Improving the estimate of forest biomass carbon storage by combining two forest inventory systems

Quantifying forest carbon storage and its spatial distribution at regional scales is critical for the creation of greenhouse gases inventories, the evaluation of forest services and carbon-oriented forest management. The plot-based forest inventory (PBFI) and stand-based forest inventory (SBFI) collect extensive information on trees and stands respectively, and together, provide an opportunity to improve the regional estimates of forest carbon. In this study, we applied the SBFI to overcome the spatial extent limits of the PBFI in neighboring plots and improve the regional carbon estimation. We found that the forests in Sichuan Province reserved a total of 624.2?Tg?C in biomass and featured a large spatial heterogeneity, with high values in natural forests and low values in plantations. We found that the solo use of PBFI derived a slightly higher (46.63?Mg?C/ha) estimation on average compared with the integrated method (43.6?Mg?C/ha). However, when considering the spatial distribution, the PBFI generated an overestimation of young forests located between 3000and 4000?m in elevation, and an underestimation in mature forests. The spatially explicit biomass carbon estimation could be helpful in guiding regional forest management and biodiversity conservation.     

Community and ecotourist perceptions of forest conservation benefits:a case study of Mabira Central Forest Reserve,Uganda

The different interests in forest resources by various stakeholders may result in differences in perceived value of forest conservation. In order to test this hypothesis, we compared the valuation by international ecotourists and local respondents of the perceived benefits of the Mabira Central Forest Reserve. The factors that influenced respondents’ valuation of forest conservation were also investigated. Describing a hypothetical scenario to elicit respondents’ willingness-to-pay (WTP) for forest conservation was the central part of the questionnaire. The WTP;income ratio was used to estimate respondents’ perceived value of forest conservation. A chi-square (χ ²) test indicated significant association between respondent category (local and tourist) and categories of perceived benefits (p-value = 0.001). The locals were more interested in direct-use values while the tourists showed greater interest in the indirect-use values. A Student's t-test showed that the WTP:income ratios of the locals were much higher than for the ecotourists (p-value < 0.001). This implies that the local communities had a higher valuation of forest conservation than the ecotourists. Regression analysis revealed that all other factors being constant, the WTP of respondents who perceived direct- and indirect-use value as the most important forest benefit was significantly higher (p < 0.05) than those who perceived no value by $5.8693 and $0.02628, respectively. The respondents who rated the contribution of the ecotourism project to community development as moderate had a significantly higher WTP compared to those who rated it as low by $6.6908. Overall, these results indicate that the benefits people derive from the forest either through direct or indirect uses influence valuation of forest conservation. Results also indicate that although ecotourismrelated benefits improved attitudes towards forest conservation, ecotourism alone may not be an adequate conservation tool because of the limited support it can provide to the local community.     

Spatially explicit demand for afforestation

Afforestation is a stated goal in European Union policy and several member states have already implemented schemes to extend forest cover. However, little is known about the magnitude of non-market benefits of afforestation and how these benefits spatially differ. In this article, we propose a novel method to spatially explicitly predict marginal willingness to pay for afforestation. The approach is illustrated with data from a discrete choice experiment on local land use changes in Germany. GIS data on the respondent's place of residence allows inferring their current endowment with forest, which enters the utility specification of each respondent's status quo alternative. Marginal willingness to pay estimates therefore represent the value of changes in local forest cover relative to the observed status quo. This relationship can be utilized to predict willingness to pay at the county level. We find that marginal willingness to pay decreases as the current endowment with forest increases. The estimated optimal share of forest based on the average respondent's preferences is between 50 and 60%. The associated county level predictions of marginal and total willingness to pay can be used to inform national, regional and local policies that aim to increase forest cover.     

Spatial interpolation of in situ data by self-organizing map algorithms (neural networks) for the assessment of carbon stocks in European forests

Self-organizing maps (SOMs) are an advanced neural networks application. SOMs were applied for the spatially explicit estimation of forest carbon stocks for a test region in Thuringia (Germany). The approach utilizes in situ national forest inventory data and satellite remote sensing data (Landsat 7 ETM+) and provides maps showing a high-resolution spatial distribution of forest carbon stocks. The generated maps are compared to alternative estimates obtained by the k-nearest neighbour (kNN) method—a remote sensing based carbon assessment. Beside maps the SOM- and kNN-approaches were utilized to calculate statistical estimates of carbon stock and growing stock. The statistical estimates were validated by calculating bias and mean square errors with reference to in situ assessments.     

Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This paper has two purposes. First, it aims to provide a critical review of MCDA methods applied to forest and other natural resource management. The review seeks to layout the nature of the models, their inherent strengths and limitations. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. The review goes beyond traditional MCDA techniques; it describes new modelling approaches to forest management. The second purpose is to describe new MCDA paradigms aimed at addressing the inherent complexity of managing forest ecosystems, particularly with respect to multiple criteria, multi-stakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking about MCDA as they are applied to forest and natural resource management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis—from methods for problem solving to methods for problem structuring.     

Modelling and mapping the suitability of European forest formations at 1-km resolution

Proactive forest conservation planning requires spatially accurate information about the potential distribution of tree species. The most cost-efficient way to obtain this information is habitat suitability modelling i.e. predicting the potential distribution of biota as a function of environmental factors. Here, we used the bootstrap-aggregating machine-learning ensemble classifier Random Forest (RF) to derive a 1-km resolution European forest formation suitability map. The statistical model use as inputs more than 6,000 field data forest inventory plots and a large set of environmental variables. The field data plots were classified into different forest formations using the forest category classification scheme of the European Environmental Agency. The ten most dominant forest categories excluding plantations were chosen for the analysis. Model results have an overall accuracy of 76%. Between categories scores were unbalanced and Mesophitic deciduous forests were found to be the least correctly classified forest category. The model’s variable ranking scores are used to discuss relationship between forest category/environmental factors and to gain insight into the model’s limits and strengths for map applicability. The European forest suitability map is now available for further applications in forest conservation and climate change issues.     

An approach to GIS-based multiple criteria decision analysis that integrates exploration and evaluation phases: Case study in a forest-dominated landscape

The increasing importance and complexity of land and natural resource management are creating a need for ecosystem-based management (EBM). Multiple criteria decision analysis (MCDA) combined with geographic information systems (GIS) can integrate factors related to the triple bottom line of ecological, economic, and social perspectives required by EBM. However, GIS-based MCDA is limited in this role because (i) it rarely integrates or encourages an exploration phase in preparation for structured evaluation and (ii) inexperienced users may find MCDA methods and GIS software difficult to use. This paper presents a novel approach for (i) supporting an exploration phase to help structure a problem and (ii) integrating the exploration and evaluation phases in an easy-to-use software system. The approach was validated through a land-management case study in a forest-dominated landscape with a variety of stakeholders. Case-study participants used the approach to rate areas within a timber harvest plan based on their potential for conflict with conservation values. The case-study decision analysis determined that between 1.3% and 6.6% of the harvest plan area had a conservation rating of 0.30 or higher on a scale of 0–1. The system was made available to the forest industry and other stakeholders to support harvest plan adjustments, demonstrating how such tools can be used to improve and integrate our knowledge of forest ecology and management. Assessment of participant feedback reveals that an exploration phase is effective in helping understand a problem and prepare for multiple criteria evaluation (MCE).     

Estimating carbon stock in secondary forests: Decisions and uncertainties associated with allometric biomass models

Secondary forests are a major terrestrial carbon sink and reliable estimates of their carbon stocks are pivotal for understanding the global carbon balance and initiatives to mitigate CO₂ emissions through forest management and reforestation. A common method to quantify carbon stocks in forests is the use of allometric regression models to convert forest inventory data to estimates of aboveground biomass (AGB). The use of allometric models implies decisions on the selection of extant models or the development of a local model, the predictor variables included in the selected model, and the number of trees and species for destructive biomass measurements. We assess uncertainties associated with these decisions using data from 94 secondary forest plots in central Panama and 244 harvested trees belonging to 26 locally abundant species. AGB estimates from species-specific models were used to assess relative errors of estimates from multispecies models. To reduce uncertainty in the estimation of plot AGB, including wood specific gravity (WSG) in the model was more important than the number of trees used for model fitting. However, decreasing the number of trees increased uncertainty of landscape-level AGB estimates substantially, while including WSG had limited effects on the accuracy of the landscape-level estimates. Predictions of stand and landscape AGB varied strongly among models, making model choice an important source of uncertainty. Local models provided more accurate AGB estimates than foreign models, but high variability in carbon stocks across the landscape implies that developing local models is only justified when landscape sampling is sufficiently intensive.     

Mapping tree aboveground biomass and carbon in Omo Forest Reserve Nigeria using Landsat 8 OLI data

Protected areas in Nigeria are important ecosystems for carbon storage. The aim of this study was to estimate and map tree aboveground biomass (TAGB) and carbon (TAGC) within a tropical forest in Nigeria. Stepwise regression analysis was implemented to develop models for predicting TAGB in the forest stand, by integrating field TAGB data with Landsat 8 OLI data. Spectral variables used in the analysis include spectral bands, vegetation indices, tasseled cap indices and principal components. Model validation was performed using independent sample plots. The results showed that incorporating more than one category of spectral variables improved the prediction of TAGB. The best-fit model was applied to map the spatial distribution of TAGB and TAGC. The TAGC was estimated as 52.3% of TAGB, based on the average carbon content of tree species derived in this study. Average TAGB and TAGC estimates for the forest stand were 373.1 ± 165.4 t ha^?1 and 194 ± 82.7 t ha^?1, respectively. Reliable estimates of TAGB and TAGC for the forest reserve were obtained. This study provides important information required to manage the forest stand for optimal carbon sequestration.     

Spatially explicit assessment of carbon stocks of a managed forest area in eastern Germany

The Kyoto-protocol permits the accounting of changes in forest carbon stocks due to forestry. Therefore, forest owners are interested in a reproducible quantification of carbon stocks at the level of forest management units and the impact of management to these stocks or their changes. We calculated the carbon stocks in tree biomass and the organic layer including their uncertainties for several forest management units (Tharandt forest, Eastern Germany, 5,500 ha) spatially explicit at the scale of individual stands by using standard forest data sources. Additionally, soil carbon stocks along a catena were quantified. Finally, carbon stocks of spruce and beech dominated stands were compared and effects of thinning intensity and site conditions were assessed. We combined forest inventory and data of site conditions by using the spatial unions of the shapes (i.e., polygons) in the stand map and the site map. Area weighted means of carbon (C) stocks reached 10.0 kg/m2 in tree biomass, 3.0 kg/m2 in the organic layer and 7.3 kg/m2 in mineral soil. Spatially explicit error propagation yielded a precision of the relative error of carbon stocks at the total studied area of 1% for tree biomass, 45% for the organic layer, and 20% for mineral soil. Mature beech dominated stands at the Tharandt forest had higher tree biomass carbon stocks (13.4 kg/m2) and lower organic layer carbon stocks (1.8 kg/m2) compared to stands dominated by spruce (11.6, 3.0 kg/m2). The difference of tree biomass stocks was mainly due to differences in thinning intensity. The additional effect of site conditions on tree carbon stocks was very small. We conclude that the spatially explicit combination of stand scale inventory data with data on site conditions is suited to quantify carbon stocks in tree biomass and organic layer at operational scale.     

Governance of forest conservation and co-benefits for Bangladesh under changing climate

We focused on key aspects of forest governance for biodiver- sity conservation in implementing new climate change policies. The national forest institutions must be adaptive to identify the existing pitfalls of prior conservation policies to take advantage of new climate change policies. Strengthening roles and technical capacity of national institutions for systematic biodiversity monitoring and carbon stock assessment is required in developing and least developed countries. Community participation needs careful analysis to ensure equitable ac- cess of particular social groups to local decision-making processes and to sustain optional livelihoods. The livelihood options around forest reserves or protected areas must be taken into account to enhance forest-based adaptation.     

Forest productivity and tree diversity relationships depend on ecological context within mid-Atlantic and Appalachian forests (USA)

Factors influencing the relationship between ecosystem productivity and biological diversity form the basis of much ecological theory. An understanding of how productivity-diversity relationships are influenced by scale of observation and unique attributes of ecoregions may provide important insights to aid conservation planning for carbon retention and biodiversity. Here we use publically available datasets to investigate patterns of productivity-diversity and explore potential factors influencing these patterns in forests located in five mid-Atlantic and Appalachian states. We used a geographic information system (GIS) to overlay multiple publically available datasets including remotely sensed estimates of productivity from MODIS and tree diversity estimated from the forest inventory analysis (FIA) database. We evaluated productivity-diversity relationships using two scales of observation (among and within ecoregions). We also determined if productivity-diversity relationships might be related to region-wide patterns in land use, and if the relationships varied by forest type, land management zones, and along gradients of mean productivity and diversity. Productivity-diversity relationships depended on scale and varied among ecoregions, and land use was correlated with both productivity and diversity. Mountainous ecoregions were characterized by positive productivity-diversity relationships, whereas coastal ecoregions were characterized by negative productivity-diversity relationships. Forest types and management zones that were on average less productive and more diverse exhibited positive productivity-diversity relationships across stands (the most productive stands were more diverse). In contrast, ecoregions and forest types that were on average more productive and less diverse exhibited negative productivity-diversity relationships (the most productive stands were less diverse). In conclusion, regional and local ecological and anthropogenic factors likely influence productivity-diversity relationships and these relationships appear to change along gradients of productivity and diversity.     

Farmers’ perceptions and attitudes toward forest watershed conservation of the North Selangor Peat Swamp Forest

Over the past several decades, the management of forest ecosystem functions through policies such as “command and control” has not been successful, largely because existing policies and legislation for natural resource management are inadequate and often formulated without consulting local communities such as farmers. However, farmers’ decisions to participate in natural resource conservation or watershed conservation more particularly are generally influenced by their knowledge of the problems and perceived benefits of conservation. This study focuses on farmers’ perceptions and attitudes toward forest watershed conservation in the North West Selangor Peat Swamp forest of Malaysia. A survey questionnaire was administered to 380 paddy farmers at the North West Selangor irrigation scheme. Dates were analyzed using exploratory factor analysis (EFA) and the theory of value and social psychology constructs. The study concludes that farmers have generally positive attitudes toward forest watershed conservation. Therefore, we recommend farmers’ involvement in the conservation and management of the North Selangor Peat Swamp Forest (NSPSF).     

浙江淳安县竹林生态服务价值评估研究

竹林具有减少土壤损失、涵养水源、释放负氧离子、固碳释氧等多种生态功能。用生态经济学原理与方法对浙江淳安县竹林的部分生态服务价值进行了评估。结果表明:淳安县竹林生态服务总价值为5.94亿元,每公顷竹林的生态服务价值为4.07万元;在生态服务总价值中,固碳释氧服务价值所占比重最大,为89.79%;其次为涵养水源服务价值,占9.52%。可见,竹林生态服务价值主要体现在改善环境质量和涵养水源方面。研究结果可以为货币化竹林生态服务提供借鉴。     

Reconciliation of research on forest carbon sequestration and water conservation

Carbon sequestration and water conservation are two of the key ecosystem services that forests provide for societal need to address environmental issues.Optimization of the dual services is the ultimate goal in forest management for mitigating global climate change and safeguarding terrestrial water balance.However,there are some tradeoffs between gain in forest productivity and ecosystem water balance.We conducted literature review based on published articles for learned knowledge on forest carbon fixation and hydrological regulations.Some knowledge gaps and research needs are identified by examining the inter-connections between forest carbon sequestration and water conservation.Past researches have helped gain basic understanding of the mechanisms and controls of forest carbon fixation and hydrological regulations as two separate issues.Tools and approaches are well established for quantifying and monitoring forest carbon and hydrological issues,operating at different spatial and temporal scales.There are knowledge gaps on how to design afforestation schemes facilitating enhanced ecosystem services in forest carbon sequestration and water conservation.For the top-down planning of afforestation in regions where water availability is anticipated to be problematic,the questions of how much and where to plant for given land availability,known environmental implications,and sustained regional development and livelihood need to be addressed.For local management considerations,the questions of what and how to plant prevail.Efforts are needed in joint studies of forest carbon sequestration and water conservation functionalities,specifically in relation to establishment and management of planted forests aiming for delivering regulatory ecosystem services in carbon sequestration,water conservation and other social values.We propose an integrated framework with dual consideration of carbon sequestration and water conservation in forest management for future research pursue.     

Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images

Forests play an important role in carbon sinks and mitigation of atmospheric concentrations of carbon dioxide and greenhouse effect. Given that sample plots used for collection of forest carbon observations are often much smaller than the map units of forest carbon at regional, national, and global scales, scientists are currently experiencing two challenges. The first challenge is to produce reliable maps of forest carbon using the data from inconsistent sizes of plots and image pixels. Also, because estimates of forest carbon normally contain uncertainties, the second challenge is to accurately model propagation of uncertainties from input data to output results. In this study, a methodology for mapping and analyzing spatial uncertainty of forest carbon estimates was developed to address these challenges. The methodological framework consisted of two methods. The first one was up-scaling method that combined and scaled up existing national forest inventory plot data and satellite images from smaller sample plots and image pixels to larger map units. The second one was spatial uncertainty analysis and error budget method that entailed modeling propagated uncertainties through a geostatistical mapping system. A case study using 46 permanent national forest inventory plots from Wu-Yuan County, Jiangxi, China, was undertaken to test this methodology. The results showed that this method reproduced not only the spatial distribution of forest carbon but also the spatial pattern of variances of its estimates and was able to quantify the contributions of uncertainties from the field plot data and satellite images to the uncertainties of forest carbon estimates. Thus, this study, to some extent, overcame the gaps that currently exist in the generation and assessment of forest carbon estimation maps. Moreover, the results showed that in this case study, the variation of the band ratio defined as (TM2 + TM3 + TM5)/TM7 contributed more uncertainties to the estimates of forest carbon than the variation of the plot data. In addition, we also found out that the product of the input plot forest carbon variance and the band ratio variance, implying the interaction between these two variables, reduced the uncertainties of the forest carbon estimates.     

Evaluating the benefit of avalanche protection forest with GIS-based risk analyses—A case study in Switzerland

The protection of people, buildings and infrastructure against natural hazards is one of the key functions of mountain forests. Since the protective function strongly depends on small-scale local conditions such as terrain and stand characteristics, spatially explicit evaluation methods are necessary to provide information required for an effective and cost-efficient forest management. Risk analyses are recognized as the best method for estimating the danger from various natural hazards. Currently, however, risk-based strategies are rarely addressed in the management of protection forest. We present and discuss a risk-based approach to evaluate the protective effect of mountain forests in a spatially explicit manner to demonstrate the advantages of future risk-based protection forest management. We illustrate the approach by performing a GIS-based risk analysis in the case study area ‘Bannwald of Andermatt’ (Switzerland) for a 300-year snow avalanche event. Classifying forest structures based on aerial photographs allowed developing different forest cover scenarios and modeling potential avalanche release areas within the forest. Potential avalanche release areas above the forest and the avalanche run-out distances under five different scenarios of forest cover were calculated by using a two-dimensional avalanche simulation model. We calculated the annual collective risk for each scenario and compared the change in risk to reveal the spatial distribution of the protective effect of the forest. Resulting risks differed strongly between forest cover change scenarios. An enlargement of an existing wind-disturbed area within lower parts of the slope resulted only in a slight increase of risk. In contrast, the effect of an unforested area in the upper parts of the observed forest more than doubled the risk. These results show how a risk-based approach can help to quantify and illustrate the impact of differences in forest cover on the protective effect of mountain forests. It is a promising approach to determine the economic value of protection forests and thus provide quantitative and qualitative information for cost-efficient forest maintenance planning. With regard to the achievements of research to date, the presented approach may serve as a valuable method to support decision-making in a future protection forest management.     

A Nondestructive,Remote Sensing-Based Estimation of the Economic Value of Aboveground Temperate Forest Biomass (Case Study: Hyrcanian Forests,Nowshahr-Iran)

ABSTRACT

Background: Traditional field-based methods of measurement of biomass and carbon storage face difficulty in collecting time-consuming and expensive, suggests the use of remote sensing-based techniques. It estimates the economic value of the aboveground biomass (AGB) using satellite remote sensing across the Hyrcanian forests of Iran. Methods: The Landsat-8 OLI sensor data were combined with field-based allometric information of 186 circular sample plots. The AGB was calculated at the plot level using the collected data and specific volumetric mass for species in the studied area. It was followed by calculating the carbon storage using a 50% carbon coefficient and the photosynthesis equation at the forest parcel level. Model results using the random forest and support vector machines. The carbon sequestration value was calculated with USD 25.3 as a shadow value of carbon in 2014 and using the replacement cost approach. Results: The highest performances achieved by RF for biomass, carbon storage and the carbon storage value (Iranian Rials of 0.67% and 16%, respectively). The value was derived once at the plot level of 12.22 million IRR (370.43 USD) per ha. In addition, at the parcel level, which resulted in an estimated value of 12.87 million IRR (390.24 USD) per ha.     

Valuing forest recreation on the national level in a transition economy: The case of Poland

Recreation benefits constitute a substantial part of the total economic value of forests, and are important for the choice of multi-functional forest policies. The application of methods valuing such benefits is in its infancy in transition economies in Central and Eastern Europe (CEE), so value estimates for policy use are sometimes transferred from Western Europe proportionally scaled down by GDP. However, little is known about how recreation values vary with income, and one risks underestimating benefits in CEE. This paper reports the findings of the first comprehensive, national-level study in any CEE country estimating annual and per trip forest recreation values in Poland using the Travel Cost (TC) and Contingent Valuation (CV) methods. Two in-person interview surveys of forest recreation behaviour were carried out. The first was administered on-site in ten representative forest areas, and the other in the homes of a national sample of adult Poles. Results show that forest recreation is highly valued in Poland, at Euros 0.64–6.93 per trip per person, depending on the valuation method. Both trip frequency and per trip values are higher than the average in Western Europe, despite a lower income level. Thus, a simple GDP-adjusted transfer from Western Europe would substantially undervalue forest recreation in Poland. Further, a comparison of TC consumer surplus estimates and GDP/capita in Europe shows no clear relationship, indicating that a range of cultural, institutional and other factors may be important.