Promoting Bird Functional Diversity on Landscapes with a Matrix of Planted Eucalyptus spp. in the Atlantic Forest.

Promoting the diversity of biological communities in areas of agricultural production is a very current debate since protected areas may not be sufficient to ensure biodiversity conservation. Among the biological communities affected by the production areas are birds, which show rapid responses to changes in the landscape. Here we seek to understand how landscape planning, concerning its composition and configuration, in areas with a matrix of planted Eucalyptus spp. forests influences the functional diversity of bird assemblages in the Atlantic Forest. Our results show that the spatial distribution design of planted forests in terms of age, land cover and clone types have effects on bird diversity with regard to functional divergence, functional evenness and species richness. These results reinforce the importance of good management for the maintenance of bird diversity. We found that bird functional diversity in planted forest matrices increased with the proximity index, proportion of native vegetation and age importance value, and is negatively influenced by edge density and proportion of forest plantation. For bird conservation, it is thus better to associate Eucalyptus spp. with other cover types in the landscape. These results corroborate that, to increase bird functional diversity, it is possible to associate conservation and production in the same landscape. Mosaic landscapes have great potential to contribute to the conservation of bird biodiversity outside protected areas. However, decisions regarding the management of planted forests and planning of improved areas intended for conservation seem to be decisive to ensure the maintenance of bird biodiversity.

Enhancing multifunctionality in European boreal forests: The potential role of Triad landscape functional zoning.

Land-use policies aim at enhancing the sustainable use of natural resources. The Triad approach has been suggested to balance the social, ecological, and economic demands of forested landscapes. The core idea is to enhance multifunctionality at the landscape level by allocating landscape zones with specific management priorities, i.e., production (intensive management), multiple use (extensive management), and conservation (forest reserves). We tested the efficiency of the Triad approach and identified the respective proportion of above-mentioned zones needed to enhance multifunctionality in Finnish forest landscapes. Through a simulation and optimization framework, we explored a range of scenarios of the three zones and evaluated how changing their relative proportion (each ranging from 0 to 100%) impacted landscape multifunctionality, measured by various biodiversity and ecosystem service indicators. The results show that maximizing multifunctionality required around 20% forest area managed intensively, 50% extensively, and 30% allocated to forest reserves. In our case studies, such landscape zoning represented a good compromise between the studied multifunctionality components and maintained 61% of the maximum achievable net present value (i.e., total timber economic value). Allocating specific proportion of the landscape to a management zone had distinctive effects on the optimized economic or multifunctionality values. Net present value was only moderately impacted by shifting from intensive to extensive management, while multifunctionality benefited from less intensive and more diverse management regimes. This is the first study to apply Triad in a European boreal forest landscape, highlighting the usefulness of this approach. Our results show the potential of the Triad approach in promoting forest multifunctionality, as well as a strong trade-off between net present value and multifunctionality. We conclude that simply applying the Triad approach does not implicitly contribute to an overall increase in forest multifunctionality, as careful forest management planning still requires clear landscape objectives.

Seasonal Forest Changes of Color and Temperature: Effects on the Mood and Physiological State of University Students.

In this study, we attempted to analyze the effect of color and temperature changes in the forest environment over time on the mood and physiological state of university students. The survey was conducted four times considering forest changes such as new leaf appearance and growth, autumn leaf changes, and fallen leaves. The participants' moods and physiological states were first evaluated in an indoor environment; a second evaluation was conducted after contact with the forest. The color visual information of the forest environment was analyzed through color extraction from photographs taken each survey day. The participants' moods and physiological states were measured using the Korean Profile of Mood States-Brief and a heart rate variability measuring device, respectively. Changes in the forest experience according to the season had an effect on university students' mood states. In particular, the effects of the spring forest experience included the relaxation of tension and the activation of vigor. This result is considered to be influenced by factors such as the season's temperature and the green color, which is predominant in the spring forest. However, no physiological changes were found in the participants according to each season. The results of this study can lead to greater consideration of the role of color in urban forest planning for universities and other public spaces.

Evaluation of mushroom production potential by combining spatial optimization and LiDAR-based forest mapping data.

High-resolution forest mapping technology is a powerful data source to assess the production capacity of forests regarding wood and non-wood ecosystem services. The study shows how to evaluate the potential benefits from forest management treatments devoted to increase mushroom supply. The study was developed in Central Spain, over a forest with important cultural and economic values attached to mushrooms. Airborne laser scanning (ALS), mushroom production models and mathematical programming as spatial optimization method are used to sequence, spatially and temporally, silviculture-oriented actions to enlarge mushroom provisioning. We present a tactical forest planning solution to incentivize mushroom yield driven by clustered silvicultural treatments applied to fine-grained segments derived from ALS data, and along a 5-year plan while embedding temporal and spatial dependencies. Mushroom yield can increase up to 18 % from current conditions if all area is treated. Our model integrates constraints to optimize the selection of segments yielding the highest benefits in terms of mushroom yield and timber removals during the treatments. The temporal sequencing was successful, so the annual interventions are scheduled aligned in space and in time to ease the actionability and realism of model outputs. The assessment of production potential is an informative, spatially and temporally explicit exercise to inform decision-makers on investment opportunities to enhance the supply of non-wood ecosystem services, tested with mushroom in this study but extendable to more non-wood ecosystem services.

Allocation of water reservoirs to fight forest fires according to the risk of occurrence.

Although forest fires are indispensable for some ecosystems, they can have profound economic, environmental, and social implications, especially when they reach high intensities. There are two crucial factors in fighting forest fires: the availability of water resources and the service network. The objective of this study was to propose an alternative methodology for allocating water reservoirs to fight forest fires. The research was divided into three stages: zoning of fire risk, delimitation of viable areas for the implementation of water reservoirs, and determining strategic locations for reservoir allocation. The variables analyzed were land use and occupation, provision of watercourses, relief orientation, slope, proximity to roads, temperature, and precipitation. Fuzzy logic, Euclidean distance, and network analysis were used as the modeling techniques. Scenarios with all risk classes and only the high- and very high-risk classes were analyzed. A total of 66% of the area was represented by the low- and moderate-risk fire classes and 53.16% had a low potential for reservoir allocation, influenced by the low availability of water resources in the area. The proposed model efficiently allocated the water collection points in the different scenarios, and allowed the determination of the areas most susceptible to the occurrence of forest fires and the optimal locations for the installation of reservoirs, with the allocation of 21 water reservoirs to attend the areas of high- and very high-risk of occurrence of fires at a safe speed (40 km h-1) and 47 reservoirs to meet all risk classes at the same speed. The proposed methodology is feasible, applicable, and adjustable and can be implemented in other conservation units and areas of economic interest.

Habitat amount and connectivity in forest planning models: Consequences for profitability and compensation schemes.

Adjacency relationships are pervasive in forest planning problems, especially the ones related to the selection of habitat networks for biodiversity conservation. Two main approaches are applied in the planning of these conservation actions: i) selection grounded on the island biogeography theory, where connected habitats are preferred and ii) selection grounded in the habitat amount hypothesis, where the amount of habitat is enforced in local landscapes, regardless of their spatial distribution. Because the presence of connectivity requirements in the creation of habitat networks impose more stringent limitations on the search for optimal solutions, they are expected to cascade to the total benefit from harvesting revenues and, consequently, to the costs of the habitat networks. The ecological implications of these approaches have been investigated, whereas the economic consequences of imposing connectivity remain unclear. Here, I address this issue and investigate the costs of selecting habitat networks in multiple forest landscapes in central Europe, applying these two approaches. To this end, a conic optimization model is proposed, to find minimum cost allocations of forest reserves. Furthermore, a sensitivity analysis on the optimal allocation is conducted, regarding the size of the habitat network required and the level of heterogeneity in forest profitability within the landscapes. The results show that habitat networks amounting to 10% of the forest area may be created with up to 5.5% reduction in the total Net Present Value (NPV), with a higher cost when connectivity is imposed (6.5%). The cost of connectivity, however, may increase in landscapes with high heterogeneity in forest profitability and with the minimum amount of habitat required. In conclusion, habitat selection must be tailored to local conditions and weight the additional costs of imposing connectivity against the requirements of the target species and the expected ecological benefits.

Trade-offs between carbon stocks and biodiversity in European temperate forests.

Policies to mitigate climate change and biodiversity loss often assume that protecting carbon-rich forests provides co-benefits in terms of biodiversity, due to the spatial congruence of carbon stocks and biodiversity at biogeographic scales. However, it remains unclear whether this holds at the scales relevant for management, and particularly large knowledge gaps exist for temperate forests and for taxa other than trees. We built a comprehensive dataset of Central European temperate forest structure and multi-taxonomic diversity (beetles, birds, bryophytes, fungi, lichens, and plants) across 352 plots. We used Boosted Regression Trees (BRTs) to assess the relationship between above-ground live carbon stocks and (a) taxon-specific richness, (b) a unified multidiversity index. We used Threshold Indicator Taxa ANalysis to explore individual species' responses to changing above-ground carbon stocks and to detect change-points in species composition along the carbon-stock gradient. Our results reveal an overall weak and highly variable relationship between richness and carbon stock at the stand scale, both for individual taxonomic groups and for multidiversity. Similarly, the proportion of win-win and trade-off species (i.e., species favored or disadvantaged by increasing carbon stock, respectively) varied substantially across taxa. Win-win species gradually replaced trade-off species with increasing carbon, without clear thresholds along the above-ground carbon gradient, suggesting that community-level surrogates (e.g., richness) might fail to detect critical changes in biodiversity. Collectively, our analyses highlight that leveraging co-benefits between carbon and biodiversity in temperate forest may require stand-scale management that prioritizes either biodiversity or carbon in order to maximize co-benefits at broader scales. Importantly, this contrasts with tropical forests, where climate and biodiversity objectives can be integrated at the stand scale, thus highlighting the need for context-specificity when managing for multiple objectives. Accounting for critical change-points of target taxa can help to deal with this specificity, by defining a safe operating space to manipulate carbon while avoiding biodiversity losses.

Optimal selective logging regime and log landing location models: a case study in the Amazon forest / Regime de corte seletivo ótimo em modelos de locação de pátios de estocagem de madeira: um estudo de caso na floresta amazônica

ABSTRACT Reduced-impact logging is a well known practice applied in most sustainable forest management plans in the Amazon. Nevertheless, there are still ways to improve the operational planning process. Therefore, the aim of this study was to create an integer linear programming (ILP) to fill in the knowledge gaps in the decision support system of reduced impact logging explorations. The minimization of harvest tree distance to wood log landing was assessed. Forest structure aspects, income and wood production were set in the model, as well as the adjacency constraints. Data are from a dense ombrophylous forest in the western Brazilian Amazon. We applied the phytosociological analysis and BDq method to define the selective logging criteria. Then, ILP models were formulated to allow the application of the constraints. Finally, 32 scenarios (unbalanced forest, UF, and balanced forest, BF) were generated and compared with real executed plans (RE). Robust results were achieved and the expected finding of each scenario was met. The feasibility to integrate ILP models in uneven-aged forest management projects was endorsed. Consequently, the UF and BF scenarios tested were efficient and concise, introducing new advances for forest management plans in the Amazon. The proposed models have a high potential to improve the selective logging activities in the Amazon forest.

RESUMO A exploração de impacto reduzido é uma prática bem conhecida e aplicada na maioria dos planos de manejo florestal sustentável na Amazônia. Todavia, ainda há a possibilidade de melhoria do processo de planejamento da operação. Diante da falta de métodos auxiliares à tomada de decisão, o objetivo do trabalho foi desenvolver modelos de programação linear inteira (PLI) para suprir esta demanda. Considerou-se a minimização da distância entre as árvores exploradas e os pátios de estocagem de madeira. Aspectos estruturais, econômicos e produtivos foram incorporados ao modelo, bem como restrições de adjacência. Os dados derivam de uma floresta ombrófila densa na Amazônia Ocidental. Previamente, utilizou-se uma análise fitossociológica e o método BDq como critério de remoção. Posteriormente, modelos de PLI foram formulados para exemplificar as aplicações. Finalmente, 32 cenários (para floresta desbalaceada, UF, e floresta balanceada, BF) foram gerados e comparados com o plano executado no campo (RE). Resultados robustos foram obtidos e atenderam às expectativas de cada cenário. A viabilidade da integração dos modelos de PLI em projetos de manejo de florestas ineqüiâneas foi testado. Os cenários UF e BF testados foram eficientes e concisos, confirmando seu potencial para aumentar a eficiência de planos de exploração madeireira e manejo florestal na Amazônia.

Use of interactive data visualization in multi-objective forest planning.

Common to multi-objective forest planning situations is that they all require comparisons, searches and evaluation among decision alternatives. Through these actions, the decision maker can learn from the information presented and thus make well-justified decisions. Interactive data visualization is an evolving approach that supports learning and decision making in multidimensional decision problems and planning processes. Data visualization contributes the formation of mental image data and this process is further boosted by allowing interaction with the data. In this study, we introduce a multi-objective forest planning decision problem framework and the corresponding characteristics of data. We utilize the framework with example planning data to illustrate and evaluate the potential of 14 interactive data visualization techniques to support multi-objective forest planning decisions. Furthermore, broader utilization possibilities of these techniques to incorporate the provisioning of ecosystem services into forest management and planning are discussed.

Forest fire spatial pattern analysis in Galicia (NW Spain).

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years.