936 resultados para spatial-temporal constraints


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The seasonal sea level variations observed from tide gauges over 1900-2013 and gridded satellite altimeter product AVISO over 1993-2013 in the northwest Pacific have been explored. The seasonal cycle is able to explain 60-90% of monthly sea level variance in the marginal seas, while it explains less than 20% of variance in the eddy-rich regions. The maximum annual and semi-annual sea level cycles (30cm and 6cm) are observed in the north of the East China Sea and the west of the South China Sea respectively. AVISO was found to underestimate the annual amplitude by 25% compared to tide gauge estimates along the coasts of China and Russia. The forcing for the seasonal sea level cycle was identified. The atmospheric pressure and the steric height produce 8-12cm of the annual cycle in the middle continental shelf and in the Kuroshio Current regions separately. The removal of the two attributors from total sea level permits to identify the sea level residuals that still show significant seasonality in the marginal seas. Both nearby wind stress and surface currents can explain well the long-term variability of the seasonal sea level cycle in the marginal seas and the tropics because of their influence on the sea level residuals. Interestingly, the surface currents are a better descriptor in the areas where the ocean currents are known to be strong. Here, they explain 50-90% of inter-annual variability due to the strong links between the steric height and the large-scale ocean currents.

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Three land-fast ice stations (one of them was the Finnish research ice breaker Aranda) and the German research aircraft Falcon were applied to measure the turbulent and radiation fluxes over the ice edge zone in the northern Baltic Sea during the Baltic Air-Sea-Ice Study (BASIS) field experiment from 16 February to 6 March 1998. The temporal and spatial variability of the surface fluxes is discussed. Synoptic weather systems passed the experimental area in a rapid sequence and dominated the conditions (wind speed, airsurface temperature difference, cloud field) for the variability of the turbulent and radiation fluxes. At the ice stations, the largest upward sensible heat fluxes of about 100 Wm�2 were measured during the passage of a cold front when the air cooled faster (�5 K per hour) than the surface. The largest downward flux of about �200 Wm�2 occurred during warm air advection when the air temperature reached +10�C but the surface temperature remained at 0�C. Spatial variability of fluxes was observed from the small scale (scale of ice floes and open water spots) to the mesoscale (width of the ice edge zone). The degree of spatial variability depends on the synoptic situation: during melting conditions downward heat fluxes were the same over ice and open water, whereas during strong cold-air advection upward heat fluxes differed by more than 100 Wm�2. A remarkable amount of grey ice with intermediate surface temperature was observed. The ice in the Baltic Sea cannot be described by one ice type only.

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Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

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Spatial and temporal fluctuations in the concentration field from an ensemble of continuous point-source releases in a regular building array are analyzed from data generated by direct numerical simulations. The release is of a passive scalar under conditions of neutral stability. Results are related to the underlying flow structure by contrasting data for an imposed wind direction of 0 deg and 45 deg relative to the buildings. Furthermore, the effects of distance from the source and vicinity to the plume centreline on the spatial and temporal variability are documented. The general picture that emerges is that this particular geometry splits the flow domain into segments (e.g. “streets” and “intersections”) in each of which the air is, to a first approximation, well mixed. Notable exceptions to this general rule include regions close to the source, near the plume edge, and in unobstructed channels when the flow is aligned. In the oblique (45 deg) case the strongly three-dimensional nature of the flow enhances mixing of a scalar within the canopy leading to reduced temporal and spatial concentration fluctuations within the plume core. These fluctuations are in general larger for the parallel flow (0 deg) case, especially so in the long unobstructed channels. Due to the more complex flow structure in the canyon-type streets behind buildings, fluctuations are lower than in the open channels, though still substantially larger than for oblique flow. These results are relevant to the formulation of simple models for dispersion in urban areas and to the quantification of the uncertainties in their predictions.

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Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1x1 km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness.

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Sand fly populations of different ecological niches in the Amaraji endemic American Cutaneous Leishmaniasis (ACL) focus of the Pernambuco Atlantic Forest region of northeastern Brazil were monitored spatiotemporally. Lutzomyia whitmani was dominant in all niches but occurred in smaller numbers in forested locations. L. whitmani was significantly less seasonal than the other species, being present throughout the year while other species were more abundant between February and April. These results suggest that L. whitmani may potentially be the principal vector of ACL in the region, even though the sand fly fauna was diverse: 88% were L.whitmani and 12% belonged to 11 other species. Two other species, L. complexa (1.3%) and L. migonei (0.8%), considered to be ACL vectors in other regions, were also present. This detailed picture of the sand fly population`s abundance and spatiotemporal distribution provides a basis for future modeling studies of forecasting sand fly activity patterns and ACL occurence.

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The macrozoobenthic community of the Castillos Lagoon system (East Coast of Uruguay) was sampled during autumn, winter, spring and summer of 1991, in order to describe the community structure and the spatial and temporal patterns of distribution. Eleven sampling stations were distributed along a salinity gradient in a north-south direction (8 replicates were collected at each station). The maximum density of organisms was found at the central part of the lagoon (stations 6 and 7) where the bivalve Erodona mactroides and gastropod Heleobia australis were dominants. No significant correlation between the overall abundance of organisms and salinity could be demonstrated (r = 0.43, p > 0.1). However, a reduction in organism abundance between the autumn and the summer coincided with a marked drop in salinity. Falling levels of dissolved oxygen could have influenced the decreasing density of organisms (r = 0.75, p < 0.05). Species richness and diversity were correlated (p < 0.1) with salinity but the degree of correlation was not uniformly significant between sampling periods.

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A data set on Diatraea saccharalis and its parasitoids, Cotesia flavipes and tachinid flies, was analysed at five spatial scales-sugarcane mill, region, intermediary, farm and zone-to determine the role of spatial scale in synchrony patterns, and on temporal population variability. To analyse synchrony patterns, only the three highest spatial scales were considered, but for temporal population variability, all spatial scales were adopted. The synchrony-distance relationship revealed complex spatial structures depending on both species and spatial scale. Temporal population variability [SD log(x+1)] levels were highest at the smallest spatial scales although, in the majority of the cases, temporal variability was inversely dependent on sample size. All the species studied, with a few exceptions, presented spatial synchrony independent of spatial scale. The tachinid flies exhibited stronger synchrony dynamics than D. saccharalis and C. flavipes in all spatial scales with the latter displaying the weakest synchrony levels, except when mill spatial scales were compared. In some cases spatial synchrony may at first decay and then increase with distance, but the presence of such patterns can change depending on the spatial scale adopted.

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Biological control of Diatraea saccharalis is regarded as one of the best examples of successful classical biological control in Brazil. Since the introduction of the exotic parasitoid, Cotesia flavipes, from Pakistan at the beginning of the 1970s, decrease in D. saccharalis infestation in sugarcane fields has been attributed to the effectiveness of this agent. Recently, the native Tachinidae fly parasitoids (Lydella minense and Paratheresia claripalpis) have also been implicated in this success. However, quantitative data confirming the actual contribution of these agents to the control of D. saccharalis are rather limited. The purpose of this study was to investigate the dynamics of the interactions between D. saccharalis and its parasitoids, emphasizing the temporal patterns of parasitism. To investigate this question, a large data set comprising information collected from two sugarcane mills located in the state of São Paulo, Brazil (Barra and Sao Joao sugarcane mills), was analysed. Basically, the data set contained monthly information about the number of D. saccharalis larvae and their parasitoids in each sample (man-hour per sample), the sugarcane varieties cultivated, the age of the sugarcane plants (only at the Sao Joao sugarcane mill) as well as the sugarcane cut at sampling time. The data were collected from March 1984 to March 1997 and from May 1982 to December 1996 for the Barra and Sao Joao sugarcane mills, respectively. Temporal inverse density-dependent parasitism was predominant for both parasitoid species with respect to all spatial scales. Although the temporal pattern of parasitism was not directly density dependent, it was evident that the tachinids and C. flavipes presented positive numerical responses according to variations in D. saccharalis densities through time.

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Biological control of Diatraea saccharalis is regarded as one of the best examples of successful classical biological control in Brazil. Since the introduction of the exotic parasitoid Cotesia flavipes, the decrease of D. saccharalis infestation in sugarcane fields has been attributed to the effectiveness of this agent. Recently, the native tachinid fly parasitoids (Lydella minense and Paratheresia claripalpis) have also been implicated in the success. Here, we investigated the spatial and temporal population interactions between C. flavipes and the tachinid flies, and provide a critical analysis of the biological control practice, focusing on the undesirable effects of introductions of exotic natural enemies. To investigate these questions, a large data set comprising information from two sugarcane mills located in the state of São Paulo, Brazil (Barra and Sao Joao Mills), was analysed. Analysis of the correlation between C. flavipes and tachinid fly population densities through time revealed that such populations were inversely correlated in the Sao Joao Mill and not correlated in the Barra Mill. Logistic regressions were computed to investigate the proportion of sites occupied by the parasitoid species at both mills as a function of time. An increasing trend in the proportion of sites occupied by C. flavipes was observed, with a concomitant decrease of the sites occupied by tachinid flies. This effect was more intense in the Sao Joao Mill. Thus, there is a convincing possibility that constant releases of C. flavipes decreased the tachinid fly populations, resulting in an undesirable effect of biological control practice.

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We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)