Publications

Boreal forests of Northern Eurasia are experiencing ongoing changes in climate, strong impacts by humans including transformation of previously untouched landscapes, and dramatically accelerating disturbance regimes. Current global and regional climatic models predict for this region the most dramatic climatic change over the globe. Unregulated and often destructive anthropogenic impacts on the environment and natural landscapes may substantially accelerate the negative consequences of climatic change. Complexities of the situation are evident: need to take decisions for underspecified dynamics systems under uncertainties; relevancy to consider dual strategy that integrates mitigative and adaptive measures, particularly under no-regret and win-win considerations; necessity to derive minimum mitigation standards from the limits of adaptation; inevitability of non-linear responses and feedbacks and probability to meet surprises in the biosphere's behavior; etc. It defines a need for development of new philosophy of cognition and policy making by using open, iterative, distributed-modular systems based on shared pools of models, tools libraries, and data sets. Such a situation defines an obligatory need to comprehensively use methodologies of applied system analysis and integrated modeling. Following the basic steps of applied systems analysis (fixation of the problem; diagnostics; (list of) stakeholders; problem mess; setting the goal; criteria; experimental research; analysis of input information; selection of the strategy, development and improvement of the model; depiction of alternatives; and decision making implementation) put the modeling on a solid scientific basis. Integrated models that include components of different nature (ecological, economic, social) are considered as a major tool of perception of future trajectories of forests in a changing world in spite of the fact that application of integrated modeling generates many cognitive problems, trade-offs and challenges. A central point of adaptation and mitigation strategies is development of robust policies. Robust policies should (1) ensure long-term stability of systems. behavior against multiple events (scenarios); (2) account for extreme events that require specific models; (3) consider uncertainties in a possible comprehensive and explicit form; (4) allow for flexibility to form a diversity of decisions dependent on associated risks and costs, performance indicators of stakeholders, (5) consider in an explicit spatio-temporal way ecological, economic and social dimensions, (6) collective risk; (7) include safety criteria, constraints, and performance indicators of involved agents. Adaptation and mitigation measures in the forest sector could be effective if they are part of a wide strategy which would involve all relevant sectors of national economy, particularly energy, industry, agriculture, tourism etc. combined in common political and institutional frameworks. Adaptation and anticipatory strategy should be an inherent part of transition to sustainable forest management. However, background philosophy of classical forestry becomes less and less reliable in a continuously changing world. Thus, modeling becomes a working tool for practical adaptive forest management. Adaptive forest management is defined as a management approach that acknowledges the lack of unequivocal and definite knowledge about the ways in which forest ecosystems work, and the uncertainty that dominates interactions with them. We consider major requirements to and specifics of adaptation and mitigation strategies in boreal forests which include inter alia: (1) a concept of sustainable development and sustainable forest management of regions of high latitudes; (2) integrated land observing systems; (3) a new system of specially protected territories; (4) new strategy and institutional background of forest fire protection; (5) legislative and normative base of adaptation and mitigation as a background of adaptive forest management; (6) system of adaptation of structure of boreal landscapes to climate change; and (7) considering management of major biogeochemical cycles, primarily carbon cycle, as a crucial issue of future strategies. We illustrate some practical results obtained by IIASA-ESM Integrated Modeling Cluster and other approaches. These examples show that recommended strategies could result in higher stability and productivity of forest ecosystems, increased abundance of favored species and reduced fragmentation of forests. However, the biggest problem deals with difficulties to reduce losses from worsening the environment and disturbances. No single strategy appears able to achieve all possible forest management objectives, and adaptation and mitigation strategies should be connected to regional climatic, ecological and social peculiarities.

. As a key component of the Earth system, roots play a key role in linking Earth's lithosphere, hydrosphere, biosphere and atmosphere. Here we combine 10 307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially explicit global high-resolution (∼ 1 km) root biomass dataset, including fine and coarse roots. In total, 142 ± 25 (95 % CI) Pg of live dry-matter biomass is stored belowground, representing a global average root : shoot biomass ratio of 0.25 ± 0.10. Earlier studies (Jackson et al., 1997; Robinson, 2007; Saugier et al., 2001) are 44 %–226 % larger than our estimations of the total root biomass in tropical, temperate and boreal forests. The total global forest root biomass from a recent estimate (Spawn et al., 2020) is 24 % larger than this study. The smaller estimation from this study is attributable to the updated forest area, spatially explicit aboveground biomass density used to predict the patterns of root biomass, new root measurements and the upscaling methodology. We show specifically that the root shoot allometry is one underlying driver that has led to methodological overestimation of root biomass in previous estimations. Raw datasets and global maps generated in this study are deposited at the open-access repository Figshare (https://doi.org/10.6084/m9.figshare.12199637.v1; Huang et al., 2020).

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions. Global spatial data for terrestrial vertebrate and vascular plant diversity, above- and below-ground biomass carbon, and potential clean freshwater volume are combined in a joint optimization study to identify potential synergies for conservation management.

During December 2020, a crowdsourcing campaign to understand what has been driving tropical forest loss during the past decade was undertaken. For 2 weeks, 58 participants from several countries reviewed almost 115 K unique locations in the tropics, identifying drivers of forest loss (derived from the Global Forest Watch map) between 2008 and 2019. Previous studies have produced global maps of drivers of forest loss, but the current campaign increased the resolution and the sample size across the tropics to provide a more accurate mapping of crucial factors leading to forest loss. The data were collected using the Geo-Wiki platform ( www.geo-wiki.org ) where the participants were asked to select the predominant and secondary forest loss drivers amongst a list of potential factors indicating evidence of visible human impact such as roads, trails, or buildings. The data described here are openly available and can be employed to produce updated maps of tropical drivers of forest loss, which in turn can be used to support policy makers in their decision-making and inform the public.

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%.

A new 1 km global IIASA ‐ IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo‐Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA ‐ IFPRI cropland product has been validated using very high‐resolution satellite imagery via Geo‐Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo‐Wiki. The first ever global field size map was produced at the same resolution as the IIASA ‐ IFPRI cropland map based on interpolation of field size data collected via a Geo‐Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

Abstract Woody canopies regulate exchanges of energy, water and carbon, and their three-dimensional (3D) structure supports much of terrestrial biodiversity. Remote sensing technologies such as airborne laser scanning (ALS) now enable the 3D mapping of entire landscapes. However, we lack the large, harmonized and geographically representative ALS collections needed to build a global picture of woody ecosystem structure. To address this challenge, we developed the Global Canopy Atlas (GCA): 3,458 ALS acquisitions transformed into standardized and analysis-ready maps of canopy height and elevation at 1 m 2 resolution. The GCA covers 56,554 km 2 across all major biomes. 19% of this area has been scanned multiple times, and 87% of all GCA products are openly available, covering 95% of the total area. To showcase its wide range of applications, we applied the GCA in three case studies. First, we validated three global satellite-derived canopy height maps, finding poor performance at native resolution (1-30 m, R 2 < 0.38) and moderate performance at 250 m resolution (R 2 < 0.65). Second, analyzing global patterns in canopy gap size frequency we discovered an unexpectedly large variation of power law exponents from branch to stand level (α = 1.52 to 2.38), pointing to a fundamental scale-dependence of forest structure. Third, we developed a framework to standardize forest turnover quantification from multi-source, multi-temporal ALS. In a temperate forest in North America it revealed that 21% of canopy gaps closed within 12 years of opening and would thus be missed by infrequent monitoring. As demonstrated by these case studies, the GCA provides a novel data source for ecologists, foresters, remote sensing scientists and the ecosystem modelling community that substantially advances our ability to understand the structure and dynamics of woody ecosystems at global scales.