A chronosequence of wood decomposition in the boreal forests of Russia

Coarse woody debris (CWD) decomposition in the Russian boreal forests of the southern taiga zone was studied at four sites located near St. Petersburg in Northwestern Russia, Krasnoyarsk in Eastern Siberia, lrkutsk in the Baikal region, and Khabarovsk in the Russian Far East. This study was part of a broader research project assessing processes associated with accumulation, storage, and release of carbon by woody detritus in the forests of Russia. A five-class system based on CWD visual characteristics was used to separate logs and snags into decay classes and to estimate their wood density. The largest effect on density was associated with decay classes and species. Region and position had minor effects on density. Decay-class specific density showed a gradual decrease from decay class one (least decayed) to decay class five (most decayed) regardless of species and region. Coniferous snags showed no decrease in density at least for the first two decay classes; for birch this decrease was gradual for both logs and snags. Species became more similar in density from decay class one to decay class five. The chronosequence approach was used to study CWD decomposition by determining change in CWD mass over time. Larch (Larix spp.) and white pine (Pinus siberica/koraiensis) logs had lower decomposition rate-constants than other studied species among the regions fluctuating between 0.015 and 0.031 year [superscript] -1 for larch and 0.015 and 0.019 year[superscript]-1 for white pine. Birch (Betula pendula) had the highest decomposition rate-constants among all species and regions ranging between 0.042 and 0.078 year-1. No effect of temperature or precipitation on decomposition rates was observed among the studied regions, although globally there is a significant effect of temperature at least for species with non-decay resistant heartwood. The management implications of the project results for increasing carbon storage potential of Russian forests through CWD management were examined. The current carbon store of CWD including all forest covered land and disturbed forestland was estimated to be 4.31 Pg C. Depending on species composition, this store can be either decreased to 1.56 Pg C with all tree species being replaced by birch, the fastest decomposing species, or increased to 8.11 Pg C with all species being replaced by Korean pine, the slowest decomposing species. The magnitude of these changes is substantial when compared to the potential increases in carbon sequestration of 2.02 Pg C associated with other management steps such as establishing plantations on forest and agricultural lands, reducing stand replacement fires, reducing harvest rates and increasing rotation age, increasing stand productivity via silvicultural treatments, and establishing plantations on sands, drained peat bogs, and mine tailings

Relating LANDSAT ETM+ and forest inventory data for mapping successional stages in a tropical wet forestRelacionando LANDSAT ETM+ e dados de inventário florestal para mapeamento estádios sucessionais em uma floresta tropical úmida

AbstractIn this study, we test whether an existing classification technique based on the integration of LANDSAT ETM+ and forest inventory data enables detailed characterization of successional stages in a tropical wet forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation hight entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (0.129). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and late successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels. ResumoNesse estudo, testamos se uma técnica de classificação existente, baseada na integração de imagens LANDSAT ETM+ e os dados de inventário florestal, permite a caracterização detalhada dos estádios sucessionais em uma área de floresta tropical úmida. Os objetivos específicos foram: (1) mapear classes de idade florestal na Estação Biológica La Selva, na Costa Rica, e (2) quantificar as incertezas da abordagem proposta em relação aos dados de campo e mapas de vegetação existente. Apesar de terem sido detectadas relações significativas entre dados ETM+ e medidas de entropia da altura da vegetação (um substituto para a idade florestal) o sistema de classificação testados nesse estudo não se demonstrou adequado para caracterizar a variação espacial em idade em La Selva, como evidenciado pela matriz de erro e o baixo coeficiente Kappa (0,129). Fatores que afetam o desempenho da classificação área de estudo em particular, incluem a alta similaridade estrutural entre os estádios sucessionais intermediário e avançado, e a baixa sensibilidade do NDVI a variações na estrutura vertical da biomassa em áreas com níveis elevados de biomassa

Global forest management data for 2015 at a 100 m resolution

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services

The Impact of Disturbance on Carbon Stores and Dynamics in Forests of Coastal Alaska

Changes in climate caused by increased concentrations of carbon dioxide (CO₂) in the Earth’s atmosphere have led land and ocean surface temperatures to increase by 0.85°C and sea level to increase by 19 cm relative to preindustrial times. Global climate change will lead to further alterations in mean temperature and precipitation, as well as their extremes that are likely to influence disturbance regimes. Disturbance play an important role in forest dynamics and succession, by influencing forest ecosystems structure and function, reorganizing forests by reducing live and increasing dead matter, and thus affecting ecosystem carbon (C) balances. Under a changing climate disturbances are likely to cause widespread tree mortality across forested landscapes, creating vast amounts of coarse woody debris (CWD) that will emit C to the atmosphere to a degree that regional C balances and future C dynamics are likely to change. C balance of forested regions depends on inputs in form of C sequestered by live components during growth and outputs in form of C emitted from dead components through decomposition and combustion. Live trees in many forest ecosystems represent the largest aboveground C pool and the dynamics of this pool, as controlled by growth and mortality, have been extensively studied. In contrast, few have examined either the post-disturbance fate of CWD C or assessed C storage potential of salvaged biomass despite the occurrence of multiple recent large-scale disturbance events. Biomass and C stores and their uncertainty were estimated in the Temperate and the Boreal ecoregions of Coastal Alaska using the empirical data from the Forest Inventory and Analysis (FIA) program, literature data, and modeling using standard methods employed by the FIA program. The average aboveground woody live (218.9±4.6 Mg/ha) and log (28.1±1.8 Mg/ha) biomass in the Temperate ecoregion were among the lowest in the Pacific Northwest, whereas snag biomass (30.5±1.0 Mg/ha) was among the highest. In the Boreal ecoregion, CWD biomass comprised almost 50% of the regional aboveground woody store (76.7±3.8 Mg/ha) with bark beetle damaged stands containing 82% of the total CWD biomass. In contrast, in the Temperate ecoregion, CWD comprised 20% of the regional aboveground woody store (277.5 ±5.4 Mg/ha) with 76% of total CWD biomass in undisturbed stands. Total C stores estimates in Coastal Alaska ranged between 1523.6 and 1892.8 Tg with the highest contribution from soils and the largest potential reductions in uncertainty related to the tree and soils C pools. The impact of a large-scale spruce bark beetle (SBB) outbreak on aboveground dead wood C dynamics on the Kenai Peninsula was modeled utilizing data from the FIA program and CWD decomposition rate-constants from a chronosequence and decomposition-vectors analysis. Decomposition rate-constants from the chronosequence ranged between -0.015 yr⁻¹ and -0.022 yr⁻¹ for logs and -0.003 yr⁻¹ and +0.002 yr⁻¹ for snags. Decomposition rate-constants from the decomposition-vectors ranged between -0.045 yr⁻¹ and +0.003 yr⁻¹ among decomposition phases and -0.048 yr⁻¹ and +0.006 yr⁻¹ among decay classes. Relative to log generating disturbances those creating snags delayed C flux from CWD to the atmosphere, produced a smaller magnitude C flux, and had the potential to store 10% to 66% more C in a disturbed system over time. The effect of several management strategies ranging from "leave-as-is" to "salvage-and-utilization" on C stores and emissions following SBB outbreak on Kenai Peninsula, Alaska was evaluated. A forest with immediate post-disturbance regeneration reached pre-disturbance C stores faster than one with delayed regeneration. Lack of regeneration, representing a loss of tree cover on the disturbed portion of the landscape, caused a permanent decrease in wood C stores. Among the "salvage-and-utilization" scenarios considered, biomass fuel production with substitution for fossil fuels created the largest long-term C storage assuming the substitution was permanent. Given that reduction in near-term emissions may be a more robust strategy than long-term ones, the "leave-as-is" scenarios may represent the most feasible way to mitigate global climate change following disturbance

A chronosequence of wood decomposition in the boreal forests of Russia

Coarse woody debris (CWD), represented by logs and snags >10 cm in diameter and >1 m in length, was sampled at eight sites in Russian boreal forests to determine the specific density of decay classes and decomposition rates. Tree species sampled included Abies siberica Ledeb., Betula pendula Roth., Betula costata Trautv., Larix siberica Ledeb., Larix dahurica Turcz., Picea abies (L.) Karst., Picea obovata Ledeb., Picea ajanensis Fisch., Pinus koraiensis Sieb. et Zucc., Pinus siberica Ledeb., Pinus sylvestris L., and Populus tremula L. The mean densities for decay classes 1 through 5 ranged from 0.516 to 0.084 g·cm–3, respectively. Annual decomposition rates varied among the species, and for logs, decomposition rates ranged from 4.2 to 7.8% for B. pendula, 2.6 to 4.9% for Picea spp., 2.7 to 4.4% for Pinus sylvestris, 1.5 to 3.1% for Larix spp., and 1.5 to 1.9% for Pinus koraiensis and Pinus siberica. Logs decomposed faster than snags. Among the sites examined, temperature and precipitation did not correlate with decomposition rates, which is consistent with other studies in the boreal region. Globally, a positive correlation between decomposition and mean annual temperatures was found, with decay-resistant trees less responsive than those with low decay resistance

Collecting Influencers: A Comparative Study of Online Network Crawlers

Online network crawling tasks require a lot of efforts for the researchers to collect the data. One of them is identification of important nodes, which has many applications starting from viral marketing to the prevention of disease spread. Various crawling algorithms has been suggested but their efficiency is not studied well. In this paper we compared six known crawlers on the task of collecting the fraction of the most influential nodes of graph. We analyzed crawlers behavior for four measures of node influence: node degree, k-coreness, betweenness centrality, and eccentricity. The experiments confirmed that greedy methods perform the best in many settings, but the cases exist when they are very inefficient

Relating LANDSAT ETM+ and forest inventory data for mapping successional stages in a wet tropical forest

In this study, we test whether an existing classification technique based on the integration of LANDSAT ETM+ and forest inventory data enables detailed characterization of successional stages in a tropical wet forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation hight entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (0.129). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and late successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels. Resumo Nesse estudo, testamos se uma técnica de classificação existente, baseada na integração de imagens LANDSAT ETM+ e os dados de inventário florestal, permite a caracterização detalhada dos estádios sucessionais em uma área de floresta tropical úmida. Os objetivos específicos foram: (1) mapear classes de idade florestal na Estação Biológica La Selva, na Costa Rica, e (2) quantificar as incertezas da abordagem proposta em relação aos dados de campo e mapas de vegetação existente. Apesar de terem sido detectadas relações significativas entre dados ETM+ e medidas de entropia da altura da vegetação (um substituto para a idade florestal) o sistema de classificação testados nesse estudo não se demonstrou adequado para caracterizar a variação espacial em idade em La Selva, como evidenciado pela matriz de erro e o baixo coeficiente Kappa (0,129). Fatores que afetam o desempenho da classificação área de estudo em particular, incluem a alta similaridade estrutural entre os estádios sucessionais intermediário e avançado, e a baixa sensibilidade do NDVI a variações na estrutura vertical da biomassa em áreas com níveis elevados de biomassa.Pages: 167-17

Mapping Successional Stages in a Wet Tropical Forest Using Landsat ETM+ and Forest Inventory Data

In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels

Coarse woody debris in forest regions of Russia

To assess regional stores of coarse woody debris (CWD) in seven major forest regions of Russia, we combined data collected as part of the routine forest inventory with measurements in 1044 sample plots and the results of density sampling of 922 dead trees. The stores of CWD in the western part of Russia (St. Petersburg, Central, Khanty- Mansi, and Novosibirsk regions) were on average lower (14–20 m3/ha or 4.0–5.8 Mg/ha) than in the East Siberian and Far Eastern regions (40–51 m3/ha or 11.0–14.4 Mg/ha). The difference in CWD stores was particularly large between young forests in two western regions (2.4 Mg/ha in St. Petersburg and 3.4 Mg/ha in the Central region) and in the east (20.4–24.4 Mg/ha). This difference is associated with the prevailing disturbance type: clear-cut harvest in western Russia and natural disturbances in the east. Analysis of variance in CWD stores indicates that region, dominant species, forest age group, productivity class, and interactions of these factors explain 87–88% of the total variance and the strongest effects are for age group and region. Lower stores of CWD within the intensively managed forest regions suggest that further expansion of forest use in many regions of Russia may reduce regional stores of CWD and carbon

Global forest management data for 2015 at a 100 m resolution

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services