8–36 % during the 1984–1999 to 42–64 % during 2000–2008. Model uncertainty analysis further demonstrated that climate warming played a dominant role in streamflow reduction in the most recent decade (i.e., 2000s). We conclude that future climate change and variability will further challenge the water supply capacity of the Miyun Reservoir to meet water demand. A comprehensive watershed management strategy needs to consider the climate variations besides vegetation management in the study basin.
Resumo:
Recently, large-scale changes in the biogeography of calanoid copepod crustaceans have been detected in the northeastern North Atlantic Ocean and adjacent seas. Strong biogeographical shifts in all copepod assemblages were found with a northward extension of more than ° in latitude of warm-water species associated with a decrease in the number of colder-water species. These changes were attributed to regional increase in sea surface temperature. Here, we have extended these studies to examine long-term changes in phytoplankton, zooplankton and salmon in relation to hydro-meteorological forcing in the northeast Atlantic Ocean and adjacent seas. We found highly significant relationships between (1) long-term changes in all three trophic levels, (2) sea surface temperature in the northeastern Atlantic, (3) Northern Hemisphere temperature and (4) the North Atlantic Oscillation. The similarities detected between plankton, salmon, temperature and hydro-climatic parameters are also seen in their cyclical variability and in a stepwise shift that started after a pronounced increase in Northern Hemisphere Temperature anomalies at the end of the 1970s. All biological variables show a pronounced change which started after circa 1982 for euphausiids (decline), 1984 for the total abundance of small copepods (increase), 1986 for phytoplankton biomass (increase) and Calanus finmarchicus (decrease) and 1988 for salmon (decrease). This cascade of biological events led to an exceptional period, which is identified after 1986 to present and followed another shift in large-scale hydro-climatic variables and sea surface temperature. This regional temperature increase therefore appears to be an important parameter that is at present governing the dynamic equilibrium of northeast Atlantic pelagic ecosystems with possible consequences for biogeochemical processes and fisheries.
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Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.
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Following the publication of our paper (Attrill et al. 2007), we became quickly aware of a couple of errors. We have subsequently been collaborating with Dr. Chris Lynam (Lynam et al. 2004, 2005) to bring together our two datasets, explore the common patterns within our data, and attempt to provide a consensus on how climate is affecting gelatinous plankton in the North Sea. During this reanalysis, two errors within the data were discovered, one involving a transcription error of a column of residuals during de-trended analysis, the other a major data entry error deep in the Continuous Plankton Recorder (CPR) database for sector B2. Here we present a revised version of table 1 from Attrill et al. (2007) to incorporate corrections to these transcription and data entry errors. These corrections alter some of the results in our original data table, mainly to increase and strengthen the number of significant relations we found (e.g., for sector B2 and whole sea area); all previous main results remain robustly significant. Following discussions with Dr. Lynam, two clarifications of statements made in Attrill et al. (2007) are also required. Page 482, Results, last line of first column: ‘‘There were no...robust, consistent relations between jellyfish frequency and any environmental variables for B and D… contrary to the findings of previous shorter time series (Lynam et al. 2005).’’ The Lynam et al. (2004, 2005) papers presented no data for the D sector and found no link in the B sector, contrary to our revised results. Page 482, Discussion, paragraph 1, last sentence: ‘‘… positive association … North of Scotland (Lynam et al. 2005) … does not appear to be maintained.’’ Our paper did not report on any data that covered Lynam et al.’s (2005) North of Scotland area so the statement is not directly supported, although their positive relation North of Scotland, when considered in conjunction with inflow, may agree with the C2 and B2 results of Attrill et al. (2007).
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While documentation of climate effects on marine ecosystems has a long history, the underlying processes have often been elusive. In this paper we review some of the ecosystem responses to climate variability and discuss the possible mechanisms through which climate acts. Effects of climatological and oceanographic variables, such as temperature, sea ice, turbulence, and advection, on marine organisms are discussed in terms of their influence on growth, distribution, reproduction, activity rates, recruitment and mortality. Organisms tend to be limited to specific thermal ranges with experimental findings showing that sufficient oxygen supply by ventilation and circulation only occurs within these ranges. Indirect effects of climate forcing through effects on the food web are also discussed. Research and data needs required to improve our knowledge of the processes linking climate to ecosystem changes are presented along with our assessment of our ability to predict ecosystem responses to future climate change scenarios. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Over the last few decades, global warming has accelerated both the rate and magnitude of changes observed in many functional units of the Earth System. In this context, plankton are sentinel organisms because they are sensitive to subtle levels of changes in temperature and might help in identifying the current effects of climate change on pelagic ecosystems. In this paper, we performed a comparative approach in two regions of the North Atlantic (i.e. the Northeast Atlantic and the North Sea) to explore the relationships between changes in marine plankton, the regional physico-chemical environment and large-scale hydro-climatic forcing using four key indices: the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the East Atlantic (EA) pattern and Northern Hemisphere Temperature (NHT) anomalies. Our analyses suggest that long-term changes in the states of the two ecosystems were synchronous and correlated to the same large-scale hydro-climatic variables: NHT anomalies, the AMO and to a lesser extent the EA pattern. No significant correlation was found between long-term ecosystem modifications and the state of the NAO. Our results suggest that the effect of climate on these ecosystems has mainly occurred in both regions through the modulation of the thermal regime.
Resumo:
Broad scale climate forcing can interact with local environmental processes to affect the observed ecological phenomena. This causes potential problems of over-extrapolation for results from a limited number of sites or the averaging out of region-specific responses if data from too wide an area are combined. In this study, an area similar in extent to the Celtic Biscay Large Marine Ecosystem, but including off-shelf areas, was partitioned using clustering of satellite chlorophyll (chl-a) measurements. The resulting clusters were used to define areas over which to combine copepod data from the Continuous Plankton Recorder. Following filtering due to data limitations, nine regions were defined with sufficient records for analysis. These regions were consistent with known oceanographic structure in the study area. Off-shelf regions showed a progressively later timing in the seasonal peak of chl-a measurements moving northwards. Generalised additive models were used to estimate seasonal and multiannual signals in the adult and juvenile stages of Calanus finmarchicus, C. helgolandicus and the Paracalanus–Pseudocalanus group. Associations between variables (sea surface temperature (SST), phenology and annual abundance) differed among taxonomic groups, but even within taxonomic groups, relationships were not consistent across regions. For example, in the deep waters off Spain and Portugal the annual abundance of Calanus finmarchicus has a weak positive association with SST, in contrast to the pattern in most other regions. The regions defined in this study provide an objective basis for investigations into the long term dynamics of plankton populations and suggest suitable sub regions for deriving pelagic system indicators.
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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.
Resumo:
Advances in habitat and climate modelling allow us to reduce uncertainties of climate change impacts on species distribution. We evaluated the impacts of future climate change on community structure, diversity, distribution and phenology of 14 copepod species in the North Atlantic. We developed and validated habitat models for key zooplankton species using continuous plankton recorder (CPR) survey data collected at mid latitudes of the North Atlantic. Generalized additive models (GAMs) were applied to relate the occurrence of species to environmental variables. Models were projected to future (2080–2099) environmental conditions using coupled hydroclimatix–biogeochemical models under the Intergovernmental Panel on Climate Change (IPCC) A1B climate scenario, and compared to present (2001–2020) conditions. Our projections indicated that the copepod community is expected to respond substantially to climate change: a mean poleward latitudinal shift of 8.7 km per decade for the overall community with an important species range variation (–15 to 18 km per decade); the species seasonal peak is expected to occur 12–13 d earlier for Calanus finmarchicus and C. hyperboreus; and important changes in community structure are also expected (high species turnover of 43–79% south of the Oceanic Polar Front). The impacts of the change expected by the end of the century under IPCC global warming scenarios on copepods highlight poleward shifts, earlier seasonal peak and changes in biodiversity spatial patterns that might lead to alterations of the future North Atlantic pelagic ecosystem. Our model and projections are supported by a temporal validation undertaken using the North Atlantic climate regime shift that occurred in the 1980s: the habitat model built in the cold period (1970–1986) has been validated in the warm period (1987–2004).
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Climate change during the last five decades has impacted significantly on natural ecosystems and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species’ bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical and habitat variables for all 87 lagomorph species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current models and only those deemed ‘modellable’ within our framework were projected under future climate scenarios (58 species). Phylogenetically-controlled regressions were used to test whether species traits correlated with predicted responses to climate change. Climate change is likely to impact more than two-thirds of lagomorph species, with leporids (rabbits, hares and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov’s Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management. We strongly advocate studies minimising data gaps in our knowledge of the Order, specifically collecting more specimens for biodiversity archives and targeting data deficient geographic regions.
Resumo:
1. The prediction and mapping of climate in areas between climate stations is of increasing importance in ecology.
2. Four categories of model, simple interpolation, thin plate splines, multiple linear regression and mixed spline-regression, were tested for their ability to predict the spatial distribution of temperature on the British mainland. The models were tested by external cross-verification.
3. The British distribution of mean daily temperature was predicted with the greatest accuracy by using a mixed model: a thin plate spline fitted to the surface of the country, after correction of the data by a selection from 16 independent topographical variables (such as altitude, distance from the sea, slope and topographic roughness), chosen by multiple regression from a digital terrain model (DTM) of the country.
4. The next most accurate method was a pure multiple regression model using the DTM. Both regression and thin plate spline models based on a few variables (latitude, longitude and altitude) only were comparatively unsatisfactory, but some rather simple methods of surface interpolation (such as bilinear interpolation after correction to sea level) gave moderately satisfactory results. Differences between the methods seemed to be dependent largely on their ability to model the effect of the sea on land temperatures.
5. Prediction of temperature by the best methods was greater than 95% accurate in all months of the year, as shown by the correlation between the predicted and actual values. The predicted temperatures were calculated at real altitudes, not subject to sea-level correction.
6. A minimum of just over 30 temperature recording stations would generate a satisfactory surface, provided the stations were well spaced.
7. Maps of mean daily temperature, using the best overall methods are provided; further important variables, such as continentality and length of growing season, were also mapped. Many of these are believed to be the first detailed representations at real altitude.
8. The interpolated monthly temperature surfaces are available on disk.
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Embora o objetivo principal da proteção internacional dos solos seja proteger tanto as funções quanto a estrutura do solo, a atual abordagem trata principalmente da proteção ao nível estrutural. Há uma carência de estudos que contemplem a ligação das funções do solo com os níveis da comunidade. Além disso, é ainda desconhecido se as variáveis ambientais (ex: tipos de solo, condições climáticas) atuam nas funções do solo da mesma maneira que influenciam sua estrutura biológica. Ademais, as alterações climáticas poderão ter sozinhas ou combinadas com os poluentes, um grande efeito nos ecossistemas terrestres. O presente trabalho propõe estudar as funções e a estrutura biológica do solo quando impactados devido a estresse tóxico (poluição por Cu) e/ou alterações a fatores como a temperatura e abundância de organismos, de maneira a simular possíveis variações regionais ou climáticas. Para alcançar os objetivos principais 3 experiências utilizando diferentes densidades de E. crypticus e 2 gerações foram feitas (Capítulos II e III). Duas experiências com mesocosmos (SMS) decorreram durante 3 meses sob uma gama de diversas temperaturas (10 – 29°C), que representam temperaturas médias para Portugal e Dinamarca (Capítulos IV e V). Duas experiências de campo também foram realizadas com intuito de validar os SMSs (Capítulo VI). Resultados demonstraram que os efeitos do Cu na reprodução dos enquitraídeos dependem da densidade inicial de organismos, especialmente na 2ª geração. Entretanto, nos SMSs expostos a Cu, a densidade inicial é menos importante nos resultados finais. O aumento da temperatura alterou majoritariamente a fase inicial de crescimento populacional. Em períodos mais longos, a abundância estabilizou tornando-se menos influenciada pelas temperaturas. Períodos longos de exposição reforçaram os efeitos da temperatura, como por ex: diversas espécies foram similarmente afetadas a 29 ou 26°C quando expostas durante 28 ou 61 dias respectivamente. De forma geral, o Cu reduziu a abundância da maioria das espécies ao longo do tempo, com poucas exceções. Os resultados da decomposição da matéria orgânica (MO) e atividade alimentar associaram-se com a abundância de organismos em baixas temperaturas (10-23°C). Entretanto, com o aumento das temperaturas (19-29°C), este comportamento não foi claro e a abundância de espécies e atividade alimentar diminuíram enquanto a decomposição da MO aumentou. Além disso, os resultados observados nos SMSs foram confirmados no campo. Mais especificamente, alterações ocorreram na fase de crescimento (correspondente à Primavera) e a exposição ao Cu diminuiu os efeitos da temperatura. Metodologias mais complexas (ex: mais gerações e experiências com múltiplas espécies) apresentam muitos benefícios, mas também proporcionam respostas mais complexas, as quais exigem um maior “peso” de evidências para serem comprovadas.
Resumo:
This study aims to analyse the relationship between safety climate and the level of risk acceptance, as well as its relationship with workplace safety performance. The sample includes 14 companies and 403 workers. The safety climate assessment was performed by the application of a Safety Climate in Wood Industries questionnaire and safety performance was assessed with a checklist. Judgements about risk acceptance were measured through questionnaires together with four other variables: trust, risk perception, benefit perception and emotion. Safety climate was found to be correlated with workgroup safety performance, and it also plays an important role in workers’ risk acceptance levels. Risk acceptance tends to be lower when safety climate scores of workgroups are high, and subsequently, their safety performance is better. These findings seem to be relevant, as they provide Occupational, Safety and Health practitioners with a better understanding of workers’ risk acceptance levels and of the differences among workgroups.