853 resultados para Spatial scale
Resumo:
This data set contains aboveground plant biomass in 2007 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) of the monoculture plots of a large grassland biodiversity experiment (the Jena Experiment). In the monoculture plots the biomass of the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species. These 60 species comprising the species pool of the Jena Experiment belong to four functional groups (grasses, legumes, tall and small herbs). Plots were sown in May 2002 and are since maintained by bi-annual weeding and mowing. Aboveground plant biomass was harvested twice in 2007 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the monocultures. This was done by clipping the vegetation at 3 cm above ground in 2 rectangles of 0.2 x 0.5 m per plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. excluding an outer edge of 0.5 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. The data for individual subsamples (i.e. rectangles) and the mean over samples for all biomass measures are given.
Resumo:
This data set contains aboveground plant biomass in 2008 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) of the monoculture plots of a large grassland biodiversity experiment (the Jena Experiment). In the monoculture plots the biomass of the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species. One of the replicate plots per species was given up after the vegetation period of 2007 for all but the nine species belonging also to the so called dominance experiment in Jena. These nine species are: Alopecurus pratensis, Anthriscus sylvestris, Arrhenatherum elatius, Dactylis glomerata, Geranium pratense, Poa trivialis, Phleum pratense, Trifolium repens and Trifolium pratense.In 2008 plot size was reduced to 2.5 x 2.5 m. These 60 species comprising the species pool of the Jena Experiment belong to four functional groups (grasses, legumes, tall and small herbs). Plots were sown in May 2002 and are since maintained by bi-annual weeding and mowing. Aboveground plant biomass was harvested twice in 2008 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the monocultures. This was done by clipping the vegetation at 3 cm above ground in 2 rectangles of 0.2 x 0.5 m per plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. excluding an outer edge of 0.5 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. The data for individual subsamples (i.e. rectangles) and the mean over samples for all biomass measures are given.
Resumo:
This data set contains aboveground plant biomass in 2009 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) of the monoculture plots of a large grassland biodiversity experiment (the Jena Experiment). In the monoculture plots the biomass of the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species. One of the replicate plots per species was given up after the vegetation period of 2007 for all but the nine species belonging also to the so called dominance experiment in Jena. These nine species are: Alopecurus pratensis, Anthriscus sylvestris, Arrhenatherum elatius, Dactylis glomerata, Geranium pratense, Poa trivialis, Phleum pratense, Trifolium repens and Trifolium pratense.In 2008 plot size was reduced to 2.5 x 2.5 m. These 60 species comprising the species pool of the Jena Experiment belong to four functional groups (grasses, legumes, tall and small herbs). Plots were sown in May 2002 and are since maintained by bi-annual weeding and mowing. Aboveground plant biomass was harvested twice in 2009 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the monocultures. This was done by clipping the vegetation at 3 cm above ground in 2 rectangles of 0.2 x 0.5 m per plot. The location of these rectangles was in the center of the plot area. The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. The data for individual subsamples (i.e. rectangles) and the mean over samples for all biomass measures are given.
Resumo:
This data set contains aboveground plant biomass in 2002 (Sown plant community; measured in biomass as dry weight) of the monoculture plots of a large grassland biodiversity experiment (the Jena Experiment). In the monoculture plots the biomass of the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species. These 60 species comprising the species pool of the Jena Experiment belong to four functional groups (grasses, legumes, tall and small herbs). Plots were sown in May 2002 and are since maintained by bi-annual weeding and mowing. Aboveground plant biomass was harvested twice in 2002 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the monocultures. This was done by clipping the vegetation at 3 cm above ground in 2 rectangles of 0.2 x 0.5 m per plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. excluding an outer edge of 0.5 m). The positions of the rectangles within plots were identical for all plots. From the harvested biomass only the separated biomass of the sown plant species was kept. All biomass was dried to constant weight (70°C, >= 48 h) and weighed. The data for individual subsamples (i.e. rectangles) and the mean over samples for all biomass measures are given.
Resumo:
This data set contains aboveground plant biomass in 2004 (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) of the monoculture plots of a large grassland biodiversity experiment (the Jena Experiment). In the monoculture plots the biomass of the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species. These 60 species comprising the species pool of the Jena Experiment belong to four functional groups (grasses, legumes, tall and small herbs). Plots were sown in May 2002 and are since maintained by bi-annual weeding and mowing. Aboveground plant biomass was harvested twice in 2004 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the monocultures. This was done by clipping the vegetation at 3 cm above ground in 2 rectangles of 0.2 x 0.5 m per plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. excluding an outer edge of 0.5 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. The data for individual subsamples (i.e. rectangles) and the mean over samples for all biomass measures are given.
Resumo:
Thesis (Ph.D.)--University of Washington, 2016-08
Resumo:
A growing interest in mapping the social value of ecosystem services (ES) is not yet methodologically aligned with what is actually being mapped. We critically examine aspects of the social value mapping process that might influence map outcomes and limit their practical use in decision making. We rely on an empirical case of participatory mapping, for a single ES (recreation opportunities), which involves diverse stakeholders such as planners, researchers, and community representatives. Value elicitation relied on an individual open-ended interview and a mapping exercise. Interpretation of the narratives and GIS calculations of proximity, centrality, and dispersion helped in exploring the factors driving participants’ answers. Narratives reveal diverse value types. Whereas planners highlighted utilitarian and aesthetic values, the answers from researchers revealed naturalistic values as well. In turn community representatives acknowledged symbolic values. When remitted to the map, these values were constrained to statements toward a much narrower set of features of the physical (e.g., volcanoes) and built landscape (e.g., roads). The results suggest that mapping, as an instrumental approach toward social valuation, may capture only a subset of relevant assigned values. This outcome is the interplay between participants’ characteristics, including their acquaintance with the territory and their ability with maps, and the mapping procedure itself, including the proxies used to represent the ES and the value typology chosen, the elicitation question, the cartographic features displayed on the base map, and the spatial scale.
Resumo:
Previous studies have shown that extreme weather events are on the rise in response to our changing climate. Such events are projected to become more frequent, more intense, and longer lasting. A consistent exposure metric for measuring these extreme events as well as information regarding how these events lead to ill health are needed to inform meaningful adaptation strategies that are specific to the needs of local communities. Using federal meteorological data corresponding to 17 years (1997-2013) of the National Health Interview Survey, this research: 1) developed a location-specific exposure metric that captures individuals’ “exposure” at a spatial scale that is consistent with publicly available county-level health outcome data; 2) characterized the United States’ population in counties that have experienced higher numbers of extreme heat events and thus identified population groups likely to experience future events; and 3) developed an empirical model describing the association between exposure to extreme heat events and hay fever. This research confirmed that the natural modes of forcing (e.g., El Niño-Southern Oscillation), seasonality, urban-rural classification, and division of country have an impact on the number extreme heat events recorded. Also, many of the areas affected by extreme heat events are shown to have a variety of vulnerable populations including women of childbearing age, people who are poor, and older adults. Lastly, this research showed that adults in the highest quartile of exposure to extreme heat events had a 7% increased odds of hay fever compared to those in the lowest quartile, suggesting that exposure to extreme heat events increases risk of hay fever among US adults.
Resumo:
This study used a large spatial scale approach in order to better quantify the relationships between maerl bed structure and a selection of potentially forcing physical factors. Data on maerl bed structure and morpho-sedimentary characteristics were obtained from recent oceanographic surveys using underwater video recording and grab sampling. Considering the difficulties in carrying out real-time monitoring of highly variable hydrodynamic and physicochemical factors, these were generated by three-dimensional numerical models with high spatial and temporal resolution. The BIOENV procedure indicated that variation in the percentage cover of thalli can best be explained (correlation = 0.76) by a combination of annual mean salinity, annual mean nitrate concentration and annual mean current velocity, while the variation in the proportion of living thalli can best be explained (correlation = 0.47) by a combination of depth and mud content. Linear relationships showed that the percentage cover of maerl thalli was positively correlated with nitrate concentration (R2 = 0.78, P < 0.01) and negatively correlated with salinity (R2 = 0.81, P < 0.01), suggesting a strong effect of estuarine discharge on maerl bed structure, and also negatively correlated with current velocity (R2 = 0.81, P < 0.01). When maerl beds were deeper than 10 m, the proportion of living thalli was always below 30% but when they were shallower than 10 m, it varied between 4 and 100%, and was negatively correlated with mud content (R2 = 0.53, P < 0.01). On the other hand, when mud content was below 10%, the proportion of living thalli showed a negative correlation with depth (R2 = 0.84, P < 0.01). This large spatial scale explanation of maerl bed heterogeneity provides a realistic physical characterization of these ecologically interesting benthic habitats and usable findings for their conservation and management.
Resumo:
Wind-generated waves in the Kara, Laptev, and East-Siberian Seas are investigated using altimeter data from Envisat RA-2 and SARAL-AltiKa. Only isolated ice-free zones had been selected for analysis. Wind seas can be treated as pure wind-generated waves without any contamination by ambient swell. Such zones were identified using ice concentration data from microwave radiometers. Altimeter data, both significant wave height (SWH) and wind speed, for these areas were further obtained for the period 2002-2012 using Envisat RA-2 measurements, and for 2013 using SARAL-AltiKa. Dependencies of dimensionless SWH and wavelength on dimensionless wave generation spatial scale are compared to known empirical dependencies for fetch-limited wind wave development. We further check sensitivity of Ka- and Ku-band and discuss new possibilities that AltiKa's higher resolution can open.
Resumo:
The air-sea flux of greenhouse gases (e.g. carbon dioxide, CO2) is a critical part of the climate system and a major factor in the biogeochemical development of the oceans. More accurate and higher resolution calculations of these gas fluxes are required if we are to fully understand and predict our future climate. Satellite Earth observation is able to provide large spatial scale datasets that can be used to study gas fluxes. However, the large storage requirements needed to host such data can restrict its use by the scientific community. Fortunately, the development of cloud-computing can provide a solution. Here we describe an open source air-sea CO2 flux processing toolbox called the ‘FluxEngine’, designed for use on a cloud-computing infrastructure. The toolbox allows users to easily generate global and regional air-sea CO2 flux data from model, in situ and Earth observation data, and its air-sea gas flux calculation is user configurable. Its current installation on the Nephalae cloud allows users to easily exploit more than 8 terabytes of climate-quality Earth observation data for the derivation of gas fluxes. The resultant NetCDF data output files contain >20 data layers containing the various stages of the flux calculation along with process indicator layers to aid interpretation of the data. This paper describes the toolbox design, the verification of the air-sea CO2 flux calculations, demonstrates the use of the tools for studying global and shelf-sea air-sea fluxes and describes future developments.
Resumo:
El estudio de los factores que rigen los patrones espaciales de la distribución del pastoreo de los herbívoros domésticos es fundamental en la ecología y el manejo de los recursos naturales. Aunque los productores y profesionales realizan ajustes anuales o estacionales de la carga animal para influir en la preferencia animal por determinados ambientes de pastoreo y alcanzar un uso eficiente del recurso forrajero, el manejo de la distribución del ganado continúa siendo un gran desafío. La heterogeneidad de los ambientes de pastoreo tiene dimensión tanto espacial como temporal, lo cual impone desafíos en el entendimiento de los factores que influyen en las decisiones de selección de hábitat por parte del ganado. En esta contribución comenzamos revisando los modelos conceptuales actuales del comportamiento del ganado a grandes escalas. Luego, presentamos algunos resultados de estudios conducidos en diferentes ecosistemas contrastantes de Argentina y New Mexico (EEUU). Estos estudios desarrollados usando animales con y sin collares GPS contribuyen a mejorar gradualmente las decisiones de manejo de los pastizales. Finalmente, hacemos unas consideraciones breves relacionadas con el manejo del ganado en Ecuador que pueden contribuir a mejorar la sustentabilidad de los sistemas de producción ganaderos.
Resumo:
We investigate key characteristics of Ca²⁺ puffs in deterministic and stochastic frameworks that all incorporate the cellular morphology of IP[subscript]3 receptor channel clusters. In a first step, we numerically study Ca²⁺ liberation in a three dimensional representation of a cluster environment with reaction-diffusion dynamics in both the cytosol and the lumen. These simulations reveal that Ca²⁺ concentrations at a releasing cluster range from 80 µM to 170 µM and equilibrate almost instantaneously on the time scale of the release duration. These highly elevated Ca²⁺ concentrations eliminate Ca²⁺ oscillations in a deterministic model of an IP[subscript]3R channel cluster at physiological parameter values as revealed by a linear stability analysis. The reason lies in the saturation of all feedback processes in the IP[subscript]3R gating dynamics, so that only fluctuations can restore experimentally observed Ca²⁺ oscillations. In this spirit, we derive master equations that allow us to analytically quantify the onset of Ca²⁺ puffs and hence the stochastic time scale of intracellular Ca²⁺ dynamics. Moving up the spatial scale, we suggest to formulate cellular dynamics in terms of waiting time distribution functions. This approach prevents the state space explosion that is typical for the description of cellular dynamics based on channel states and still contains information on molecular fluctuations. We illustrate this method by studying global Ca²⁺ oscillations.
Resumo:
Tese de Doutoramento, Ciências do Mar, da Terra e do Ambiente, Ramo: Ciências do Mar, Especialização em Ecologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016