The q-gradient method for global optimization

The q-gradient is an extension of the classical gradient vector based on the concept of Jackson's derivative. Here we introduce a preliminary version of the q-gradient method for unconstrained global optimization. The main idea behind our approach is the use of the negative of the q-gradient of the objective function as the search direction. In this sense, the method here proposed is a generalization of the well-known steepest descent method. The use of Jackson's derivative has shown to be an effective mechanism for escaping from local minima. The q-gradient method is complemented with strategies to generate the parameter q and to compute the step length in a way that the search process gradually shifts from global in the beginning to almost local search in the end. For testing this new approach, we considered six commonly used test functions and compared our results with three Genetic Algorithms (GAs) considered effective in optimizing multidimensional unimodal and multimodal functions. For the multimodal test functions, the q-gradient method outperformed the GAs, reaching the minimum with a better accuracy and with less function evaluations.Comment: 12 pages, 1 figur

Using policy scenarios to assess challenges and opportunities for reaching restoration targets in Brazil’s Atlantic Forest

Brazil’s Atlantic Forest is a global restoration hotspot. Most of the remaining forest areas are degraded and separated by large cities, and agricultural lands essential for national food security. Brazil’s restoration agenda is defined by multiple national and global restoration targets and policies, including Brazil’s Native Vegetation Protection Law (No. 12,651/2012) also known as the Forest Code, which sets minimum levels of native vegetation to be maintained or restored in rural properties. In this study we simulate the impacts of alternative restoration policies addressing targets for Brazil, and explore their impacts on selected terrestrial species and agricultural development potential in the Atlantic Forest biome. Our results show several policy options could result in different restoration amounts and spatial distributions being implemented between 2020 and 2050, but trade-offs between agriculture, biodiversity and rural livelihoods differ. Compared to the baseline scenario (implementation of the Forest Code), a scenario which focuses restoration on small farms (not mandated to undergo restoration under the current legislation) could increase forest area by 6.7 Mha across the biome (139% more than with the Forest Code), while a scenario which maximizes biodiversity gains could lead to an additional 3.9 Mha by 2050 (81% more compared to the Forest Code). We find that our restoration scenarios still allow cropland expansion and an increase in cattle herd, while pasturelands decrease. There are relatively small agricultural production losses under the alternative restoration scenarios when compared to the baseline (up to 14.4%), meaning that cattle ranching intensification is critical to enable large-scale restoration to co-exist with agricultural production. Our scenarios suggest that ambitious restoration targets in the Atlantic Forest biome (up to 15.5 Mha, consistent with existing regional initiatives) could be feasible with necessary improvements in pasture yield and a focus on scaling up support and developing restoration policies for smallholder farmers

A decentralized approach to model national and global food and land use systems

The achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO2 sink of 3.7 GtCO2e yr−1 over the period 2020–2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities

Expanding the soy moratorium to Brazil's Cerrado

The Cerrado biome in Brazil is a tropical savanna and an important global biodiversity hot spot. Today, only a fraction of its original area remains undisturbed, and this habitat is at risk of conversion to agriculture, especially to soybeans. Here, we present the first quantitative analysis of expanding the Soy Moratorium (SoyM) from the Brazilian Amazon to the Cerrado biome. The SoyM expansion to the Cerrado would prevent the direct conversion of 3.6 million ha of native vegetation to soybeans by 2050. Nationally, this would require a reduction in soybean area of approximately 2%. Relative risk of future native vegetation conversion for soybeans would be driven by the Brazilian domestic market, China, and the European Union. We conclude that, to preserve the Cerrado's biodiversity and ecosystem services, urgent action is required, including a zero native vegetation conversion agreement such as the SoyM

Eroding resilience of deforestation interventions—evidence from Brazil’s lost decade

Brazil once set the example for curtailing deforestation with command and control policies, but, in the last decade, these interventions have gone astray. Environmental research and policy today are largely informed by the earlier successes of deforestation interventions, but not their recent failures. Here, we investigate the resilience of deforestation interventions. We discuss how the recent trend reversal in Brazil came to be, and what its implications for the design of future policies are. We use newly compiled information on environmental fines in an econometric model to show that the enforcement of environmental policy has become ineffective in recent years. Our results add empirical evidence to earlier studies documenting the erosion of the institutions responsible for forest protection, and highlight the considerable deforestation impacts of this erosion. Future efforts for sustainable forest protection should be aimed at strengthening institutions, spreading responsibilities, and redistributing the common value of forests via incentive-based systems

Global optimization using q-gradients

Made available in DSpace on 2019-09-12T16:53:35Z (GMT). No. of bitstreams: 0 Previous issue date: 2016Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The q-gradient vector is a generalization of the gradient vector based on the q-derivative. We present two global optimization methods that do not require ordinary derivatives: a q-analog of the Steepest Descent method called the q-G method and a q-analog of the Conjugate Gradient method called the q-CG method. Both q-G and q-CG are reduced to their classical versions when q equals 1. These methods are implemented in such a way that the search process gradually shifts from global in the beginning to almost local search in the end. Moreover, Gaussian perturbations are used in some iterations to guarantee the convergence of the methods to the global minimum in a probabilistic sense. We compare q-G and q-CG with their classical versions and with other methods, including CMA-ES, a variant of Controlled Random Search, and an interior point method that uses finite-difference derivatives, on 27 well-known test problems. In general, the q-G and q-CG methods are very promising and competitive, especially when applied to multimodal problems. (C) 2016 Elsevier B.V. All rights reserved.[Gouvea, Erica J. C.; Soterroni, Aline C.; Scarabello, Marluce C.; Ramos, Fernando M.] Natl Inst Space Res INPE, Lab Comp & Appl Math, Sao Jose Dos Campos, SP, Brazil[Gouvea, Erica J. C.] Universidade de Taubaté (Unitau), Exact Sci Inst[Regis, Rommel G.] St Josephs Univ, Dept Math, Philadelphia, PA 19131 US

The impact of climate change on Brazil's agriculture

Brazilian agricultural production provides a significant fraction of the food consumed globally, with the country among the top exporters of soybeans, sugar, and beef. However, current advances in Brazilian agriculture can be directly impacted by climate change and resulting biophysical effects. Here, we quantify these impacts until 2050 using GLOBIOM-Brazil, a global partial equilibrium model of the competition for land use between agriculture, forestry, and bioenergy that includes various refinements reflecting Brazil's specificities. For the first time, projections of future agricultural areas and production are based on future crop yields provided by two Global Gridded Crop Models (EPIC and LPJmL). The climate change forcing is included through changes in climatic variables projected by five Global Climate Models in two emission pathways (RCP2.6 and RCP8.5) participating in the ISIMIP initiative. This ensemble of twenty scenarios permits accessing the robustness of the results. When compared to the baseline scenario, GLOBIOM-Brazil scenarios suggest a decrease in soybeans and corn production, mainly in the Matopiba region in the Northern Cerrado, and southward displacement of agricultural production to near-subtropical and subtropical regions of the Cerrado and the Atlantic Forest biomes

Current policies are insufficient to protect or restore Brazil’s cost-effective conservation priority zones

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 ${^\circ}$ 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

Projections for Land Use Change in Brazil: 2000-2050, links to files in ArcGIS shapefile format

This data set contains the inputs and the results of the REDD+ Policy Assessment Centre project (REDD-PAC) project (http://www.redd-pac.org), developed by a consortium of research institutes (IIASA, INPE, IPEA, UNEP-WCMC), supported by Germany's International Climate Initiative. Taking a new land use map of Brazil for 2000 as input, the research team used the global economic model GLOBIOM to project land use changes in Brazil up to 2050. Model projections show that Brazil has the potential to balance its goals of protecting the environment and becoming a major global producer of food and biofuels. The model results were taken into account by Brazilian decision-makers when developing the country's intended nationally determined contribution (INDC)

Future environmental and agricultural impacts of Brazil's Forest Code with GLOBIOM-Brazil, links to files in ArcGIS shapefile format

This data set contains the input data and the land-use change projections according to the various scenarios of the paper Soterroni et al. (2018, doi:10.1088/1748-9326/aaccbb). The paper contains the main findings of the REDD-PAC project (www.redd-pac.org) and it describes the GLOBIOM-Brazil model, the regional version of GLOBIOM model for Brazil, an important tool for the RESTORE+ project (www.restoreplus.org). Both projects are part of the International Climate Initiative (IKI) supported by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) based on a decision adopted by the German Bundestag