Effect of Climate Change on Tropical Dry Forests

Around 1.6 billion people in the world are directly dependent on forests for food, fodder, fuel, shelter, and livelihood, out of which 60 million are entirely dependent on forests. Forests silently provide us with ecosystem services such as climate regulation, carbon sequestration, harbouring biodiversity, synchronizing nutrient cycling, and many more. Tropical Dry Forests (TDF's) occupy around 42% of total forest area of the tropics and subtropics and facilitate sustenance of world's marginalized populations. Change in vegetation composition and distribution, deflected succession, carbon sequestration potential, nutrient cycling and symbiotic associations would affect TDF at ecosystem level. At species level, climate change will impact photosynthesis, phenology, physiognomy, seed germination, and temperature-sensitive physiological processes. In order to mitigate the effects of climate change, specific mitigation and adaptation strategies are required for TDF that need to be designed with concerted efforts from scientists, policy makers and local stakeholders.

Effects of Forestry on Carbon Emissions in China: Evidence From a Dynamic Spatial Durbin Model

Research has proved the significance of forests in controlling carbon emissions, however, our research sheds light on the management of existing forests to combat climate change. To examine the role of forestation and forest investment activities, dynamic spatial techniques are used for 30 provinces of China. The results suggest that forest investment and management not only reduce carbon locally but also in neighboring provinces. Furthermore, the findings of the current study confirmed that forest investment is the most viable practice to control carbon emissions in China instead of just increasing total forest area. Reforms regarding the management of forests would be a good policy for both pollution reduction and employment generation.

Economic potential of adopting genomic technology in Alberta’s tree improvement sector

The adoption of genomic technology and the use of improved seeds are expected to improve timber productivity in Alberta. However, this improvement will need to take place within the confines of the public-private nature of the sector where 93% of the total forest area is publicly owned. The purpose of this study is to explore the extent to which a timber harvest policy known as the allowable cut effect can affect the welfare outcomes of adopting genomics-assisted tree breeding. Using the forest industry of Alberta as the empirical setting, the economic returns to the adoption of this new breeding technology in lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) and white spruce (Picea glauca (Moench) Voss) are calculated by estimating a timber supply model and a spatial equilibrium model. Under certain policy and technology improvement scenarios, the economic returns are negative, which would result in non-adoption of the technology. However, under other feasible conditions, the payoffs of genomics-assisted tree breeding research are large and positive. These results illustrate the important role that government policies can have on the returns to adopting new technologies.

Economic potential of adopting genomic technology in Alberta’s tree improvement sector

The adoption of genomic technology and the use of improved seeds are expected to improve timber productivity in Alberta. However, this improvement will need to take place within the confines of the public-private nature of the sector where 93% of the total forest area is publicly owned. The purpose of this study is to explore the extent to which a timber harvest policy known as the allowable cut effect can affect the welfare outcomes of adopting genomics-assisted tree breeding. Using the forest industry of Alberta as the empirical setting, the economic returns to the adoption of this new breeding technology in lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) and white spruce (Picea glauca (Moench) Voss) are calculated by estimating a timber supply model and a spatial equilibrium model. Under certain policy and technology improvement scenarios, the economic returns are negative, which would result in non-adoption of the technology. However, under other feasible conditions, the payoffs of genomics-assisted tree breeding research are large and positive. These results illustrate the important role that government policies can have on the returns to adopting new technologies.

Effects of Land-Related Policies on Deforestation in a Protected Area: The Case Study of Rema-Kalenga Wildlife Sanctuary, Bangladesh

In protected areas (PAs) in Bangladesh, as policies shift from net deforestation, conservation initiatives and various management plans have been implemented to reduce deforestation and include public participation at multiple levels. However, the interactive effect of land-related policies on deforestation in PAs is poorly understood. In this study, land-use change analysis using geographic information system data was performed to investigate how policies affected land use and land cover change in Rema-Kalenga Wildlife Sanctuary (RKWS), particularly the National Forest Policy (1979~), National Land Policy (2001~), and Agricultural Land Policy (1999~), using a series of Landsat images captured at different times. Our analyses showed that the total forest area increased in the 1994–2005 period when a plantation program was implemented, and also that many forest areas were replaced with noncommercial agricultural land areas in the 2005–2013 and 2013–2018 periods, when land zoning and co-management programs were implemented under different land-related policies. Commercial and non-commercial agricultural land expansions were the main drivers of deforestation, suggesting that several programs under the different land-related policies could have had synergetic effects on deforestation even in PAs. Our findings emphasize the importance of considering the undesirable effects of land-related policies in Pas, and the need to support the community for forest conservation.

Yield table for selected black locust (Robinia pseudoacacia L.) cultivars

In Hungary, the black locust (Robinia pseudoacacia L.) can be considered as the most important fast-growing, stand-forming introduced tree species. Due to its positive growing technological characteristics as well as wood utilization possibilities, at the present, black locust is the most widely planted tree species in Hungary, covering 25% of the country’s total forest area. One of the important tasks ahead of Hungarian black locust growers is to improve the quality of black locust stands with introducing selected cultivars. For the estimation of the growth rate and yield a numerical yield table has been constructed on the basis of surveys of the experimental plots established in pure,managed ’Nyirségi’ ,’Üllői’ and ’Jászkiséri’ black locust cultivars’ plantations which can be suitable for sawlogs production. In the course of 56 stand surveys the key stand characteristics were measured, and then, were reconsidered the average height, diameter (DBH), volume, basal area and stem number given separately for the main (remaining), secondary (removal) and total stands per hectare. The programmable editing procedure allows to extention and formal change of information content of the yield table according to different demands.

Recreational and health forests of Kremenets district, Ternopil region

The article presents the results of the research of recreational and health stands in Kremenets district of Ternopil region. The total area of these forests is 5868.2 hectares. Studies of the typological structure of the forests were carried out according to the methods of AlekseevPohrebniak Forest Typology of Forestry Ecological School. MapInfo Professional 12.0 and a vector map of Ukraine were used to construct a map-scheme of the research region. The typological variety of recreational and health-improving stands is represented from subors (В) to dubravas (D). Thus, dubravas are the largest share among them (72.9% of the total area covered with forest vegetation). The share of the area of sudubravas is 17.7% of the total area covered with forest vegetation; the rest is subors (9.4%). Forest managers have identified 14 types of forests on the territory of the research facility. Thus, there are only 2 types of forest in the subors, 8 types of forest in the sudubravas and 4 types of forests in the dubravas. The most common type of forest in Kremenets district is fresh hornbeam forest represented 71.6% of the total area covered with forest vegetation. The share of fresh hornbeam-oak-pine forest reaches 17.1%; a slightly smaller share is represented by fresh oak-pine subors — 9.4%. The forest species diversity is represented by 22 species of trees. Thus, among these tree species, the largest area is occupied by Common Oak (Quercus robur L.) — 40.6% of the total area covered with forest vegetation, and 29.1% — by Scots Pine (Pinus sylvestris L.). Stands of artificial origin (78.0% of the total area covered with forest vegetation) are dominant; the rest of stands have natural origin (22.0%). The age structure of stands is unbalanced. Middle-aged stands dominate (57.9% of the total area covered with forest vegetation). The share of maturing, young and matured forests ranges from 9.0 to 14.9% of the total forest area. In terms of relative completeness, stands with a density of 0.71–0.8 dominate which is 37.7% of the total area covered with forest vegetation. The share of stands with completeness of 0.61–0.7 (29.9%) and 0.81–0.9 (14.5%) is slightly smaller. The bonitete classes are dominated by stands of the I bonitete class — 51.3% of the total area covered with forest vegetation. Thus, the share of II, Ia and III bonitete classes varies from 7.1 to 23.3% of the total forest area

Mapping Forest And Agroforestry Units For Environmental Planning. Study Case Transboundary Region Mexico-Guatemala

The cross-border region of Mexico and Guatemala is part of the continuum in the aspects of relief, climate, hydrography, geology, land cover and land use of Mesoamerica, one of the most biologically diverse regions on the planet. Historically, the region has been continuously affected by meteorological phenomena, such as mass movement in the highland and floods in the lowland, which affected cities, communities and production activities year after year and led to the loss and deterioration of the ecosystems. To handle this problem, a proposal for environmental planning is suggested. The final objective is to provide key information that concerns the implementation of Sustainable Development Goals, particularly related to the protection and restoration of forest areas. In this study, spatial analysis and modeling were applied to map homogeneous units for environmental planning in the Mexico-Guatemala trans-border region. Additionally, forest area as a proportion of the total land area, its share inside the natural protected areas and distribution by ecosystem type were calculated for 2010 and 2019. From the data analysis it was found that the total forest area in the region has decreased from 47% in 2010 to 43 % in 2019; 27% and 25% of the total area, respectively, correspond to forests within the natural protected areas. The principal ecosystem type in the Natural Protected Areas corresponds to tropical forest. Two conclusions can be drawn, that agroforestry zoning is an important tool to monitor forest areas in the context of achieving Sustainable Development Goals and that the natural protected areas play a fundamental role in the preservation of the forest in the region.

Understanding the Spatially Explicit Distribution of Regional Tree Species Using Multi-Seasonal Sentinel-1&2 Imagery within Google Earth Engine

Background Accurate information on tree species is much in demand for forestry management and further investigations on biodiversity and forest ecosystem services. Over regional or large areas, discriminating tree species at high resolution is deemed challenging by lack of representative features and computational power. Methods A novel methodology to delineate the explicit spatial distribution of dominated six tree species (Pinus, Quercus, Betula, Populus, Larch, and Apricot) and one residual class using the analysis-ready large volume multi-sensor imagery within Google Earth Engine (GEE) platform is demonstrated and used to map a 10 m classification with detail analysis of spatial pattern for an area covering over 90,000 km 2 between 41° N and 45° N. Random Forest (RF) algorithm built into GEE was used for tree species mapping, together with the multi-temporal features extracted from Sentinel-1/2 and topographic imagery data. The composition of tree species in natural forests and plantations in city and county-level were performed in detail afterwards. Results The proposed model achieved a reliable overall agreement (77.5%, 0.71 kappa), and the detailed analysis on the spatial distributing of targeted species indicated that the plantations (Pinus, Populus, Larch, and Apricot) outnumber natural forests (Quercus and Betula) by 6%, and they were mainly grown in the northern and southern regions, respectively. Moreover, Arhorchin had the largest total forest area of over 4,500 km 2 , while Hexingten and Aohan ranked first in natural forest and plantation area, and the class proportion of the number of tree species in Karqin and Ningcheng was more balanced. Conclusions It is our belief that combined multi-source information of the machine learning algorithm within cloud platforms is beneficial to map a reliable spatial tree species over large areas on a fine scale. High-resolution tree species information based on online tools could be more easily considered for practical forestry management and further studies on forest ecosystems.

Mapping regional forest management units: a road-based framework in Southeastern Coastal Plain and Piedmont

Management practices are one of the most important factors affecting forest structure and function. Landowners in southern United States manage forests using appropriately sized areas, to meet management objectives that include economic return, sustainability, and esthetic enjoyment. Road networks spatially designate the socio-environmental elements for the forests, which represented and aggregated as forest management units. Road networks are widely used for managing forests by setting logging roads and firebreaks. We propose that common types of forest management are practiced in road-delineated units that can be determined by remote sensing satellite imagery coupled with crowd-sourced road network datasets. Satellite sensors do not always capture road-caused canopy openings, so it is difficult to delineate ecologically relevant units based only on satellite data. By integrating citizen-based road networks with the National Land Cover Database, we mapped road-delineated management units across the regional landscape and analyzed the size frequency distribution of management units. We found the road-delineated units smaller than 0.5 ha comprised 64% of the number of units, but only 0.98% of the total forest area. We also applied a statistical similarity test (Warren’s Index) to access the equivalency of road-delineated units with forest disturbances by simulating a serious of neutral landscapes. The outputs showed that the whole southeastern U.S. has the probability of road-delineated unit of 0.44 and production forests overlapped significantly with disturbance areas with an average probability of 0.50.