Publications

A global dataset of crowdsourced land cover and land use reference data (2011-2012)

Climate Change and Disturbance Interact to Alter Landscape Reflectivity (Albedo) in Boreal Forests Across a Large Latitudinal Gradient in Siberia

No abstract is provided for this article.

Downgrading Recent Estimates of Land Available for Biofuel Production

Recent estimates of additional land available for bioenergy production range from 320 to 1411 million ha. These estimates were generated from four scenarios regarding the types of land suitable for bioenergy production using coarse-resolution inputs of soil productivity, slope, climate, and land cover. In this paper, these maps of land availability were assessed using high-resolution satellite imagery. Samples from these maps were selected and crowdsourcing of Google Earth images was used to determine the type of land cover and the degree of human impact. Based on this sample, a set of rules was formulated to downward adjust the original estimates for each of the four scenarios that were previously used to generate the maps of land availability for bioenergy production. The adjusted land availability estimates range from 56 to 1035 million ha depending upon the scenario and the ruleset used when the sample is corrected for bias. Large forest areas not intended for biofuel production purposes were present in all scenarios. However, these numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development.

First mission - towards a global harmonised in-situ data repository for forest biomass datasets validation

Global measurements of forest height, biomass are urgently needed as essential climate and ecosystem variables, but can benefit from greater co-operation between remote sensing (RS) and forest ecological communities. The Forest Observation System - FOS (https://forest-observation-system.net/ [https://forest-observation- system.net/]) is an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. FOS aims to link the RS community with ecologists who measure forest biomass and estimating biodiversity in the field. The FOS aims to overcome data sharing issues and introduce a standard biomass data flow from tree-level measurement to the plot-level aggregation served in the most suitable form for the RS. Ecologists benefit from the FOS with improved access to global biomass information, data standards, gap identification and potentially improved funding opportunities to address the known gaps and deficiencies in the data. FOS closely collaborate with the CTFS-ForestGEO, the ForestPlots.net (incl. RAfNFOR, AfriTRON and T-FORCES), AusCover, TmFO and the llASA network. FOS is an open initiative with other networks and teams most welcome to join. The online database provides open access for forest plot location, canopy height and above-ground biomass. Plot size is 0.25ha or larger. Comparison of plot biomass data with available global and regional maps (incl. Kindermann et al., 2013; Thurner et al., 2013; Saatchi et al., 2011; Baccini et al., 2012; Avitabile et al., 2016; Hu et al., 2016; Santoro et al., 2018) shows wide range of uncertainties associated with biomass estimation.

Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map

Data fusion represents a powerful way of integrating individual sources of information to produce a better output than could be achieved by any of the individual sources on their own. This paper focuses on the data fusion of different land cover products derived from remote sensing. In the past, many different methods have been applied, without regard to their relative merit. In this study, we compared some of the most commonly-used methods to develop a hybrid forest cover map by combining available land cover/forest products and crowdsourced data on forest cover obtained through the Geo-Wiki project. The methods include: nearest neighbour, naive Bayes, logistic regression and geographically-weighted logistic regression (GWR), as well as classification and regression trees (CART). We ran the comparison experiments using two data types: presence/absence of forest in a grid cell; percentage of forest cover in a grid cell. In general, there was little difference between the methods. However, GWR was found to perform better than the other tested methods in areas with high disagreement between the inputs.

Impacts of vegetation fire in Russia on global carbon cycles in the past five years (Abstract)

LACO-WIKI-A new open access online portal for land cover validation with high resolution imagery

No abstract is provided for this article.

Impact of terrestrial ecosystems of Russia on the global carbon cycle from 2003-2008: An attempt of synthesis

No abstract is provided for this article.

Integration of remote sensing and ground methods in research of carbon cycling of Russian forests

Global planted trees extent 2015

We provide a global extent of planted trees landscapes (aggregated land use classes of planted forest, woody plantations and agroforestry). The layer has binary value and represents the status for the year 2015 at a spatial resolution of 100 m. The layer has been derived from a global forest management map produced by the Nature Map project (https://naturemap.earth/). The description of the methodology could be found here: https://doi.org/10.5281/zenodo.3933966

Dynamics of pine forest productivity with age depends on soil properties

No abstract is provided for this article.

New estimates of live biomass and net primary production of Russian forests: A footprint of climate change?

The paper presents new estimates of live biomass (phytomass) and net primary production (NPP) of Russian forests for 1993 and 2003. These indicators are estimated based on forest inventory data and a specially developed semi-empirical modeling system. The latter contains regional models of growth by major forest forming species, multi-dimensional models of phytomass and models of biological production. It is shown that the fractional structure of forest phytomass substantially differs from previous estimates that indicated significant temporal trends of the share of aboveground wood (AGW), green part (GP) and belowground (BG) phytomass. The total forest NPP is substantially higher than previously reported. These changes may be attributed to climatic change which was dramatic over the last four decades, particularly in Asian Russia.

Global patterns of tree wood density

Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high-resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree-level wood density measurements. An ensemble of four top-performing models combined with eight cross-validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%-63% of spatial variations, followed by vegetation characteristics (25%-31%) and edaphic properties (11%-16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change.

Carbon account of forest ecosystems as a fuzzy system: a case study for Northern Eurasia

We consider practicality of a verified account of Net Ecosystem Carbon Budget for forest ecosystems (CA) that supposes reliable assessment of uncertainties, i.e. understanding uncertainty of The FCA is a fuzzy (underspecified) system, of which membership function is inherently stochastic. Thus, any individually used of FCA is not able to estimate structural and usually reported method are inevitably partial. Attempting an estimation of full uncertainties of the studied system we follow the requirements of applied systems analysis integrating the major methods of terrestrial ecosystems carbon account, assessing the method for intermediate and final indicators of CA with their following mutual constraints. Landscape-ecosystem approach (LEA) 1) serves for strict systems designing the account, 2)contains all relevant spatially distributed empirical and semi-empirical data and models, and 3) is presented in form of an Integrated Land Information System (ILIS). By-pixel parametrization of forest cover is provided by utilizing multi-sensor remote sensing data (1 RS products used) within GEO-wiki platform and other relevant information based on special optimization algorithms. Major carbn fluxes within the LEA (NPP, HR, disturbances etc.) are estimated based on fusion of empirical data with process-based elements by sets of regionally distributed models. Uncertainties within LEA are assessed for each module and at each step of the account. Withi method results and (including LEA, process-based models, eddy covariance, and inverse modelling) are harmoized based on the Bayesian approach. The above methodology have been applied to carbon account of Russian forests for 2000-2010;uncertainties of the FCA for individual years were estimated in limits of 25%. We discussed strengths and weaknesses of the paproach, system requirements to different methods of FCA, information and research needs, obtained and potential levels of uncertainties.

A dataset of forest biomass structure for Eurasia

The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930–2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

R data script: From acacia to eucalypt: productivity and fertility implications of plantations species shift in Indonesia

The plantation forestry sector in Indonesia has seen a change in species from Acacia mangium to Eucalyptus pellita. This change, forced by diseases spreads, has affected more than 90% of the plantation area in Indonesia and it is unprecedented in its scale in the history of plantation forestry (Nambiar et al., 2018). It is also a change of tree species with very different eco-physiological patterns: Acacias – in contrast to eucalypts - are leguminous trees and therefore self-sufficient in nitrogen supply and capable of building significant stocks of nitrogen and carbon in the soil, two main determinants of plantation productivity. The large-scale species shift therefore raises questions about the sustainability of the pulp and paper sector in Indonesia in the coming decades as well as the role of past land use and site quality in Indonesia’s forest restoration pledge. The proposed contribution therefore aims at analyzing the sustainability in terms of productivity of the Indonesian plantation forestry sector under the new eucalypts regime. To that end, we will deploy the BioGeoChemistry Management Model (BGCMAN; Pietsch, 2014) which is capable of representing the carbon, water and nitrogen cycles in great detail. Expected results will include a reconstruction of the rise and fall of A. mangium and shift to E. pellita as well as forecasts of plantation productivity and soil fertility over the next decades; it will notably answer the question for how long soil N-stock accumulated by acacias will be able to feed eucalypts.

Mapping Human Impact Using Crowdsourcing

This chapter outlines how crowdsourcing and Google Earth have been used to create the first global crowdsourced map of human impact. Human impact in this context refers to the degree to which the landscape has been modified by humans as visible from satellite imagery...

Quantifying Impacts of National-Scale Afforestation on Carbon Budgets in South Korea from 1961 to 2014

Forests play an important role in regulating the carbon (C) cycle. The main objective of this study was to quantify the effects of South Korean national reforestation programs on carbon budgets. We estimated the changes in C stocks and annual C sequestration in the years 1961–2014 using Korea-specific models, a forest cover map (FCM), national forest inventory (NFI) data, and climate data. Furthermore, we examined the differences in C budgets between Cool forests (forests at elevations above 700 m) and forests in lower-altitude areas. Simulations including the effects of climate conditions on forest dynamics showed that the C stocks of the total forest area increased from 6.65 Tg C in 1961 to 476.21 Tg C in 2014. The model developed here showed a high degree of spatiotemporal reliability. The mean C stocks of the Cool forests and other forests increased from 4.03 and 0.43 Mg C ha−1, respectively, to 102.43 and 73.76 Mg C ha−1 at a rate of 1.82 and 1.36 Mg C ha−1 yr−1 during the same period. These results imply that, although the total Cool forest area of South Korea occupied only about 12.3% (772,788 ha) of the total forest area, the Cool forests play important roles in C balances and forest ecosystems in South Korea. Annual C sequestration totals are projected to decrease at a low rate in the near future because the overall growth rate of a mature forest decreases as the stand ages. Our results quantified forest C dynamics in South Korean forests before and after national reforestation programs. Furthermore, our results can help in development of regional and national forest management strategies to allow for sustainable development of society and to cope with climate change in South Korea.