950 resultados para pollen and vegetation
Resumo:
Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.
Resumo:
Temporal and spatial patterns of soil water content affect many soil processes including evaporation, infiltration, ground water recharge, erosion and vegetation distribution. This paper describes the analysis of a soil moisture dataset comprising a combination of continuous time series of measurements at a few depths and locations, and occasional roving measurements at a large number of depths and locations. The objectives of the paper are: (i) to develop a technique for combining continuous measurements of soil water contents at a limited number of depths within a soil profile with occasional measurements at a large number of depths, to enable accurate estimation of the soil moisture vertical pattern and the integrated profile water content; and (ii) to estimate time series of soil moisture content at locations where there are just occasional soil water measurements available and some continuous records from nearby locations. The vertical interpolation technique presented here can strongly reduce errors in the estimation of profile soil water and its changes with time. On the other hand, the temporal interpolation technique is tested for different sampling strategies in space and time, and the errors generated in each case are compared.
Resumo:
A high-resolution record of sea-level change spanning the past 1000 years is derived from foraminiferal and chronological analyses of a 2m thick salt-marsh peat sequence at Chezzetcook, Nova Scotia, Canada. Former mean tide level positions are reconstructed with a precision of +/- 0.055 in using a transfer function derived from distributions of modern salt-marsh foraminifera. Our age model for the core section older than 300 years is based on 19 AMS C-14 ages and takes into account the individual probability distributions of calibrated radiocarbon ages. The past 300 years is dated by pollen and the isotopes Pb-206, Pb-207, Pb-210, Cs-137 and Am-241. Between AD 1000 and AD 1800, relative sea level rose at a mean rate of 17cm per century. Apparent pre-industrial rises of sea level dated at AD 1500-1550 and AD 1700-1800 cannot be clearly distinguished when radiocarbon age errors are taken into account. Furthermore, they may be an artefact of fluctuations in atmospheric C-14 production. In the 19th century sea level rose at a mean rate of 1.6mm/yr. Between AD 1900 and AD 1920, sea-level rise accelerated to the modern mean rate of 3.2mm/yr. This acceleration corresponds in time with global temperature rise and may therefore be associated with recent global warming. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
An investigation using the Stepping Out model of early hominin dispersal out of Africa is presented here. The late arrival of early hominins into Europe, as deduced from the fossil record, is shown to be consistent with poor ability of these hominins to survive in the Eurasian landscape. The present study also extends the understanding of modelling results from the original study by Mithen and Reed (2002. Stepping out: a computer simulation of hominid dispersal from Africa. J. Hum. Evol. 43, 433-462). The representation of climate and vegetation patterns has been improved through the use of climate model output. This study demonstrates that interpretative confidence may be strengthened, and new insights gained when climate models and hominin dispersal models are integrated. (C) 2007 Elsevier Ltd. All rights reserved.
Resumo:
Climate variability in the African Soudano-Sahel savanna zone has attracted much attention because of the persistence of anomalously low rainfall. Past efforts to monitor the climate of this region have focused on rainfall and vegetation conditions, while land surface temperature (LST) has received less attention. Remote sensing of LST is feasible and possible at global scale. Most remotely sensed estimates of LST are based on the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) that are limited in their ability to capture the full diurnal cycle. Although more frequent observations are available from past geostationary satellites, their spatial resolution is coarser than that of polar orbiting satellites. In this study, the improved capabilities of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the METEOSAT Second Generation (MSG) instrument are used to remotely sense the LST in the African Soudano-Sahel savanna zone at a resolution of 3 km and 15 minutes. In support of the Radiative Atmospheric Divergence using the ARM Mobile Facility (AMF), GERB and AMMA Stations (RADAGAST) project, African Monsoon Multidisciplinary Analyses (AMMA) project and the Department of Energy's Atmospheric Radiation Measurement (ARM) program, the ARM Mobile Facility was deployed during 2006 in this climatically sensitive region, thereby providing a unique opportunity to evaluate remotely sensed algorithms for deriving LST.
Resumo:
Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.
Resumo:
To inspire new ideas in research on pollination ecology, we list the most important unanswered questions in the field. This list was drawn up by contacting 170 scientists from different areas of pollination ecology and asking them to contribute their opinion on the greatest knowledge gaps that need to be addressed. Almost 40% of them took part in our email poll and we received more than 650 questions and comments, which we classified into different categories representing various aspects of pollination research. The original questions were merged and synthesised, and a final vote and ranking led to the resultant list. The categories cover plant sexual reproduction, pollen and stigma biology, abiotic pollination, evolution of animal-mediated pollination, interactions of pollinators and floral antagonists, pollinator behaviour, taxonomy, plant-pollinator assemblages, geographical trends in diversity, drivers of pollinator loss, ecosystem services, management of pollination, and conservation issues such as the implementation of pollinator conservation. We focused on questions that were of a broad scope rather than case-specific; thus, addressing some questions may not be feasible within single research projects but constitute a general guide for future directions. With this compilation we hope to raise awareness of pollination-related topics not only among researchers but also among non-specialists including policy makers, funding agencies and the public at large.
Resumo:
Rats and mice have traditionally been considered one of the most important pests of sugarcane. However, "control" campaigns are rarely specific to the target species, and can have an effect on local wildlife, in particular non-pest rodent species. The objective of this study was to distinguish between rodent species that are pests and those that are not, and to identify patterns of food utilization by the rodents in the sugarcane crop complex. Within the crop complex, subsistence crops like maize, sorghum, rice, and bananas, which are grown alongside the sugarcane, are also subject to rodent damage. Six native rodent species were trapped in the Papaloapan River Basin of the State of Veracruz; the cotton rat (Sigmodon hispidus), the rice rat (Oryzomys couesi), the small rice rat (O. chapmani), the white footed mouse (Peromyscus leucopus), the golden mouse (Reithrodontomys sumichrasti), and the pigmy mouse (Baiomys musculus). In a stomach content analysis, the major food components for the cotton rat, the rice rat and the small rice rat were sugarcane (4.9 to 30.1 %), seed (2.7 to 22.9%), and vegetation (0.9 to 29.8%); while for the golden mouse and the pigmy mouse the stomach content was almost exclusively seed (98 to 100%). The authors consider the first three species to be pests of the sugarcane crop complex, while the last two species are not.
Resumo:
During glacial periods, atmospheric CO2 concentration increases and decreases by around 15 ppm. At the same time, the climate changes gradually in Antarctica. Such climate changes can be simulated in models when the AMOC (Atlantic Meridional Oceanic Circulation) is weakened by adding fresh water to the North Atlantic. The impact on the carbon cycle is less straightforward, and previous studies give opposite results. Because the models and the fresh water fluxes were different in these studies, it prevents any direct comparison and hinders finding whether the discrepancies arise from using different models or different fresh water fluxes. In this study we use the CLIMBER-2 coupled climate carbon model to explore the impact of different fresh water fluxes. In both preindustrial and glacial states, the addition of fresh water and the resulting slow-down of the AMOC lead to an uptake of carbon by the ocean and a release by the terrestrial biosphere. The duration, shape and amplitude of the fresh water flux all have an impact on the change of atmospheric CO2 because they modulate the change of the AMOC. The maximum CO2 change linearly depends on the time integral of the AMOC change. The different duration, amplitude, and shape of the fresh water flux cannot explain the opposite evolution of ocean and vegetation carbon inventory in different models. The different CO2 evolution thus depends on the AMOC response to the addition of fresh water and the resulting climatic change, which are both model dependent. In CLIMBER-2, the rise of CO2 recorded in ice cores during abrupt events can be simulated under glacial conditions, especially when the sinking of brines in the Southern Ocean is taken into account. The addition of fresh water in the Southern Hemisphere leads to a decline of CO2, contrary to the addition of fresh water in the Northern Hemisphere.
Resumo:
• UV-B radiation currently represents c. 1.5% of incoming solar radiation. However, significant changes are known to have occurred in the amount of incoming radiation both on recent and on geological timescales. Until now it has not been possible to reconstruct a detailed measure of UV-B radiation beyond c. 150 yr ago. • Here, we studied the suitability of fossil Pinus spp. pollen to record variations in UV-B flux through time. In view of the large size of the grain and its long fossil history, we hypothesized that this grain could provide a good proxy for recording past variations in UV-B flux. • Two key objectives were addressed: to determine whether there was, similar to other studied species, a clear relationship between UV-B-absorbing compounds in the sporopollenin of extant pollen and the magnitude of UV-B radiation to which it had been exposed; and to determine whether these compounds could be extracted from a small enough sample size of fossil pollen to make reconstruction of a continuous record through time a realistic prospect. • Preliminary results indicate the excellent potential of this species for providing a quantitative record of UV-B through time. Using this technique, we present the first record of UV-B flux during the last 9500 yr from a site near Bergen, Norway.
Resumo:
The emerging discipline of urban ecology is shifting focus from ecological processes embedded within cities to integrative studies of large urban areas as biophysical-social complexes. Yet this discipline lacks a theory. Results from the Baltimore Ecosystem Study, part of the Long Term Ecological Research Network, expose new assumptions and test existing assumptions about urban ecosystems. The findings suggest a broader range of structural and functional relationships than is often assumed for urban ecological systems. We address the relationships between social status and awareness of environmental problems, and between race and environmental hazard. We present patterns of species diversity, riparian function, and stream nitrate loading. In addition, we probe the suitability of land-use models, the diversity of soils, and the potential for urban carbon sequestration. Finally, we illustrate lags between social patterns and vegetation, the biogeochemistry of lawns, ecosystem nutrient retention, and social-biophysical feedbacks. These results suggest a framework for a theory of urban ecosystems.
Resumo:
Global syntheses of palaeoenvironmental data are required to test climate models under conditions different from the present. Data sets for this purpose contain data from spatially extensive networks of sites. The data are either directly comparable to model output or readily interpretable in terms of modelled climate variables. Data sets must contain sufficient documentation to distinguish between raw (primary) and interpreted (secondary, tertiary) data, to evaluate the assumptions involved in interpretation of the data, to exercise quality control, and to select data appropriate for specific goals. Four data bases for the Late Quaternary, documenting changes in lake levels since 30 kyr BP (the Global Lake Status Data Base), vegetation distribution at 18 kyr and 6 kyr BP (BIOME 6000), aeolian accumulation rates during the last glacial-interglacial cycle (DIRTMAP), and tropical terrestrial climates at the Last Glacial Maximum (the LGM Tropical Terrestrial Data Synthesis) are summarised. Each has been used to evaluate simulations of Last Glacial Maximum (LGM: 21 calendar kyr BP) and/or mid-Holocene (6 cal. kyr BP) environments. Comparisons have demonstrated that changes in radiative forcing and orography due to orbital and ice-sheet variations explain the first-order, broad-scale (in space and time) features of global climate change since the LGM. However, atmospheric models forced by 6 cal. kyr BP orbital changes with unchanged surface conditions fail to capture quantitative aspects of the observed climate, including the greatly increased magnitude and northward shift of the African monsoon during the early to mid-Holocene. Similarly, comparisons with palaeoenvironmental datasets show that atmospheric models have underestimated the magnitude of cooling and drying of much of the land surface at the LGM. The inclusion of feedbacks due to changes in ocean- and land-surface conditions at both times, and atmospheric dust loading at the LGM, appears to be required in order to produce a better simulation of these past climates. The development of Earth system models incorporating the dynamic interactions among ocean, atmosphere, and vegetation is therefore mandated by Quaternary science results as well as climatological principles. For greatest scientific benefit, this development must be paralleled by continued advances in palaeodata analysis and synthesis, which in turn will help to define questions that call for new focused data collection efforts.
Resumo:
This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.
Resumo:
Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.
Resumo:
The decomposition of soil organic matter (SOM) is temperature dependent, but its response to a future warmer climate remains equivocal. Enhanced rates of decomposition of SOM under increased global temperatures might cause higher CO2 emissions to the atmosphere, and could therefore constitute a strong positive feedback. The magnitude of this feedback however remains poorly understood, primarily because of the difficulty in quantifying the temperature sensitivity of stored, recalcitrant carbon that comprises the bulk (>90%) of SOM in most soils. In this study we investigated the effects of climatic conditions on soil carbon dynamics using the attenuation of the 14C ‘bomb’ pulse as recorded in selected modern European speleothems. These new data were combined with published results to further examine soil carbon dynamics, and to explore the sensitivity of labile and recalcitrant organic matter decomposition to different climatic conditions. Temporal changes in 14C activity inferred from each speleothem was modelled using a three pool soil carbon inverse model (applying a Monte Carlo method) to constrain soil carbon turnover rates at each site. Speleothems from sites that are characterised by semi-arid conditions, sparse vegetation, thin soil cover and high mean annual air temperatures (MAATs), exhibit weak attenuation of atmospheric 14C ‘bomb’ peak (a low damping effect, D in the range: 55–77%) and low modelled mean respired carbon ages (MRCA), indicating that decomposition is dominated by young, recently fixed soil carbon. By contrast, humid and high MAAT sites that are characterised by a thick soil cover and dense, well developed vegetation, display the highest damping effect (D = c. 90%), and the highest MRCA values (in the range from 350 ± 126 years to 571 ± 128 years). This suggests that carbon incorporated into these stalagmites originates predominantly from decomposition of old, recalcitrant organic matter. SOM turnover rates cannot be ascribed to a single climate variable, e.g. (MAAT) but instead reflect a complex interplay of climate (e.g. MAAT and moisture budget) and vegetation development.