Forests, Volume 5, Issue 7 (July 2014) – 15 articles , Pages 1508-1814

The aim of this study was to test the potential of a constellation of remote sensing satellites, the Disaster Monitoring Constellation (DMC), for retrieving a temporal record of forest leaf area index (LAI) in the United Kingdom (U.K.). Ground-based LAI measurements were made over a 12-month period in broadleaf woodland at Risley Moss Nature Reserve, Lancashire, U.K. The ground-based LAI varied between zero in January to a maximum of 4.5 in July. Nine DMC images, combining data from UK-DMC and NigeriaSat-1, were acquired, and all images were cross-calibrated and atmospherically corrected. The spectral reflectance of the test site was extracted, and a range of vegetation indices were then computed and correlated with the ground measurements of LAI. The soil adjusted vegetation index (SAVI) had the strongest correlation, and this was used to derive independent estimates of LAI using the “leave-one-out” method. The root mean square error of the LAI estimates was 0.47, which was close to that calculated for the ground-measured LAI. This study shows, for the first time, that data from a constellation of high temporal, medium spatial resolution optical satellite sensors may be used to map seasonal variation in woodland canopy leaf area index (LAI) in cloud-prone areas, like the U.K. Full article

We present an in-depth analysis of natural forest management practices in Costa Rica based on a new historical forestry GIS database encompassing five conservation regions in the country where selective logging has been prevalent for the last 18 years. Natural forest management refers to the selective logging practices for the production of timber in natural forest ecosystems. The study considers natural forest management plans developed following a standardized format, based on Forestry Law 7575, established in 1996. Our results show a positive aspect of forest management where a large percentage of the managed forest is still standing, contrary to other tropical countries where selective logging promotes land use change. The negative finding is that managed forest areas occur in the last remaining forest fragments outside of protected areas, which challenges the continuity of selective logging in the near and mid future due to the potential impoverishment of the isolated forest stands. The most negative aspect is the recent establishment, by law, of a very short return logging cycle (10–15 years—minimum cutting cycle) as it contradicts ecological studies showing that tropical forests require over 60 years for the forest structure and composition to return to a state similar to pre-logging states. Our results should inform decision makers and managers in conservation areas to review current policies and establish new benchmarks for sustainable forest management in the country. Full article

Growing stock volume is an important biophysical parameter describing the state and dynamics of the Boreal zone. Validation of growing stock volume (GSV) maps based on satellite remote sensing is challenging due to the lack of consistent ground reference data. The monitoring and assessment of the remote Russian forest resources of Siberia can only be done by integrating remote sensing techniques and interdisciplinary collaboration. In this paper, we assess the information content of GSV estimates in Central Siberian forests obtained at 25 m from ALOS-PALSAR and 1 km from ENVISAT-ASAR backscatter data. The estimates have been cross-compared with respect to forest inventory data showing 34% relative RMSE for the ASAR-based GSV retrievals and 39.4% for the PALSAR-based estimates of GSV. Fragmentation analyses using a MODIS-based land cover dataset revealed an increase of retrieval error with increasing fragmentation of the landscape. Cross-comparisons of multiple SAR-based GSV estimates helped to detect inconsistencies in the forest inventory data and can support an update of outdated forest inventory stands. Full article

Despite the growing ecological and social importance of second-growth and regenerating forests across much of the world, significant inconsistencies remain in the legal framework governing these forests in many tropical countries and elsewhere. Such inconsistencies and uncertainties undermine attempts to improve both the transparency and sustainability of management regimes. Here, we present a case-study overview of some of the main challenges facing the governance of second-growth forests and the forest restoration process in the Brazilian Amazon, with a focus on the state of Pará, which is both the most populous state in the Amazon and the state with the highest rates of deforestation in recent years. First, we briefly review the history of environmental governance in Brazil that has led to the current system of legislation governing second-growth forests and the forest restoration process in Pará. Next, we draw on this review to examine the kinds of legislative and operational impediments that stand in the way of the development and implementation of a more effective governance system. In particular, we highlight problems created by significant ambiguities in legal terminology and inconsistencies in guidance given across different levels of government. We also outline some persistent problems with the implementation of legal guidance, including the need to understand local biophysical factors in order to guide an effective restoration program, as well as difficulties presented by access to technical assistance, institutional support and financial resources for the establishment and monitoring of both existing secondary forests and newly regenerating areas of forest. Whilst we focus here on a Brazilian case study, we suggest that these kinds of impediments to the good governance of second-growth forests are commonplace and require more concerted attention from researchers, managers and policy makers. Full article

Douglas-fir is the most commercially important timber species in the US Pacific Northwest due to its ecological prevalence and its superior wood attributes, especially strength and stiffness properties that make it highly prized for structural applications. Its economic significance has led to extensive establishment and management of plantations over the last few decades. Cultural treatments and genetic improvement designed to increase production of utilizable wood volume also impact tree morphology and wood properties. Many of these impacts are mediated by crown development, particularly the amount and distribution of foliage and size and geometry of branches. Natural selection for branch architecture that optimizes reproductive fitness may not necessarily be optimal for stem volume growth rate or for wood properties controlling the quality of manufactured solid wood products. Furthermore, Douglas-fir does not self-prune within the rotation lengths currently practiced. This paper synthesizes extensive Douglas-fir research in the Pacific Northwest addressing: (1) the effects of silviculture and genetics on branch structure and associated consequences for wood quality and the product value chain; and (2) methods to measure, monitor, modify, and model branch attributes to assist managers in selecting appropriate silvicultural techniques to achieve wood quality objectives and improve the value of their Douglas-fir resource. Full article

Half of the productive forest area in Sweden is owned by small-scale private forest owners. However, there is a lack of comprehensive information that would allow categorizing small-scale private forest owners according to their management strategy. In this study, we surveyed small-scale private forest owners in Sweden to determine the proportions who applied various management strategies. We analyzed the results using chi-square tests to identify the most relevant factors affecting the management strategy choices of individual forest owners. We found that “soft” factors, such as the importance of income from the forest, membership in a forest owners’ association, certification and an interest in and knowledge of forestry issues, had a stronger impact on the choice of management strategy than most “hard” factors related to the owner or the property, such as gender and distance between the owner’s residence and the property. However, property size was the most important factor and was associated with the importance of income derived from the forest and several other soft factors. Full article

During the past decade in forest mapping and monitoring applications, the ability to acquire spatially accurate, 3D remote-sensing information by means of laser scanning, digital stereo imagery and radar imagery has been a major turning point. These 3D data sets that use single- or multi-temporal point clouds enable a wide range of applications when combined with other geoinformation and logging machine-measured data. New technologies enable precision forestry, which can be defined as a method to accurately determine characteristics of forests and treatments at stand, sub-stand or individual tree level. In precision forestry, even individual tree-level assessments can be used for simulation and optimization models of the forest management decision support system. At the moment, the forest industry in Finland is looking forward to next generation’s forest inventory techniques to improve the current wood procurement practices. Our vision is that in the future, the data solution for detailed forest management and wood procurement will be to use multi-source and -sensor information. In this communication, we review our recent findings and describe our future vision in precision forestry research in Finland. Full article

The difficulty of defining and quantifying forest degradation is a major constraint in the implementation of the international mitigation mechanism Reduced Emissions from Deforestation and Forest Degradation (REDD+). Our aim is to develop an operational framework for defining and quantifying forest degradation at a local level for early REDD+ projects and for national REDD+ programmes, through a ground level approach. We critically review and discuss national and international definitions of forest and of forest degradation, and then analyze the main difficulties in making these operational, evaluating the key elements and threshold values that are used, and contextualizing them using Mexico as a case study. We conclude that, given the lack of historical biomass data and the limited capability for monitoring degradation using remote sensing, forest degradation is best measured against a local benchmark that represents areas of low or no degradation that have comparable biophysical characteristics. Use of benchmarks of this type could offer a quick-start option for local assessment and construction of reference levels for forest degradation. These could be refined as more data become available and could eventually be integrated into national monitoring systems. Full article

Among the machine learning tools being used in recent years for environmental applications such as forestry, self-organizing maps (SOM) and the k-nearest neighbor (kNN) algorithm have been used successfully. We applied both methods for the mapping of organic carbon (C_org) in riparian forests due to their considerably high carbon storage capacity. Despite the importance of floodplains for carbon sequestration, a sufficient scientific foundation for creating large-scale maps showing the spatial C_org distribution is still missing. We estimated organic carbon in a test site in the Danube Floodplain based on RapidEye remote sensing data and additional geodata. Accordingly, carbon distribution maps of vegetation, soil, and total C_org stocks were derived. Results were compared and statistically evaluated with terrestrial survey data for outcomes with pure remote sensing data and for the combination with additional geodata using bias and the Root Mean Square Error (RMSE). Results show that SOM and kNN approaches enable us to reproduce spatial patterns of riparian forest C_org stocks. While vegetation C_org has very high RMSEs, outcomes for soil and total C_org stocks are less biased with a lower RMSE, especially when remote sensing and additional geodata are conjointly applied. SOMs show similar percentages of RMSE to kNN estimations. Full article

Forest health is a complex concept including many ecosystem functions, interactions and values. We develop a quantitative system applicable to many forest types to assess tree mortality with respect to stable forest structure and composition. We quantify impacts of observed tree mortality on structure by comparison to baseline mortality, and then develop a system that distinguishes between structurally stable and unstable forests. An empirical multivariate index of structural sustainability and a threshold value (70.6) derived from 22 nontropical tree species’ datasets differentiated structurally sustainable from unsustainable diameter distributions. Twelve of 22 species populations were sustainable with a mean score of 33.2 (median = 27.6). Ten species populations were unsustainable with a mean score of 142.6 (median = 130.1). Among them, Fagus grandifolia, Pinus lambertiana, P. ponderosa, and Nothofagus solandri were attributable to known disturbances; whereas the unsustainability of Abies balsamea, Acer rubrum, Calocedrus decurrens, Picea engelmannii, P. rubens, and Prunus serotina populations were not. This approach provides the ecological framework for rational management decisions using routine inventory data to objectively: determine scope and direction of change in structure and composition, assess excessive or insufficient mortality, compare disturbance impacts in time and space, and prioritize management needs and allocation of scarce resources. Full article

Monitoring is a central element in the implementation of national REDD+ and may be essential in providing the data needed to support benefit distribution. We discuss the options for benefit sharing systems in terms of technical feasibility and political acceptability in respect of equity considerations, and the kind of data that would be needed for the different options. We contrast output-based distribution systems, in which rewards are distributed according to performance measured in terms of carbon impacts, with input-based systems in which performance is measured in term of compliance with prescribed REDD+ activities. Output-based systems, which would require regular community carbon inventories to produce Tier 3 data locally, face various challenges particularly for the case of assessing avoided deforestation, and they may not be perceived as equitable. Input-based systems would require data on activities undertaken rather than change in stocks; this information could come from community-acquired data. We also consider how community monitored data could support national forest monitoring systems and the further development of national REDD+. Full article

Methods for woody plant herbicide screening were assayed with the goal of reducing resources and time required to conduct preliminary screenings for new products. Rapid screening methods tested included greenhouse seedling screening, germinal screening, and seed screening. Triclopyr and eight experimental herbicides from Dow AgroSciences (DAS 313, 402, 534, 548, 602, 729, 779, and 896) were tested on black locust, loblolly pine, red maple, sweetgum, and water oak. Screening results detected differences in herbicide and species in all experiments in much less time (days to weeks) than traditional field screenings and consumed significantly less resources (<500 mg acid equivalent per herbicide per screening). Using regression analysis, various rapid screening methods were linked into a system capable of rapidly and inexpensively assessing herbicide efficacy and spectrum of activity. Implementation of such a system could streamline early-stage herbicide development leading to field trials, potentially freeing resources for use in development of beneficial new herbicide products. Full article

Terrestrial laser scanning (TLS) data makes possible to directly characterize the three-dimensional (3D) distribution of canopy foliage elements. The scanned edges of these elements may result in incorrectly point measurements (i.e., “ghost points”) impacting the quality of point cloud data. Therefore, estimation of the ghost points’ spatial visibilities, measurement of their characteristics and their removal are essential. In order to quantify the improvements on data quality, a method is developed in this study to efficiently correct for ghost points. Since the occurrence of ghost points is governed by a number of factors, (e.g., scanning resolution and distance, object properties, incident angle); the developed method is based on the analysis of the effects of these factors under controlled conditions where canopy-like objects (i.e., leaves, branches and layers of leaves) were scanned using a continuous-wave TLS system that employs phase-shift technology. Manual extraction of ghost points was done in order to calculate the relative amount of ghost points per scan, or ghost points ratio (gpr). The gpr values were computed in order to: (i) analyze their relationships with variables representing the above factors; and (ii) be used as a reference to evaluate the performance of filters used for extraction of ghost points. The ghost points’ occurrence was modeled by fitting regression models using different predictor variables that represent the variables under study. The obtained results indicated that reduced models with three predictors were suitable for gpr estimation in artificial leaves and in artificial branches, with a relative root mean squared error (RMSE) of 4.7% and 3.7%, respectively; while the full model with four predictors was appropriate for artificial layers of leaves, with relative RMSE of 4.5%. According to the statistical analysis, scanning distance was identified as the most important variable for modeling ghost points occurrence. Results indicated that optimized distance-based filters relative to the scanning distance have improved the outcomes in ghost points detection, in comparison to standard filtering criteria. These results suggest that more accurate characterization of forest canopy 3D structures can be achieved by removing ghost points using the new developed method. Full article

We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratios estimates were developed based on (1) proportion of times the independent variables had statistical significance and (2) proportion of times independent variables met the original study authors’ expectations. In F2D models, we confirmed the success of popular independent variables such as population, income, and urban proximity estimates but found timber rents and site productivity variables less successful. In F2A models, we confirmed success of popular explanatory variables such as forest and agricultural rents and costs, governmental programs, and site quality, but we found population, income, and urban proximity estimates less successful. In U2D models, successful independent variables found were urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. In F2NF models, we found poor success using timber rents but high success using agricultural rents, site quality, population, and income. Success ratios and discussion of new or less popular, but promising, variables was also included. This meta-analysis provided insight into the general success of econometric independent variables for future forest-use or -cover change research. Full article

Small-scale farmers in the Brazilian Amazon collectively hold tenure over more than 12 million ha of permanent forest reserves, as required by the Forest Code. The trade-off between forest conservation and other land uses entails opportunity costs for them and for the country, which have not been sufficiently studied. We assessed the potential income generated by multiple use forest management for farmers and compared it to the income potentially derived from six other agricultural land uses. Income from the forest was from (i) logging, carried out by a logging company in partnership with farmers’ associations; and (ii) harvesting the seeds of Carapa guianensis (local name andiroba) for the production of oil. We then compared the income generated by multiple-use forest management with the income from different types of agrarian systems. According to our calculations in this study, the mean annual economic benefits from multiple forest use are the same as the least productive agrarian system, but only 25% of the annual income generated by the most productive system. Although the income generated by logging may be considered low when calculated on an annual basis and compared to incomes generated by agriculture, the one-time payment after logging is significant (US$5,800 to US$33,508) and could be used to implement more intensive and productive cropping systems such as planting black pepper. The income from forest management could also be used to establish permanent fields in deforested areas for highly productive annual crops using conservation agriculture techniques. These techniques are alternatives to the traditional land use based on periodic clearing of the forest. Nevertheless, the shift in current practices towards adoption of more sustainable conservation agriculture techniques will also require the technical and legal support of the State to help small farmers apply these alternatives, which aim to integrate forest management in sustainable agricultural production systems. Full article