Cerrado biome, home of many plants endemic species, is suffering significant habitat loss due to anthropic actions, including natural cover loss and climate change. Here we assess how climate change and future natural cover loss will impact the distribution of endemic and threatened flora in the Cerrado, considering two scenarios related to the implementation of Brazil's Forest Code: the baseline scenario (BS), which reflects partial implementation, and the full implementation of Brazil's Forest Code (IFC). By 2050, distribution losses are projected at 33% under the SSP126 scenario, increasing to 37% and 41% under the SSP245 and SSP585 scenarios, respectively. Species are likely to retreat to the southern, southeastern, and central regions, which are the richest in species but will face the most severe reductions. Despite the IFC scenario offering better protection, nearly all species (239) will still experience distribution reductions, even under the most favorable scenarios in this analysis. The study confirms that both climate and natural cover loss will significantly diminish the geographical range of most species by 2050, particularly in areas with the highest current richness. This trend could lead to increased extinction risks, which could be reduced with the full implementation of the Forest Code.

The geography of urban crime has often been associated with the city's geography. In this study we analyze the geography of street robbery and its relation to the various urban patterns in the city of São Paulo. First, we analyze how different variables influence the spatial distribution of street robbery, using a combination of geospatial and statistical methodologies. Then, we analyze how these different variables behave over the city of São Paulo according to eight types of urban patterns. Finally, we interpret the resulting body of evidence considering existing criminological theory. Our results suggest that the geography of street robbery in São Paulo is a result of two main drivers: (1) accessibility and population flow, tied to key roadways in the city, and (2) social issues, tied to high murder rates and, in a smaller degree, low income. Within the city's geography, these two factors tend to not align spatially and are sometimes diametrically opposite. As we found, the geography of street robbery in São Paulo is a middle of the way between these two drivers, albeit closer to the social issues driver. We also discuss some policy implications and possibilities for future research.

Land-use and land-cover change (LULCC) models are important tools for environmental policy planning. LULCC models are frequently constrained to the generation of projections at a specific resolution. However, subsequent studies or models may require finer resolutions. In this work, a downscaling method for LULCC models is proposed that uses a mathematical programming approach to disaggregate the multiple layers of the land-use change projections while respecting a series of constraints. The method is calibrated and validated with MapBiomas data for the years 2000 and 2018 converted for the GLOBIOM-Brazil model, successfully predicting land-use at a finer resolution. Also, as proof of concept, the calibrated model is also applied for GLOBIOM-Brazil projections for 2050. This paper advances the state-of-the-art by proposing and testing a downscaling method using a mathematical programming approach with spatial effects, that operates on multi-layered land-use projections with a range of constraints while allowing flexibility on the number and type of the specific layers and constraints.

This study examines how land tenure constrains Brazil’s ability to meet its deforestation control and forest restoration goals in its Amazonia biome. Our findings are based on an updated assessment of land tenure and land use in the region. Between 2019 and 2021, 44% of deforestation in Amazonia occurred in private lands, while forest removal in settlements ranged from 31% to 27% of the total. Deforestation in undesignated public lands increased from 11% in 2008 to 18% in 2021. Deforestation is highly concentrated, with 1% of properties accounting for 82.5% of forest cuts in 2021. In Amazonia, there is considerable non-compliance with the legal reserve provisions set by Brazil’s Forest Code. Legal reserve deficits in private lands sum up to 18.17 Mha (million hectares), compared with 12.49 Mha of legal reserve surpluses. Even if all forest surpluses are offered in the forest credits market set in the Forest Code, farmers still need to restore 5.67 Mha to comply with the law. Large-scale cattle ranchers have a legal reserve deficit of 10.35 Mha (34% of their area). Most crop farming occurs in medium and large properties (4.63 Mha) with a large proportion of legal reserve deficits (45%). Given the political power and financial resources of large ranchers and crop producers, Brazil faces major challenges in inducing these farmers to meet their legal obligations. Therefore, Brazil needs to combine robust command-and-control strategies with market-based policies to achieve its deforestation and forest restoration goals. The government should tailor forest protection and restoration policies to the needs of different landowners, considering their land use practices, technical capacity, and financial resources.

Communities across the United States are continually impacted by natural hazards, leading to material and human losses. Natural Hazard Vulnerability (NHV) assessments can help identify variables that can increase the community's susceptibility to these losses. Several studies have assessed NHV, but few have accounted for specific losses or considered more than one dimension of vulnerability (typically, social vulnerability is assessed). This study assessed NHV at the county level in the United States, considering five dimensions (social, environmental, institutional, economic, and health) during two years (2000 and 2010) and accounting for damages and casualties. Results provide valuable and generalized insights on how NVH manifests in society. It confirms that NHV should be assessed by particular impact and that it is dynamic: sets of variables associated with heightened losses can change over time and when evaluating distinct impacts (damages and casualties). This study emphasizes the importance of tailoring NHV assessments to specific impacts and underscores the dynamic nature of these assessments, providing valuable insights for both researchers and decision-makers enabling the development of more effective risk-reduction strategies.

In Brazil, conservation priority zones, in spite of their key role in preserving natural vegetation and its environmental resources are frequently located outside the country’s public network of protected areas (PAs). Here we present the first study on land-use impacts inside Brazil’s unprotected (i.e. outside PAs) Cost-Effective conservation priority Zones (CEZs), for the period 2020–2050. CEZs are conservation priority zones that had experienced low levels of human impact in 2020. In this study, we consider various governance scenarios, including different deforestation control and native vegetation restoration policies. To this end, a land-use change model is combined with a downscaling method to generate natural vegetation cover projections at a 0.01 ∘ resolution. Results, which include the effects of climate change on the expansion of the Brazilian agriculture, project native vegetation losses (through deforestation) or gains (through restoration) inside unprotected CEZs. If the current pattern of disregard for the environment persists, our results indicate that a large share of the native vegetation inside Brazil’s CEZs is likely to disappear, with negative impacts on biodiversity preservation, green-house gas emissions and ecosystem services in general. Moreover, even if fully implemented and enforced, Brazil’s current Forest Code is insufficient to adequately protect CEZs from anthropization, especially in the Cerrado biome. We expect that this study can help improving the conservation and restoration of CEZs in Brazil.

Green crimes are violations of environmental laws that aim to protect human well-being, natural resources, and ecosystems. Brazil has recorded an increase in green crimes in recent years. In this study, we used Spatial Durbin and other regression models to analyze the relationship between land use and green crime. We test whether there is a positive association between green crimes and the following land uses: urban edge areas, rural edge areas, and mixed urban uses. The results show that green crimes are spatially related to areas of high contact and exposure between human activity and the natural environment (urban and rural mixed uses), but that human presence by itself (presence of industrial activity) is not particularly associated with the occurrence of green crimes. These findings can serve to design and deploy data-driven policies and policing of green crimes.

In its Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change, Brazil committed to reducing greenhouse gas emissions and restoring its forests. This study examines the challenges of fulfilling these commitments in Brazilian Amazonia. We carry out a detailed assessment of the current status of land tenure in the region and its relation to deforestation. After dealing with conflicts and overlaps between data from various sources, we produce a new map of public and private land tenure in Amazonia. Combining this map with Brazil's official data on deforestation, we find out how much natural vegetation has been preserved in each public or private area. The result is used to estimate how much deforestation is illegal. We also establish how much deforestation is associated with each land tenure type. Our results show that most deforestation inside rural properties is done by a few landowners, a finding that has important consequences for law enforcement. We then assess the challenges for reforestation in detail. To do so, we consider how much forest needs to be rehabilitated according to Brazil's Forest Code. Our analysis provides a comprehensive appraisal of the potential opportunity costs for forest restoration in the biome, considering farm size and land use. This analysis provides insights into targeted land use policies that can meet Brazil’s forest restoration goals.

Although income inequality has been often pointed out as an important cause of crime, it is yet unclear how spatial patterns of income in a city can explain its geography of crime. In this study, we apply a model to test the influence of income inequality on the spatial concentration of residential burglaries in the city of Campinas, Brazil. Following criminological theory, our model decomposes income inequality into two hypothetical effects: that of local income, which determines how attractive residences are to burglary, and exposure to poverty, where poverty boosts criminal motivation through economic hardship. Our study reveals that higher local income is indeed significant and positively associated to higher burglary risk, but that exposure to poverty does not increase risk. Therefore, higher income areas more surrounded by poor areas do not feature a particularly increased burglary risk if compared to other higher income areas, contrary to what could be expected from some criminological frameworks such as relative deprivation and strain theories. Instead, our findings suggest that the geography of residential burglaries can be explained by the distribution of burglary opportunities, that is, of where the most profitable targets are. To conclude, we compare our findings to other existing studies.

Standardized crime rates (e.g., “homicides per 100,000 people”) are commonly used in crime analysis as indicators of victimization risk but are prone to several issues that can lead to bias and error. In this study, a more robust approach (GWRisk) is proposed for tackling the problem of estimating victimization risk. After formally defining victimization risk and modeling its sources of uncertainty, a new method is presented: GWRisk uses geographically weighted regression to model the relation between crime counts and population size, and the geographically varying coefficient generated can be interpreted as the victimization risk. A simulation study shows how GWRisk outperforms naïve standardization and Empirical Bayesian Estimators in estimating risk. In addition, to illustrate its use, GWRisk is applied to the case of residential burglaries in Belo Horizonte, Brazil. This new approach allows more robust estimates of victimization risk than other traditional methods. Spurious spikes of victimization risk, commonly found in areas with small populations when other methods are used, are filtered out by GWRisk. Finally, GWRisk allows separating a reference population into segments (e.g., houses, apartments), estimating the risk for each segment even if crime counts were not provided per segment.

Objectives Crime counts are sensitive to granularity choice. There is an increasing interest in analyzing crime at very fine granularities, such as street segments, with one of the reasons being that coarse granularities mask hot spots of crime. However, if granularities are too fine, counts may become unstable and unrepresentative. In this paper, we develop a method for determining a granularity that provides a compromise between these two criteria. Methods Our method starts by estimating internal uniformity and robustness to error for different granularities, then deciding on the granularity offering the best balance between the two. Internal uniformity is measured as the proportion of areal units that pass a test of complete spatial randomness for their internal crime distribution. Robustness to error is measured based on the average of the estimated coefficient of variation for each crime count. Results Our method was tested for burglaries, robberies and homicides in the city of Belo Horizonte, Brazil. Estimated "optimal" granularities were coarser than street segments but finer than neighborhoods. The proportion of units concentrating 50% of all crime was between 11% and 23%. Conclusions By balancing internal uniformity and robustness to error, our method is capable of producing more reliable crime maps. Our methodology shows that finer is not necessarily better in the micro-analysis of crime, and that units coarser than street segments might be better for this type of study. Finally, the observed crime clustering in our study was less intense than the expected from the law of crime concentration.

The relationship between crime and income inequality is a complex and controversial issue. While there is some consensus that a relationship exists, the nature of it is still the subject of much debate. In this paper, this relationship is investigated in the context of urban geography and whether income inequality can explain the geography of crime within cities. This question is examined for the specific case of residential burglaries in the city of Belo Horizonte, Brazil, where I tested how much burglary rates are affected by local average household income and by local exposure to poverty, while I controlled for other variables relevant to criminological theory, such as land-use type, density and accessibility. Different scales were considered for testing the effect of exposure to poverty. This study reveals that, in Belo Horizonte, the rate of burglaries per single family house is significantly and positively related to income level, but a higher exposure to poverty has no significant independent effect on these rates at any scale tested. The rate of burglaries per apartment, on the other hand, is not significantly affected by either average household income or exposure to poverty. These results seem consistent with a description where burglaries follow a geographical distribution based on opportunity, rather than being a product of localized income disparity and higher exposure between different economic groups.

Este trabalho apresenta um ambiente de visualizacao interativo em tempo-real para a simulacao do comportamento de risers rigidos verticais. O riser e um duto cilindrico essencial na extracao de oleo em aguas profundas e ultra-profundas, uma tarefa desafiadora que impoe diversas cargas sobre a estrutura. Ondas, correntes e movimentos da plataforma sao algumas dessas fontes de tensao, que podem levar a danos por fadiga ou mesmo rupturas. Simulacoes computacionais e uma ferramenta de grande valia para prevenir e diagnosticar tais problemas, mas em geral apresentam a desvantagem de produzir um grande volume de dados numericos de dificil interpretacao. Tecnicas de visualizacao cientifica podem ser utilizadas para representar os dados de uma maneira mais intuitiva e realista. Entretanto, os sistemas identificados na literatura apresentam limitacoes quanto a interacao em tempo-real. A visualizacao e realizada como um playback, apos a simulacao ter sido completado, e sempre que os parâmetros de simulacao sao alterados o usuario deve esperar um tempo consideravel enquanto os resultados sao recalculados. Neste trabalho, o ambiente desenvolvido permite a visualizacao do comportamento do riser com interacao em tempo-real, em que o novo comportamento do riser e obtido imediatamente apos os parâmetros de simulacao ser alterado pelo usuario. Abstract

Adessowiki (http://www.adessowiki.org) is a collaborative environment for development, documentation, teaching and knowledge repository of scientific computing algorithms. The system is composed of a collection of collaborative web pages in the form of a wiki. The articles of this wiki can embed programming code that will be executed on the server when the page is rendered, incorporating the results as figures, texts and tables on the document. The execution of code at the server allows hardware and software centralization and access through a web browser. This combination of a collaborative wiki environment, central server and execution of code at rendering time enables a host of possible applications like, for example: a teaching environment, where students submit their reports and exercises on Adessowiki without needing to install special software; authoring of texts, papers and scientific computing books, where figures are generated in a reproducible way by programs written by the authors; comparison of solutions and benchmarking of algorithms given that all the programs are executed under the same configuration; creation of an encyclopedia of algorithms and executable source code. Adessowiki is an environment that carries simultaneously documentation, programming code and results of its execution without any software configuration such as compilers, libraries and special tools at the client side.