82 resultados para Large-scale Analysis

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Biotic and abiotic phenological observations can be collected from continental to local spatial scale. Plant phenological observations may only be recorded wherever there is vegetation. Fog, snow and ice are available as phenological para-meters wherever they appear. The singularity of phenological observations is the possibility of spatial intensification to a microclimatic scale where the equipment of meteorological measurements is too expensive for intensive campaigning. The omnipresence of region-specific phenological parameters allows monitoring for a spatially much more detailed assessment of climate change than with weather data. We demonstrate this concept with phenological observations with the use of a special network in the Canton of Berne, Switzerland, with up to 600 observations sites (more than 1 to 10 km² of the inhabited area). Classic cartography, gridding, the integration into a Geographic Information System GIS and large-scale analysis are the steps to a detailed knowledge of topoclimatic conditions of a mountainous area. Examples of urban phenology provide other types of spatially detailed applications. Large potential in phenological mapping in future analyses lies in combining traditionally observed species-specific phenology with remotely sensed and modelled phenology that provide strong spatial information. This is a long history from cartographic intuition to algorithm-based representations of phenology.

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The link between high precipitation in Dronning Maud Land (DML), Antarctica, and the large-scale atmospheric circulation is investigated using ERA-Interim data for 1979–2009. High-precipitation events are analyzed at Halvfarryggen situated in the coastal region of DML and at Kohnen Station located in its interior. This study further includes a comprehensive comparison of high precipitation in ERA-Interim with precipitation data from the Antarctic Mesoscale Prediction System (AMPS) and snow accumulation measurements from automatic weather stations (AWSs), with the limitations of such a comparison being discussed. The ERA-Interim and AMPS precipitation data agree very well. However, the correspondence between high precipitation in ERA-Interim and high snow accumulation at the AWSs is relatively weak. High-precipitation events at both Halvfarryggen and Kohnen are typically associated with amplified upper level waves. This large-scale atmospheric flow pattern is preceded by the downstream development of a Rossby wave train from the eastern South Pacific several days before the precipitation event. At the surface, a cyclone located over the Weddell Sea is the main synoptic ingredient for high precipitation both at Halvfarryggen and at Kohnen. A blocking anticyclone downstream is not a requirement for high precipitation per se, but a larger share of blocking occurrences during the highest-precipitation days in DML suggests that these blocks strengthen the vertically integrated water vapor transport (IVT) into DML. A strong link between high precipitation and the IVT perpendicular to the local orography suggests that IVT could be used as a “proxy” for high precipitation, in particular over DML's interior.

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This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

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Secondary forests in the Lower Mekong Basin (LMB) are increasingly recognized as a valuable component of land cover, providing ecosystem services and benefits for local users. A large proportion of secondary forests in the LMB, especially in the uplands, are maintained by swidden cultivation. In order to assess the regional-scale status and dynamic trends of secondary forests in the LMB, an analysis of existing regional land cover data for 1993 and 1997 was carried out and forms the basis of this paper. To gain insight into the full range of dynamics affecting secondary forests beyond net-change rates, cross-tabulation matrix analyses were performed. The investigations revealed that secondary forests make up the largest share of forest cover in the LMB, with over 80% located in Laos and Cambodia. The deforestation rates for secondary forests are 3 times higher than the rates for other forest categories and account for two-thirds of the total deforestation. These dynamics are particularly pronounced in the less advanced countries of the LMB, especially in Laos, where national policies and the opening up of national economies seem to be the main drivers of further degradation and loss of secondary forests.

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Understanding natural climate variability and its driving factors is crucial to assessing future climate change. Therefore, comparing proxy-based climate reconstructions with forcing factors as well as comparing these with paleoclimate model simulations is key to gaining insights into the relative roles of internal versus forced variability. A review of the state of modelling of the climate of the last millennium prior to the CMIP5–PMIP3 (Coupled Model Intercomparison Project Phase 5–Paleoclimate Modelling Intercomparison Project Phase 3) coordinated effort is presented and compared to the available temperature reconstructions. Simulations and reconstructions broadly agree on reproducing the major temperature changes and suggest an overall linear response to external forcing on multidecadal or longer timescales. Internal variability is found to have an important influence at hemispheric and global scales. The spatial distribution of simulated temperature changes during the transition from the Medieval Climate Anomaly to the Little Ice Age disagrees with that found in the reconstructions. Thus, either internal variability is a possible major player in shaping temperature changes through the millennium or the model simulations have problems realistically representing the response pattern to external forcing. A last millennium transient climate response (LMTCR) is defined to provide a quantitative framework for analysing the consistency between simulated and reconstructed climate. Beyond an overall agreement between simulated and reconstructed LMTCR ranges, this analysis is able to single out specific discrepancies between some reconstructions and the ensemble of simulations. The disagreement is found in the cases where the reconstructions show reduced covariability with external forcings or when they present high rates of temperature change.

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Changes in Greenland accumulation and the stability in the relationship between accumulation variability and large-scale circulation are assessed by performing time-slice simulations for the present day, the preindustrial era, the early Holocene, and the Last Glacial Maximum (LGM) with a comprehensive climate model. The stability issue is an important prerequisite for reconstructions of Northern Hemisphere atmospheric circulation variability based on accumulation or precipitation proxy records from Greenland ice cores. The analysis reveals that the relationship between accumulation variability and large-scale circulation undergoes a significant seasonal cycle. As the contributions of the individual seasons to the annual signal change, annual mean accumulation variability is not necessarily related to the same atmospheric circulation patterns during the different climate states. Interestingly, within a season, local Greenland accumulation variability is indeed linked to a consistent circulation pattern, which is observed for all studied climate periods, even for the LGM. Hence, it would be possible to deduce a reliable reconstruction of seasonal atmospheric variability (e.g., for North Atlantic winters) if an accumulation or precipitation proxy were available that resolves single seasons. We further show that the simulated impacts of orbital forcing and changes in the ice sheet topography on Greenland accumulation exhibit strong spatial differences, emphasizing that accumulation records from different ice core sites regarding both interannual and long-term (centennial to millennial) variability cannot be expected to look alike since they include a distinct local signature. The only uniform signal to external forcing is the strong decrease in Greenland accumulation during glacial (LGM) conditions and an increase associated with the recent rise in greenhouse gas concentrations.

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Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore propose a novel approach that uses approximate Principal Component Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large datasets from the UCI repository, the approach significantly improves run times with minimal loss in accuracy.

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This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

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Despite an increased scientific interest in the relatively new phenomenon of large-scale land acquisition (LSLA), data on processes on the local level remain sparse and superficial. However, knowledge about the concrete implementation of LSLA projects and the different impacts they have on the heterogeneous group of project affected people is indispensable for a deepened understanding of the phenomenon. In order to address this research gap, a team of two anthropologists and a human geographer conducted in-depth fieldwork on the LSLA project of Swiss based Addax Bioenergy in Sierra Leone. After the devastating civil war, the Sierra Leonean government created favourable conditions for foreign investors willing to lease large areas of land and to bring “development” to the country. Being one of the numerous investing companies, Addax Bioenergy has leased 57’000 hectares of land to develop a sugarcane plantation and an ethanol factory to produce biofuel for the export to the European market. Based on participatory observation, qualitative interview techniques and a network analysis, the research team aimed a) at identifying the different actors that were necessary for the implementation of this project on a vertical level and b) exploring various impacts of the project in the local context of two villages on a horizontal level. The network analysis reveals a complex pattern of companies, institutions, nongovernmental organisations and prominent personalities acting within a shifting technological and discursive framework linking global scales to a unique local context. Findings from the latter indicate that affected people initially welcomed the project but now remain frustrated since many promises and expectations have not been fulfilled. Although some local people are able to benefit from the project, the loss of natural resources that comes along with the land lease affects livelihoods of vulnerable groups – especially women and land users – considerably. However, this research doesn’t only disclose impacts on local people’s previous lives but also addresses strategies they adopt in the newly created situation that has opened up alternative spaces for renegotiations of power and legitimatisation. Therewith, this explorative study reveals new aspects of LSLA that have not been considered adequately by the investing company nor by the general academic discourse on LSLA.

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This chapter aims to overcome the gap existing between case study research, which typically provides qualitative and process-based insights, and national or global inventories that typically offer spatially explicit and quantitative analysis of broader patterns, and thus to present adequate evidence for policymaking regarding large-scale land acquisitions. Therefore, the chapter links spatial patterns of land acquisitions to underlying implementation processes of land allocation. Methodologically linking the described patterns and processes proved difficult, but we have identified indicators that could be added to inventories and monitoring systems to make linkage possible. Combining complementary approaches in this way may help to determine where policy space exists for more sustainable governance of land acquisitions, both geographically and with regard to processes of agrarian transitions. Our spatial analysis revealed two general patterns: (i) relatively large forestry-related acquisitions that target forested landscapes and often interfere with semi-subsistence farming systems; and (ii) smaller agriculture-related acquisitions that often target existing cropland and also interfere with semi-subsistence systems. Furthermore, our meta-analysis of land acquisition implementation processes shows that authoritarian, top-down processes dominate. Initially, the demands of powerful regional and domestic investors tend to override socio-ecological variables, local actors’ interests, and land governance mechanisms. As available land grows scarce, however, and local actors gain experience dealing with land acquisitions, it appears that land investments begin to fail or give way to more inclusive, bottom-up investment models.

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Large-scale land acquisition, or "land grabbing", has become a key research topic among scholars interested in agrarian change, development, and the environment. The term "land acquisitions" refers to a highly contested process in terms of governance and impacts on livelihoods and human rights. This book focuses on South-East Asia. A series of thematic and in-depth case studies put "land grabbing" into specific historical and institutional contexts. The volume also offers a human rights analysis of the phenomenon, examining the potential and limits of human rights mechanisms aimed at preventing and mitigating land grabs' negative consequences.