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Abstract
Dinamica_EGO LUCC Urban Expansion
... Calibration was performed on a single model, and the terms simulation and projection, although referring to the same model, are used to differentiate the use of the model in different stages. The historical transition matrix calculates the net rate of change from one land use and land cover class to another in a given time step (Soares-Filho et al., 2009). The matrix was calculated in multiple time steps, which indicated the annual rate of change from state i to state j within a 5-year time window. ...
... According to Soares-Filho et al. (2009), when the future projection of LULC is based on patterns of changes that occurred in the past and not on simulation of alternative scenarios, DINAMICA EGO uses weights of evidence approach, thus defining the transition probability of each pixel. According to Thompson et al. (2020), this method is based on a modified form of Bayes' conditional probability theorem; it derives weights so that the effect of each spatial variable on a LULC transition is calculated independently. ...
... The values assigned as limits to determine the independence between the variables used are less than 0.5, as suggested by Bonham-Carter (1994). Thus, variables that are correlated with each other should be removed from the model or associated with a third variable (Soares-Filho et al., 2009). In addition to the probability maps of transitions originated by the weights of evidence, the model for the simulation uses transitions functions. ...
The hydrological parameter Curve Number (CN) was projected in the future in a 30 m spatial resolution grid for the Amazon. Through the DINAMICA EGO platform, Land Use and Land Cover (LULC) were calibrated, simulated, validated, and projected for 2049 in a five-year time frame from 2009. The reclassified LULCs of 2009, 2014, and 2019 of the MapBiomas 5.0 project were used as input to DINAMICA EGO. Calibration was prepared using the 2009 and 2014 maps and the 2014 simulated map; the validation was carried out using the 2014 map, 2019, and 2019 simulated. In the calibration, the multiple window similarity values were all above 50% for the models of each basin, except for the Tapajós which was 40% in spatial resolution of 255 m. Validation values ranged between 36% and 76% at a spatial resolution of 255 m. Concerning the future projection of CN, the average CN of the Amazon region is equal to 77. The highest values of CN were found in the southern regions of the basins of the Xingu, Tapajós, Madeira, and throughout the basins of the Araguaia and Tocantins. In this Amazon region, in 2049, the areas of high CN will increase due to forest conversion to pasture/agriculture, implying larger runoff and flooding, including the urban areas, which will also expand. These floods will be intensified concerning those that already occur in the Amazon.
In an era of rapid climate and land transformation, it is increasingly important to understand how future changes impact natural systems. Scenario studies can offer the structure and perspective needed to understand the impacts of change and help inform management and conservation decisions. We implemented a scenario-based approach to assess how two high impact drivers of landscape change influence the distributions of managed wildlife species (n = 10) in the New England region of the northeastern United States. We used expert derived species distribution models (SDMs) and scenarios developed by the New England Landscape Futures Project (NELFP) to estimate how species distributions change under various trajectories (n = 5) of landscape change. The NELFP scenarios were built around two primary drivers – Socio-Economic Connectedness (SEC) and Natural Resource Planning and Innovation (NRPI) – and provide plausible alternatives for how the New England region may change over 50 years (2010–2060). Our models generally resulted in species occurrence and richness declines by 2060. The majority of species (7 of 10) experienced declines in regional occurrence for all NELFP scenarios, and one species experienced a projected increase in mean regional occurrence for all scenarios. Our results indicate that the NRPI and SEC drivers strongly influenced projected distribution changes compared to baseline projections. NRPI had a greater impact on distribution change for five species (coyote, moose, striped skunk, white-tailed deer, and wild turkey), while SEC had a greater impact on four species (American black bear, bobcat, raccoon, and red fox); one species (gray fox) was equally influenced by both NRPI and SEC. These results emphasize the importance of integrating both natural resource planning and socio-economic factors when addressing issues of distribution change and offer insights that can inform proactive management and conservation planning.
Deforestation driven by agricultural expansion is a major threat to the biodiversity of the Amazon Basin. Modelling how deforestation responds to environmental policy implementation has thus become a policy relevant scientific undertaking. However, empirical parameterization of land-use/cover change (LUCC) models is challenging due to the high complexity and uncertainty of land-use decisions. Bayesian Network (BN) modelling provides an effective framework to integrate various data sources including expert knowledge. In this study, we integrate remote sensing products with data from farm-household surveys and a decision game to model LUCC at the BR-163, in Brazil. Our ‘business as usual’ scenario indicates cumulative forest cover loss in the study region of 8,000 km² between 2014 and 2030, whereas ‘intensified law-enforcement’ would reduce cumulative deforestation to 1,600 km² over the same time interval. Our findings underline the importance of conservation law enforcement in modulating the impact of agricultural market incentives on land cover change.
Abstract The effects of Amazon deforestation have been simulated with a coupled general circulation model (GCM). The deforestation influences the global tropics, and in
Received 7 May 2007; revised 7 August 2007; accepted 9 August 2007; published 13 September 2007. (1) Field observations and numerical studies revealed that large scale deforestation in Amazonia could alter the regional climate significantly, projecting a warmer and somewhat drier post-deforestation climate. In this study we employed the CPTEC-INPE AGCM to assess the effects of Amazonian deforestation on the regional climate, using simulated land cover maps from a business-as-usual scenario of future deforestation in which the rainforest was gradually replaced by degraded pasture or by soybean cropland. The results for eastern Amazonia, where changes in land cover are expected to be larger, show increase in near-surface air temperature, and decrease in evapotranspiration and precipitation, which occurs mainly during the dry season. The relationship between precipitation and deforestation shows an accelerating decrease of rainfall for increasing deforestation for both classes of land use conversions. Continued expansion of cropland in Amazonia is possible and may have important consequences for the sustainability of the region's remaining natural vegetation. Citation: Sampaio, G., C. Nobre, M. H. Costa, P. Satyamurty, B. S. Soares-Filho, and M. Cardoso (2007), Regional climate change over eastern Amazonia caused by pasture and soybean cropland expansion, Geophys. Res. Lett., 34, L17709,
The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300 Mg ha−1 here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300 Mg ha−1. Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200 Mg ha−1. The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and belowground biomass, is 86 Pg C with ±20% uncertainty.
Rural Amazonians, especially Indians, extractivists and other forest dwellers, desperately need something that they can sell. Sale of material commodities taken from the rainforest is the focus of most attempts to encourage ‘sustainable development’ for these populations, but the mother lode waiting to be tapped is not a material commodity, but rather the forest's environmental services. Converting services like biodiversity maintenance, carbon storage and water cycling into monetary flows that can support a population of forest guardians requires crossing a series of hurdles. Reliable quantification of the magnitude of services being offered is a first necessity. How to convert forest environmental services into an income stream, and how to convert this stream into a foundation for sustainable development in rural Amazonia is a great challenge. Effort should be focused on tapping environmental services as a long-term strategy for maintaining both rainforest and its population. In addition to progressing toward long-term goals, immediate measures are needed to support the population and to avoid further loss of forest.
Many pathways have been proposed for including land use in a post-2012 climate agreement. Several involve new accounting structures which are quite different from the rules established in the Marrakech Accords and related decisions. However, a mechanism based largely on the structure agreed for the first commitment period also has its benefits. This paper discusses the weaknesses of the current system of land use, land-use change and forestry (LULUCF) accounting in the Kyoto Protocol's first commitment period, and proposes a mechanism based on that existing structure, but with modifications to address the weaknesses.
For the evaluation of results from remote sensing and high-resolution spatial models it is often necessary to assess the similarity of sets of maps. This paper describes a method to compare raster maps of categorical data. The method applies fuzzy set theory and involves both fuzziness of location and fuzziness of category. The fuzzy comparison yields a map, which specifies for each cell the degree of similarity on a scale of 0 to 1. Besides this spatial assessment of similarity also an overall value for similarity is derived. This statistic corrects the cell-average similarity value for the expected similarity. It can be considered the fuzzy equivalent of the Kappa statistic and is therefore called KFuzzy. A hypothetical case demonstrates how the comparison method distinguishes minor changes and fluctuations within patterns from major changes. Finally, a practical case illustrates how the method can be useful in a validation process.
The current annual rates of tropical deforestation from Brazil and Indonesia alone would equal four-fifths of the emissions reductions gained by implementing the Kyoto Protocol in its first commitment period, jeopardizing the goal of Protocol to avoid dangerous anthropogenic interference with the climate system. We propose the novel concept of compensated reduction, whereby countries that elect to reduce national level deforestation to below a previously determined historical level would receive post facto compensation, and commit to stabilize or further reduce deforestation in the future. Such a program could create large-scale incentives to reduce tropical deforestation, as well as for broader developing country participation in the Kyoto Protocol, and leverage support for the continuity of the Protocol beyond the 20082012 first commitment period. Pages: 267-276
The distribution of sources and sinks of carbon among the world's ecosystems is uncertain. Some analyses show northern midlatitude lands to be a large sink, whereas the tropics are a net source(1); other analyses show the tropics to be nearly neutral. whereas northern mid-latitudes are a small sink(2,3). Here we show that the annual flux of carbon from deforestation and abandonment of agricultural lands in the Brazilian Amazon was a source of about 0.2 g C yr(-1)over the period 1989-1998 (1 Pg is 10(15)g). This estimate is based on annual rates of deforestation and spatially detailed estimates of deforestation, regrowing forests and biomass. Logging may add another 5-10 percent to this estimate(4), and fires may double the magnitude of the source in years following a drought(4), The annual source of carbon from land-use change and fire approximately offsets the sink calculated for natural ecosystems in the region(5,6). Thus this large area of tropical forest is nearly balanced with respect to carbon, but has an interannual variability of +/- 0.2 PgC yr(-1). Pages: 301-304
The DINAMICA model has been developed as a new tool to investigate trajectory of landscapes and dynamics of spatial phenomena. In this paper, we explore the capability of DINAMICA to reproduce a wide range of spatial patterns of change. First, we provide a short description of the DINAMICA architecture, and then we present and discuss the results of a series of simulations using simplified synthetic maps and varying the parameters of DINAMICAs transition functions. The simulation results are assessed by using selected landscape structure metrics, such as fractal dimension, patch cohesion index, and nearest neighbor distance. These simulation examples are used to show how DINAMICA can be calibrated, as well as its potential to replicate the evolving spatial patterns of a variety of dynamic phenomena. Pages: 721-728
Logging has been a much maligned feature of frontier development in the Amazon. Most discussions ignore the fact that logging can be part of a renewable, environmentally benign, and broadly equitable economic activity in these remote places. We estimate there to be some 4.5 +/- 1.35 billion m(3) of commercial timber volume in the Brazilian Amazon today, of which 1.2 billion m(3) is currently profitable to harvest, with a total potential stumpage value of 2.3 billion over 30 years. Indeed, on all land accessible to harvesting, the timber industry could produce an average of more than 16 million m(3) per year over a 30-year harvest cycle-entirely outside of current protected areas-providing 1.8 billion in sawnwood sales tax revenue. This level of harvest could be profitably complemented with an additional 10% from logging concessions on National Forests. This advance, however, should be realized only through widespread adoption of reduced impact logging techniques.
This paper examines the potential role of carbon sequestration in forests under a range of exogenously chosen carbon price paths. The price paths were chosen to simulate several different climate change policies. The results indicate that global sequestration could range from 48�147 Pg C by 2105 for carbon prices ranging from 800 per t C by the end of the century. The timing of sequestration is found to be sensitive to the assumed carbon price path. Low initial carbon prices (20 per t C in 2010) followed by rapid price increases, as might occur if policy makers try to stabilize future concentrations, suggest little, if any, sequestration during the next 20 years (-0.2 to 4.5 Pg C). If policy makers develop policies that support higher initial carbon prices, ranging from 100 per t C, 17 to 23 Pg C could be sequestered in forests over the next 20 years. Overall, our results indicate that forestry is not an efficient stopgap measure for long-term policy goals, but that it is instead an important long-term partner with other mitigation options.
Expansion of the cattle and soy industries in the Amazon basin has increased deforestation rates and will soon push all-weather highways into the region's core. In the face of this growing pressure, a comprehensive conservation strategy for the Amazon basin should protect its watersheds, the full range of species and ecosystem diversity, and the stability of regional climates. Here we report that protected areas in the Amazon basin--the central feature of prevailing conservation approaches--are an important but insufficient component of this strategy, based on policy-sensitive simulations of future deforestation. By 2050, current trends in agricultural expansion will eliminate a total of 40% of Amazon forests, including at least two-thirds of the forest cover of six major watersheds and 12 ecoregions, releasing 32 +/- 8 Pg of carbon to the atmosphere. One-quarter of the 382 mammalian species examined will lose more than 40% of the forest within their Amazon ranges. Although an expanded and enforced network of protected areas could avoid as much as one-third of this projected forest loss, conservation on private lands is also essential. Expanding market pressures for sound land management and prevention of forest clearing on lands unsuitable for agriculture are critical ingredients of a strategy for comprehensive conservation.
Carbon emissions from tropical deforestation account for about 25% of all anthropogenic
carbon dioxide emissions but cannot be credited under current climate change agreements.
In the discussions around the architecture of the post-2012 climate regime, the possibility of
including credits for reduced emissions from deforestation arises. The paper reviews two
approaches for this, compensated reductions (CR) as proposed by Santilli et al. and the Joint
Research Centre proposal that combine voluntary commitments by non-Annex I countries to
reduce emissions from deforestation with carbon market financing. Both approaches have
the clear advantages of simplicity and the possibility of fitting to an evolving greenhouse gas
emission reduction regime. The authors consider the strengths and limitations of each
proposal and build upon them to address several implementation challenges and options for
improvement. Given the urgency of avoiding dangerous climate change, the timely development
of technically sound, politically acceptable, cost-effective and practicable measures
to reduce emissions from deforestation and forest degradation is essential. These two
approaches take us a step closer to this goal, but they need to be refined rapidly to enable this
goal to be realised.
This report describes a program, FRAGSTATS, developed to quantify landscape structure. Two separate versions of FRAGSTATS exist: one for vector images and one for raster images. In this report, each metric calculated by GRAGSTATS is described in terms of its ecological application and limitations. Example landscapes are included, and a discussion is provided of each metric as it relates to the sample landscapes. -from Authors
This paper outlines a taxonomy of spatial econometric model specifications that incorporate spatial externalities in various ways. The point of departure is a reduced form in which local or global spillovers are expressed as spatial multipli-ers. From this, a range of familiar and less familiar specifications is derived for the structural form of a spatial regression.
New genemlized statistical methods to measure agreement between two maps at multiple-resolutions, where each cell in each map has a multinomial distribution among any number of categories, are presented. This methodology quantifies agreement between any two categorical maps, where either map uses fuzzy or crisp classification. The method measures the agreement at various resolutions by aggregating neighboring cells into an increasingly coarse grid. At each resolution, the method partitions the overall agreement into correct due to chance, correct due to quantity, correct due to location, error due to location, and error due to quantity. In addition, the method computes six statistics that are useful to interpret the difierences between maps, and shows how these statistics change with resolution. This technique is particularly useful for characterizing land-cover change and for validating land-cover change models. For illustration, this paper applies these theoretical concepts to the validation of a land-use change model for Costa Rica.
The spatial distribution of human activities in forest frontier regions is strongly influenced by transportation infrastructure. With the planned paving of 6000 km of highway in the Amazon Basin, agricultural frontier expansion will follow, triggering potentially large changes in the location and rate of deforestation. We developed a land-cover change simulation model that is responsive to road paving and policy intervention scenarios for the BR-163 highway in central Amazonia. This corridor links the cities of Cuiabá, in central Brazil, and Santarém, on the southern margin of the Amazon River. It connects important soybean production regions and burgeoning population centers in Mato Grosso State with the international port of Santarém, but 1000 km of this road are still not paved. It is within this context that the Brazilian government has prioritized the paving of this road to turn it into a major soybean exportation facility. The model assesses the impacts of this road paving within four scenarios: two population scenarios (high and moderate growth) and two policy intervention scenarios. In the ‘business-as-usual’ policy scenario, the responses of deforestation and land abandonment to road paving are estimated based on historical rates of Amazon regions that had a major road paved. In the ‘governance’ scenario, several plausible improvements in the enforcement of environmental regulations, support for sustainable land-use systems, and local institutional capacity are invoked to modify the historical rates. Model inputs include data collected during expeditions and through participatory mapping exercises conducted with agents from four major frontier types along the road. The model has two components. A scenario-generating submodel is coupled to a landscape dynamics simulator, ‘DINAMICA’, which spatially allocates the land-cover transitions using a GIS database. The model was run for 30 years, divided into annual time steps. It predicted more than twice as much deforestation along the corridor in business-as-usual vs. governance scenarios. The model demonstrates how field data gathered along a 1000 km corridor can be used to develop plausible scenarios of future land-cover change trajectories that are relevant to both global change science and the decision-making process of governments and civil society in an important rainforest region.
The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. In the present contribution several estimates of forest biomass are compared for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. Three questions were posed: First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas?
The answer to the first two questions is that estimates of biomass for Brazil's Amazonian forests (including dead and belowground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modelling of forest recovery following observed stand-replacing disturbances, and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.
We developed a process-based model of forest growth, carbon cycling and land-cover dynamics named CARLUC (for CARbon and Land-Use Change) to estimate the size of terrestrial carbon pools in terra firme (nonflooded) forests across the Brazilian Legal Amazon and the net flux of carbon resulting from forest disturbance and forest recovery from disturbance. Our goal in building the model was to construct a relatively simple ecosystem model that would respond to soil and climatic heterogeneity that allows us to study the impact of Amazonian deforestation, selective logging and accidental fire on the global carbon cycle. This paper focuses on the net flux caused by deforestation and forest re-growth over the period from 1970 to 1998. We calculate that the net flux to the atmosphere during this period reached a maximum of ∼0.35 PgC yr−1 (1 PgC= 1 × 1015 gC) in 1990, with a cumulative release of ∼7 PgC from 1970 to 1998. The net flux is higher than predicted by an earlier study (Houghton et al., 2000) by a total of 1 PgC over the period 1989–1998 mainly because CARLUC predicts relatively high mature forest carbon storage compared with the datasets used in the earlier study. Incorporating the dynamics of litter and soil carbon pools into the model increases the cumulative net flux by∼1 PgC from 1970 to 1998, while different assumptions about land-cover dynamics only caused small changes. The uncertainty of the net flux, calculated with a Monte-Carlo approach, is roughly 35% of the mean value (1 SD).
The “weights of evidence” statistical method, previously applied to the problem of relating mineral occurrences to geological and geomorphological features, has been applied to the question of whether in a particular area there may be a spatial correlation between seismic epicenters and various geological and geophysical parameters. We find that seismicity in western Quebec is associated with NNE-trending drainage features and positive aeromagnetic anomalies. Our interpretation is that NNE-trending zones of weakness are being re-activated in the presence of a NE-SW regional compressive stress field and that less competent zones in the upper crust, as delineated by positive aeromagnetic anomalies, are causing stress and, hence, seismicity to be concentrated in the subjacent middle crust.
The dynamics of the Atlantic Rainforest loss and recovery are still not fully understood despite its long history of human occupation. In this study, we investigated changes in an Atlantic Rainforest region due to major biophysical and human proximate causes. First, we modeled land-cover and land-use changes from 1962 to 2000, including deforestation and forest regrowth, and thereby simulated future landscape trajectories to assess their possible effects on the conservation of forest species of the Ibiúna Plateau, a region located in Southeastern Brazil within the Atlantic Rainforest biome. We modeled four scenarios (status quo, random, lawenforcement, and land-use intensification) and simulated their resulting landscape trajectories for the year 2019 using DINAMICA. The landscape dynamics in the study region were particularly intense. During the first period of 1962–1981, the rate of forest regrowth (3% year−1) was greater than the rate of deforestation (2% year−1), whereas in the latter period of 1981–2000, increasing urbanization and the spreading of rural establishments resulted in more deforestation (2.9% year−1) than regrowth (1% year−1). These dynamics imprinted a heterogeneous landscape, leading to the predominance of progressively younger secondary forests with increasingly less capacity of hosting sensitive forest species. The influence of proximate causes on the dynamics of deforestation and forest regrowth showed consistent patterns, such as higher forest regrowth rates near rivers, on steep slopes and far from dirt roads, whereas losses in young secondary vegetation and forest were far from rivers, on gentle slopes and near urban areas. Of the modeled scenarios, only the law enforcement scenario may lead to the recovery of a network of interconnected forest patches, suggesting that simply the enforcement of current forest laws, which prohibit deforestation on unsuitable agricultural areas and along river margins and establish a minimum of 20% of forest remnant per rural property, may effectively favor forest species conservation in the short term (two decades) without the need of any forest restoration effort.
dinamica, a spatially explicit simulation model of landscape dynamics has been developed. dinamica is a cellular automata model that presents multi-scale vicinity-based transitional functions, incorporation of spatial feedback approach to a stochastic multi-step simulation engine, and the application of logistic regression to calculate the spatial dynamic transition probabilities. This model was initially conceived for the simulation of Amazonian landscape dynamics, particularly the landscapes evolved in areas occupied by small farms. For testing its performance, the model was used to simulate spatial patterns of land-use and land-cover changes produced by the Amazonian colonists in clearing the forest, cultivating the land, and eventually abandoning it for vegetation succession. The study area is located in an Amazonian colonization frontier in the north of Mato Grosso state, Brazil. The model was run for two sub-areas of colonization projects, using an 8-year time span, from 1986 to 1994. The simulated maps were compared with land-use and land-cover maps, obtained from digital classification of remote sensing images, using the multiple resolution fitting procedure and a set of landscape structure measures, including fractal dimension, contagion index, and the number of patches for each type of land-use and land-cover class. The results from the validation methods for the two areas showed a good performance of the model, indicating that it can be used for replicating the spatial patterns created by landscape dynamics in Amazonian colonization regions occupied by small farms. Possible applications of dinamica include the evaluation of landscape fragmentation produced by different architectures of colonization projects and the prediction of a region's spatial pattern evolution according to various dynamic phases.
Studies that relate changes in land cover with changes in river discharge at the small scale (<1 km2) are abundant. These studies generally indicate that deforestation causes an increase in the annual mean discharge. However, previous studies that evaluated the effects of changes in land cover in larger river basins (>100 km2) usually have not found similar relationships. Here we analyse a 50-year long time series of discharge of a tropical river, the Tocantins River at Porto Nacional (175,360 km2), as well as precipitation over this drainage area, during a period where substantial changes in land cover occurred in the basin (1949–1998). Based on agricultural census data, we estimate that, in 1960, about 30% of the basin was used for agriculture. Previous work indicates that by 1995, agriculture had increased substantially, with about 49% of the basin land used as cropland and pastures. Initially, we compare one period with little changes in land cover (period 1-1949–1968) with another with more intense changes in land cover (period 2-1979–1998). Our analysis indicates that, while precipitation over the basin is not statistically different between period 1 and period 2 (α=0.05), annual mean discharge in period 2 is 24% greater than in period 1 (P<0.02), and the high-flow season discharge is greater by 28% (P<0.01). Further analyses present additional evidence that the change in vegetation cover altered the hydrological response of this region. As the pressure for changes in land cover in that region continue to increase, one can expect important further changes in the hydrological regime of the Tocantins River.
Quantitatively evaluating the goodness of fit of ecological simulation models is difficult, and no generally agreed upon method has evolved. This paper presents a method for quantifying the goodness of fit of spatial and/or time series data and models based on measuring the similarity of the patterns, and the idea that measurement at one resolution is not sufficient to describe complex patterns. The method yields indices that summarize the way the fit changes as the resolution of measurement changes. An expanding ‘window’ is used to gradually degrade the resolution of the comparison. Lack of fit can be partitioned into ‘registration’, ‘resolution’ and residual components. This allows a better understanding of the underlying patterns and type of correspondence. Multiple resolution methods yield additional information not contained in single resolution methods that is necessary to adequately evaluate the performance of complex ecological models.
Carbon emissions from tropical deforestation account for about 25% of all anthropogenic carbon dioxide emissions but cannot be credited under current climate change agreements. In the discussions around the architecture of the post-2012 climate regime, the possibility of including credits for reduced emissions from deforestation arises. The paper reviews two approaches for this, compensated reductions (CR) as proposed by Santilli et al. and the Joint Research Centre proposal that combine voluntary commitments by non-Annex I countries to reduce emissions from deforestation with carbon market financing. Both approaches have the clear advantages of simplicity and the possibility of fitting to an evolving greenhouse gas emission reduction regime. The authors consider the strengths and limitations of each proposal and build upon them to address several implementation challenges and options for improvement. Given the urgency of avoiding dangerous climate change, the timely development of technically sound, politically acceptable, cost-effective and practicable measures to reduce emissions from deforestation and forest degradation is essential. These two approaches take us a step closer to this goal, but they need to be refined rapidly to enable this goal to be realised.
The evaluation of the spatial similarities and land use change between two raster maps is traditionally based on pixel-by-pixel comparison techniques. However, a pixel-by-pixel comparison can register a small displacement in pixels as land use disagreement even though the land use patterns may be essentially the same. The techniques of unique polygons mapping and hierarchical fuzzy pattern matching, where the maps are compared on both a local and global level, are combined to provide a more robust alternative approach. Local matchings determine the degree of containment of each unique polygon in the template map in terms of fuzzy areal intersections. Formally, the local agreement values are based on polygon property containments and are calculated from a fuzzy logical Max-Min compositional algorithm. A global agreement value is derived by the fuzzy summation of the local matchings. The uses of these basic methods are discussed and further refinements and modelling possibilities are outlined.
Reimpresión en 2002 Incluye bibliografía e índice
A text detailing critical aspects of geographic information systems for land resources assessment. Nine chapters cover themes on: 1. Overview of GIS components - computer mapping, data bases, future directions. 2. Data structures for thematic maps, including files, spatial data definitions, vector and raster structures, database facilities. 3. Digital elevation models. 4. Data input, verification, storage and output. 5. Methods of spatial data analysis and modelling, ranging from basic map overlay, to natural language processing. 6. Data quality, errors, and the nature of spatial data on maps. 7. Classification techniques - multivariate, and using expert systems. 8. Spatial interpolation methods. 9. Selecting a GIS. Each chapter has a list of references, and two appendices give a glossary of terms, and a list of selected information sources.-after Author
How to Distribute REDD Funds Across Countries? A Stock-Flow Mechanism. Submission to the United Nations Framework Convention on Climate Change regarding AWG-LCA
- A Cattaneo
Cattaneo, A. How to Distribute REDD Funds Across Countries? A Stock-Flow Mechanism.
Submission to the United Nations Framework Convention on Climate Change regarding
AWG-LCA (FCCC/AWGLCA/2008/L.7) (2008).
Monitoramento da Floresta Amazônica Brasileira por Satélite ‐ Projeto PRODES. [online] <http://www FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure
- K Mcgarigal
- B J Marks
INPE (Instituto Nacional de Pesquisas Espaciais). Monitoramento da Floresta Amazônica
Brasileira por Satélite ‐ Projeto PRODES. [online] <http://www.obt.inpe.br/prodes>
(2007)
McGarigal, K. and Marks, B.J. FRAGSTATS: Spatial pattern analysis program for quantifying
landscape structure. PNW‐GTR‐351. U.S. Department of Agriculture, Forest Service,
Pacific Northwest Research Station, Portland. (1995).
How to deal with non-obvious rules for biodiversity conservation in fragmented landscapes?
- J P Metzger
Metzger, J.P. How to deal with non-obvious rules for biodiversity conservation in fragmented
landscapes? The Brazilian Journal of Nature Conservation 4, 125-139 (2006).
Balancing conservation and economic sustainability: the future of the Amazon timber industry doi: 10.1007/s00267‐009‐9337‐1 Pontius, R.G.Jr. Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions
- F Merry
- B S Soares‐filho
- D Nepstad
- G Amacher
- H Rodrigues
Merry, F., Soares‐Filho, B.S., Nepstad, D., Amacher, G. and Rodrigues, H. Balancing
conservation and economic sustainability: the future of the Amazon timber industry.
Environmental Management (2009). doi: 10.1007/s00267‐009‐9337‐1
Pontius, R.G.Jr. Statistical methods to partition effects of quantity and location during
comparison of categorical maps at multiple resolutions. Photogrammetric Engineering
and Remote Sensing 68, 1041‐1049 (2002).
- L Anselin
- Externalities
Anselin, L. Spatial Externalities, Spatial Multipliers and Spatial Econometrics. (University of
Illinois, Urbana-Champaign, 2002).