947 resultados para spatially explicit


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1 We used simulated and experimental plant populations to analyse mortality-driven pattern formation under size-dependent competition. Larger plants had an advantage under size-asymmetric but not under symmetric competition. Initial patterns were random or clumped. 2 The simulations were individual-based and spatially explicit. Size-dependent competition was modelled with different rules to partition overlapping zones of influence. 3 The experiment used genotypes of Arabidopsis thaliana with different morphological plasticity and hence size-dependent competition. Compared with wild types, transgenic individuals over-expressed phytochrome A and had decreased plasticity because of disabled phytochrome-mediated shade avoidance. Therefore, competition among transgenics was more asymmetric compared with wild-types. 4 Density-dependent mortality under symmetric competition did not substantially change the initial spatial pattern. Conversely, simulations under asymmetric competition and experimental patterns of transgenic over-expressors showed patterns of survivors that deviated substantially from random mortality independent of initial patterns. 5 Small-scale initial patterns of wild types were regular rather than random or clumped. We hypothesize that this small-scale regularity may be explained by early shade avoidance of seedlings in their cotyledon stage. 6 Our experimental results support predictions from an individual-based simulation model and support the conclusion that regular spatial patterns of surviving individuals should be interpreted as evidence for strong, asymmetric competitive interactions and subsequent density-dependent mortality.

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Increasing commercial pressures on land are provoking fundamental and far-reaching changes in the relationships between people and land. Much knowledge on land-oriented investments projects currently comes from the media. Although this provides a good starting point, lack of transparency and rapidly changing contexts mean that this is often unreliable. The International Land Coalition, in partnership with Oxfam Novib, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), University of Pretoria, Centre for Development and Environment of the University of Bern (CDE), and GIZ, started to compile an inventory of land-related investments. This project aims to better understand the extent, trends and impacts of land-related investments by supporting an ongoing and systematic stocktaking exercise of the various investment projects currently taking place worldwide. It involves a large number of organizations and individuals working in areas where land transactions are being made, and able to provide details of such investments. The project monitors land transactions in rural areas that imply a transformation of land use rights from communities and smallholders to commercial use, and are made both by domestic and foreign investors (private actors, governments, government-back private investors). The focus is on investments for food or agrofuel production, timber extraction, carbon trading, mineral extraction, conservation and tourism. A novel way of using ITC to document land acquisitions in a spatially explicit way and by using an approach called “crowdsourcing” is being developed. This approach will allow actors to share information and knowledge directly and at any time on a public platform, where it will be scrutinized in terms of reliability and cross checked with other sources. Up to now, over 1200 deals have been recorded across 96 countries. Details of such transactions have been classified in a matrix and distributed to over 350 contacts worldwide for verification. The verified information has been geo-referenced and represented in two global maps. This is an open database enabling a continued monitoring exercise and the improvement of data accuracy. More information will be released over time. The opportunities arise from overcoming constraints by incomplete information by proposing a new way of collecting, enhancing and sharing information and knowledge in a more democratic and transparent manner. The intention is to develop interactive knowledge platform where any interested person can share and access information on land deals, their link to involved stakeholders, and their embedding into a geographical context. By making use of new ICT technologies that are more and more in the reach of local stakeholders, as well as open access and web-based spatial information systems, it will become possible to create a dynamic database containing spatial explicit data. Feeding in data by a large number of stakeholders, increasingly also by means of new mobile ITC technologies, will open up new opportunities to analyse, monitor and assess highly dynamic trends of land acquisition and rural transformation.

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Land degradation as well as land conservation maps at a (sub-) national scale are critical for pro-ject planning for sustainable land management. It has long been recognized that online accessible and low-cost raster data sets (e.g. Landsat imagery, SRTM-DEM’s) provide a readily available basis for land resource assessments for developing countries. However, choice of spatial, tempo-ral and spectral resolution of such data is often limited. Furthermore, while local expert knowl-edge on land degradation processes is abundant, difficulties are often encountered when linking existing knowledge with modern approaches including GIS and RS. The aim of this study was to develop an easily applicable, standardized workflow for preliminary spatial assessments of land degradation and conservation, which also allows the integration of existing expert knowledge. The core of the developed method consists of a workflow for rule-based land resource assess-ment. In a systematic way, this workflow leads from predefined land degradation and conserva-tion classes to field indicators, to suitable spatial proxy data, and finally to a set of rules for clas-sification of spatial datasets. Pre-conditions are used to narrow the area of interest. Decision tree models are used for integrating the different rules. It can be concluded that the workflow presented assists experts from different disciplines in col-laboration GIS/RS specialists in establishing a preliminary model for assessing land degradation and conservation in a spatially explicit manner. The workflow provides support when linking field indicators and spatial datasets, and when determining field indicators for groundtruthing.

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High-resolution records of calibrated proxy data for the past millennium are fundamental to place current changes into the context of pre-industrial natural forced and unforced variability. Although the need for regional spatially-explicit comprehensive reconstructions is widely recognized, the proxy data sources are still scarce, particularly for the Southern Hemisphere and especially for South America. We present a 600-year long warm season temperature record from varved sediments of Lago Plomo, a proglacial lake of the Northern Patagonian Ice field in Southern Chile (46°59′S, 72°52′W, 203 m a.s.l.). The thickness of the bright summer sediment layer relative to the dark winter layer (measured as total brightness; % reflectance 400–730 nm) is calibrated against warm season SONDJF temperature (1900–2009; r = 0.58, p(aut) = 0.056, RE = 0.52; CE = 0.15, RMSEP = 0.28 °C; five-year triangular filtered data). In Lago Plomo, warm summer temperatures lead to enhanced glacier melt and suspended sediment transport, which results in thicker light summer layers and to brighter sediments. Although Patagonia shows pronounced regional differences in decadal temperature trends and variability, the 600 years temperature reconstruction from Lago Plomo compares favourably with other regional/continental temperature records, but also emphasizes significant regional differences for which no data and information existed so far. These regional differences seem to be real as they are also reflected in modern climate data sets (1900–2010). The reconstruction shows pronounced subdecadal – multidecadal variability with cold phases during parts of the Little Ice Age (16th and 18th centuries) and in the beginning of the 20th century. The most prominent warm phase is the 19th century which is as warm as the second half of the 20th century. The exceptional summer warmth AD 1780–1810 is also found in other archives of Northern Patagonia and Central Chile. Our record shows the delayed 20th century warming in the Southern Hemisphere. The comparison between winter precipitation and summer temperature (inter-seasonal coupling) from Lago Plomo reveals alternating phases with parallel and contrasting decadal trends of winter precipitation and summer temperature (positive and negative running correlations Rwinter PP; summer TT). This observation from the sediment proxy data is also confirmed by two sets of reanalysis data for the 20th century. Reanalysis data show that phases with negative correlations between winter precipitation and summer temperature (e.g., dry winters and warm summers) at Lago Plomo are characteristic for periods when circumpolar Westerly flow is displaced southward and enhanced around 60°S.

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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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Due to its extraordinary biodiversity and rapid deforestation, north-eastern Madagascar is a conservation hotspot of global importance. Reducing shifting cultivation is a high priority for policy-makers and conservationists; however, spatially explicit evidence of shifting cultivation is lacking due to the difficulty of mapping it with common remote sensing methods. To overcome this challenge, we adopted a landscape mosaic approach to assess the changes between natural forests, shifting cultivation and permanent cultivation systems at the regional level from 1995 to 2011. Our study confirmed that shifting cultivation is still being used to produce subsistence rice throughout the region, but there is a trend of intensification away from shifting cultivation towards permanent rice production, especially near protected areas. While large continuous forest exists today only in the core zones of protected areas, the agricultural matrix is still dominated by a dense cover of tree crops and smaller forest fragments. We believe that this evidence makes a crucial contribution to the development of interventions to prevent further conversion of forest to agricultural land while improving local land users' well-being.

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The Janzen–Connell hypothesis proposes that specialized herbivores maintain high numbers of tree species in tropical forests by restricting adult recruitment so that host populations remain at low densities. We tested this prediction for the large timber tree species, Swietenia macrophylla, whose seeds and seedlings are preyed upon by small mammals and a host-specific moth caterpillar Steniscadia poliophaea, respectively. At a primary forest site, experimental seed additions to gaps – canopy-disturbed areas that enhance seedling growth into saplings – over three years revealed lower survival and seedling recruitment closer to conspecific trees and in higher basal area neighborhoods, as well as reduced subsequent seedling survival and height growth. When we included these Janzen–Connell effects in a spatially explicit individual-based population model, the caterpillar's impact was critical to limiting Swietenia's adult tree density, with a > 10-fold reduction estimated at 300 years. Our research demonstrates the crucial but oft-ignored linkage between Janzen–Connell effects on offspring and population-level consequences for a long-lived, potentially dominant tree species.

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The Out-of-Africa (OOA) dispersal ∼50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.

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Domestic dog rabies is an endemic disease in large parts of the developing world and also epidemic in previously free regions. For example, it continues to spread in eastern Indonesia and currently threatens adjacent rabies-free regions with high densities of free-roaming dogs, including remote northern Australia. Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions. Existing rabies models typically focus on long-term control programs in endemic countries. However, simulation models describing the dog rabies incursion scenario in regions where rabies is still exotic are lacking. We here describe such a stochastic, spatially explicit rabies simulation model that is based on individual dog information collected in two remote regions in northern Australia. Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy). Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested. This model is suitable for exploring rabies spread and control before an incursion in populations of largely free-roaming dogs that live close together with their owners. It can be used for ad-hoc contingency or response planning prior to and shortly after incursion of dog rabies in previously free regions. One challenge that remains is model parameterisation, particularly how dogs' roaming and contacts and biting behaviours change following a rabies incursion in a previously rabies free population.

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Patterns of size inequality in crowded plant populations are often taken to be indicative of the degree of size asymmetry of competition, but recent research suggests that some of the patterns attributed to size‐asymmetric competition could be due to spatial structure. To investigate the theoretical relationships between plant density, spatial pattern, and competitive size asymmetry in determining size variation in crowded plant populations, we developed a spatially explicit, individual‐based plant competition model based on overlapping zones of influence. The zone of influence of each plant is modeled as a circle, growing in two dimensions, and is allometrically related to plant biomass. The area of the circle represents resources potentially available to the plant, and plants compete for resources in areas in which they overlap. The size asymmetry of competition is reflected in the rules for dividing up the overlapping areas. Theoretical plant populations were grown in random and in perfectly uniform spatial patterns at four densities under size‐asymmetric and size‐symmetric competition. Both spatial pattern and size asymmetry contributed to size variation, but their relative importance varied greatly over density and over time. Early in stand development, spatial pattern was more important than the symmetry of competition in determining the degree of size variation within the population, but after plants grew and competition intensified, the size asymmetry of competition became a much more important source of size variation. Size variability was slightly higher at higher densities when competition was symmetric and plants were distributed nonuniformly in space. In a uniform spatial pattern, size variation increased with density only when competition was size asymmetric. Our results suggest that when competition is size asymmetric and intense, it will be more important in generating size variation than is local variation in density. Our results and the available data are consistent with the hypothesis that high levels of size inequality commonly observed within crowded plant populations are largely due to size‐asymmetric competition, not to variation in local density.

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Past and future forest composition and distribution in temperate mountain ranges is strongly influenced by temperature and snowpack. We used LANDCLIM, a spatially explicit, dynamic vegetation model, to simulate forest dynamics for the last 16,000 years and compared the simulation results to pollen and macrofossil records at five sites on the Olympic Peninsula (Washington, USA). To address the hydrological effects of climate-driven variations in snowpack on simulated forest dynamics, we added a simple snow accumulation-and-melt module to the vegetation model and compared simulations with and without the module. LANDCLIM produced realistic present-day species composition with respect to elevation and precipitation gradients. Over the last 16,000 years, simulations driven by transient climate data from an atmosphere-ocean general circulation model (AOGCM) and by a chironomid-based temperature reconstruction captured Late-glacial to Late Holocene transitions in forest communities. Overall, the reconstruction-driven vegetation simulations matched observed vegetation changes better than the AOGCM-driven simulations. This study also indicates that forest composition is very sensitive to snowpack-mediated changes in soil moisture. Simulations without the snow module showed a strong effect of snowpack on key bioclimatic variables and species composition at higher elevations. A projected upward shift of the snow line and a decrease in snowpack might lead to drastic changes in mountain forests composition and even a shift to dry meadows due to insufficient moisture availability in shallow alpine soils.

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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

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The data have been extracted and compiled from various sources but mainly from the ICES data base. The ICES data are from catch databases downloaded from the ICES website on 2014-01-14. These data are resolved by ICES area, country and year. During inspection of these data, it was noted that Norwegian data for years before 1950 had not been entered into the catch database on the ICES website. ICES has been notified of this omission by B. R. MacKenzie. The Norwegian data from ICES Bulletins. Statistiques has been added. Additional historical bluefin tuna catch data from other fishery reports and sources have been included in the data file for years preceding those when countries started reported their landings officially to ICES. These additional data have been reported in the literature previously (MacKenzie and Myers 2007, Fisheries Research).

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The data have been extracted and compiled from various sources but mainly from the ICES data base. The ICES data are from catch databases downloaded from the ICES website on 2014-01-14. These data are resolved by ICES area, country and year. During inspection of these data, it was noted that Norwegian data for years before 1950 had not been entered into the catch database on the ICES website. ICES has been notified of this omission by B. R. MacKenzie. The Norwegian data from ICES Bulletins. Statistiques has been added. Additional historical bluefin tuna catch data from other fishery reports and sources have been included in the data file for years preceding those when countries started reported their landings officially to ICES. These additional data have been reported in the literature previously (MacKenzie and Myers 2007, Fisheries Research).

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Mapping is an important tool for the management of plant invasions. If landscapes are mapped in an appropriate way, results can help managers decide when and where to prioritize their efforts. We mapped vegetation with the aim of providing key information for managers on the extent, density and rates of spread of multiple invasive species across the landscape. Our case study focused on an area of Galapagos National Park that is faced with the challenge of managing multiple plant invasions. We used satellite imagery to produce a spatially-explicit database of plant species densities in the canopy, finding that 92% of the humid highlands had some degree of invasion and 41% of the canopy was comprised of invasive plants. We also calculated the rate of spread of eight invasive species using known introduction dates, finding that species with the most limited dispersal ability had the slowest spread rates while those able to disperse long distances had a range of spread rates. Our results on spread rate fall at the lower end of the range of published spread rates of invasive plants. This is probably because most studies are based on the entire geographic extent, whereas our estimates took plant density into account. A spatial database of plant species densities, such as the one developed in our case study, can be used by managers to decide where to apply management actions and thereby help curtail the spread of current plant invasions. For example, it can be used to identify sites containing several invasive plant species, to find the density of a particular species across the landscape or to locate where native species make up the majority of the canopy. Similar databases could be developed elsewhere to help inform the management of multiple plant invasions over the landscape.