Designing an optimized landscape restoration with spatially interdependent non-linear models.

Brazilian Atlantic Forest is a biodiversity hotspot drastically fragmented due to different land use practices. Our understanding on the impacts of fragmentation and restoration practices on ecosystem functionality significantly increased during the last decades. However, it is unknown to our knowledge how a precision restoration approach, integrated with landscape metrics, will affect the decision-making process of forest restoration. Here, we applied Landscape Shape Index and Contagion metrics in a genetic algorithm for planning forest restoration in watersheds at the pixel level. We evaluated how such integration may configure the precision of restoration with scenarios related to landscape ecology metrics. The genetic algorithm worked toward optimizing the site, shape, and size of forest patches across the landscape according to the results obtained in applying the metrics. Our results, obtained by simulations of scenarios, support aggregation of forest restoration zones as expected, with priority restoration areas indicated where most of the aggregation of forest patches occurs. Our optimized solutions for the study area (Santa Maria do Rio Doce Watershed) predicted an important improvement of landscape metrics (LSI = 44 %; Contagion/LSI = 73 %). Largest shifts are suggested based on LSI (i.e., three larger fragments) and Contagion/LSI (i.e., only one well-connected fragment) optimizations. Our findings indicate that restoration in an extremely fragmented landscape will promote a shift toward more connected patches and with reduction of the surface:volume ratio. Our work explores the use of genetic algorithms to propose forest restoration based on landscape ecology metrics in a spatially explicit innovative approach. Our results indicate that LSI and Contagion:LSI ratio may affect the choice concerning precise location of restoration sites based on forest fragments scattered in the landscape and reinforce the usefulness of genetic algorithms to yield an optimized-driven solution for restoration initiatives.

Optimized allocation of forest restoration zones to minimize soil losses in watersheds.

Increase of water erosion is one of the main problems in watersheds all over the world and directly affects soil and water resources, causing economic and environmental losses. We proposed a combination of Genetic Algorithm and Erosion/Deposition modelling to allocate vegetation zones in order to reduce soil losses within watersheds. In this study, we have used Unit Stream Power Based Erosion Deposition (USPED) model to predict the spatial distribution of erosion and sediment deposition. Based on USPED estimates, Genetic Algorithm optimize site as well size of forest restoration zones in order to reduce soil losses. Proposed approach considered watershed entirely, in a cell-level optimization, to find the best possible arrangement of forest zones. For initial scenario, soil loss estimate was 2.045,55 ton. ha-1. year-1 and after optimization we achieved 52% reduction. Optimized forest zones formed connected and compacted patches, which enable field implementation. Methodology is also applicable to other watersheds around world.

Markov chains and cellular automata to predict environments subject to desertification.

The foremost objective of this study was to analyze the performance of a Markov chain/cellular automata model for predicting land use/land cover changes in environments predisposed to desertification. The study area is the Vieira river basin, located in Montes Claros (MG, Brazil). Land use/land cover prognosis was performed for the year 2005 so that this result could be compared with the ranked image for the same year, taken as ground truth. Kappa indices were used to evaluate the change level that occurred between these two cases. Results from cellular automata were evaluated from those of the Markov chain model. The latter proved to be efficient in the quantitative prediction of changes in land use/land cover. Regarding the cellular automata, an average performance was noted in the spatial distribution of classes. Specifically, with regard to desertification, the use of the CA-Markov model was effective at estimating the total area of the most susceptible class to this process, Bare Soil; however, it was inefficient in its spatialization. Even with the caveats related to the performance of cellular automata, the overall prediction capacity of CA-Markov models can be considered as good.

A new methodology for royalties distribution of the Itaipu hydroelectric plant: The hydrographic basin as the unit of analysis.

Over the past few years, many sectors such as energy generation, industry, domestic supply, and agriculture have encountered serious environmental problems due to the lack of rainfall. Thus, the purpose of this paper is to review the current methodology of royalties distribution from Itaipu hydroelectric plant. In the proposed approach, two criteria were considered to establish the division of Itaipu royalties: (1) the relative percentage of the water flow in the generation of electricity and, (2) the relative percentage of the drop in the height of water. 62 hydroelectric plants were evaluated in this study. In 52 plants the water flow was the factor that most contributed to the generation of electricity. In 2013, 346 municipalities benefited the Itaipu royalties. With the proposed methodology, 1,327 municipalities will receive the resource, what would increase the revenue of each of these municipalities by, on average, US$ 87,436.91 per year. The methodology presented herein proposes a reduction in the environmental disparity that now exists in Brazil, through improvement to Government instruments and environmental policies. The distribution of royalties throughout the watershed can provide additional resources to support payment programs for environmental services at the state and municipality levels.

Spatial and temporal distribution of urban heat islands.

The formation of an urban heat island (UHI) is one of the most common impacts of the urbanization process. To mitigate the effects of UHI, the planning of urban forests (e.g., creation of parks, forests and afforestation streets) has been the major tool applied in this context. Thus, the aim of this study is to evaluate the spatial and temporal distribution of heat islands in Vila Velha, ES, Brazil using the mono-window algorithm. The study followed these methodological steps: 1) mapping of urban green areas through a photointerpretation screen; 2) application of the mono-window algorithm to obtain the spatial and temporal patterns of land surface temperature (LST); 3) correlation between LST and the normalized difference vegetation index (NDVI) and normalized difference build-up index (NDBI); 4) application of ecological evaluation index. The results showed that the mean values of LST in urban areas were at least 2.34 to 7.19°C higher than undeveloped areas. Moreover, the positive correlation between LST and NDBI showed an amplifying effect of the developed areas for UHI, while areas with a predominance of vegetation attenuated the effect of UHI. Urban centers, clustered in some parts of the city, received the worst ecological assessment index. Finally, the adoption of measures to guide the urban forest planning within urban centers is necessary to mitigate the effect of heat islands and provide thermal comfort in urban areas.

Fuzzy logic applied to prospecting for areas for installation of wood panel industries.

Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops.

Itaipu royalties: The role of the hydroelectric sector in water resource management.

For countries dependent on hydroelectricity, water scarcity poses a real risk. Hydroelectric plants are among the most vulnerable enterprises to climate change. Investing in the conservation of the hydrographic basin is a solution found by the hydropower sector. Given the importance of the Itaipu plant to the energy matrix of Brazil and Paraguay, the aim of this study is to review the current distribution of royalties from Itaipu, using the hydrographic basin as a of criterion of analysis. Approximately 98.73% of the Itaipu basin is in Brazil. The flow contributes 99% of the total electricity generated there, while the drop height of the water contributes only 1%. Under the current policy, royalties are shared equally between Brazil and Paraguay. In the proposed approach, each country would receive a percentage for their participation in the drop height and water flow in the output of the turbines, which are intrinsic factors for electricity generation. Thus, Brazil would receive 98.35% of the royalties and Paraguay, 1.65%. The inclusion of the hydrographic basin as a criterion for the distribution of royalties will promote more efficient water resource management, since the payment will be distributed throughout the basin of the plant. The methodology can be applied to hydroelectric projects worldwide.

Geotechnology and landscape ecology applied to the selection of potential forest fragments for seed harvesting.

The Atlantic Forest biome is recognized for its biodiversity and is one of the most threatened biomes on the planet, with forest fragmentation increasing due to uncontrolled land use, land occupation, and population growth. The most serious aspect of the forest fragmentation process is the edge effect and the loss of biodiversity. In this context, the aim of this study was to evaluate the dynamics of forest fragmentation and select potential forest fragments with a higher degree of conservation for seed harvesting in the Itapemirim river basin, Espírito Santo State, Brazil. Image classification techniques, forest landscape ecology, and multi-criteria analysis were used to evaluate the evolution of forest fragmentation to develop the landscape metric indexes, and to select potential forest fragments for seed harvesting for the years 1985 and 2013. According to the results, there was a reduction of 2.55% of the occupancy of the fragments in the basin between the years 1985 and 2013. For the years 1985 and 2013, forest fragment units 2 and 3 were spatialized with a high potential for seed harvesting, representing 6.99% and 16.01% of the total fragments, respectively. The methodology used in this study has the potential to be used to support decisions for the selection of potential fragments for seed harvesting because selecting fragments in different environments by their spatial attributes provides a greater degree of conservation, contributing to the protection and conscious management of the forests. The proposed methodology can be adapted to other areas and different biomes of the world.

GIS applied to location of fires detection towers in domain area of tropical forest.

In most countries, the loss of biodiversity caused by the fires is worrying. In this sense, the fires detection towers are crucial for rapid identification of fire outbreaks and can also be used in environmental inspection, biodiversity monitoring, telecommunications mechanisms, telemetry and others. Currently the methodologies for allocating fire detection towers over large areas are numerous, complex and non-standardized by government supervisory agencies. Therefore, this study proposes and evaluates different methodologies to best location of points to install fire detection towers considering the topography, risk areas, conservation units and heat spots. Were used Geographic Information Systems (GIS) techniques and unaligned stratified systematic sampling for implementing and evaluating 9 methods for allocating fire detection towers. Among the methods evaluated, the C3 method was chosen, represented by 140 fire detection towers, with coverage of: a) 67% of the study area, b) 73.97% of the areas with high risk, c) 70.41% of the areas with very high risk, d) 70.42% of the conservation units and e) 84.95% of the heat spots in 2014. The proposed methodology can be adapted to areas of other countries.