Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the twenty-first century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Northern Eurasia Future Initiative (NEFI): Facing the Challenges and Pathways of Global Change in the Twenty-first Century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies codesigned with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Postfire recruitment failure in Scots pine forests of southern Siberia

Wildfire disturbances effect changes in vegetation communities that in turn influence climate. Such changes in boreal forest ecosystems can persist over decadal time scales or longer. In the ecotone between boreal forest and steppe in the region southeast of Lake Baikal in southern Siberia, shifts between the two vegetation types may be precipitated by variations in site specific conditions, as well as disturbance characteristics such as fire frequency and severity. Warmer, drier conditions in the region have been associated with a decrease in fire return intervals and greater burn severity that may, in turn, drive conversion of forests to steppe vegetation at a greater rate than has occurred prior to the onset of warming and drying. Stand-replacing fires in Pinus sylvestris stands in southern Siberia may lead to recruitment failure postfire, particularly on southwest to west-facing slopes, which are more often dominated by grasses. This study uses a combination of field data and remotely sensed indices of vegetation and moisture to distinguish between recruitment pathways in southern Siberia, and to study the influence of factors related to soils, topography, fire severity and winter snow cover on these. We expected that recruitment success would be associated with lower burn severity (higher NBR), higher greenness (NDVI) and moisture (NDMI), and winter snow (NDSI) postfire. We also expected phenological characteristics to differ among recruitment paths. Prior to burning, our sites are broadly similar in terms of remotely sensed indices of moisture (NDMI), vegetation (NDVI), and winter fractional snow cover (NDSI), but recruitment failure sites are generally drier and less green postfire. Initial differences in greenness and moisture among sites characterized by abundant recruitment (AR), intermediate recruitment (IR) and recruitment failure (RF) become more pronounced over the initial decades postfire. The earliest separability of AR and RF sites using remotely sensed indices occurs in the winter months 3–4 years postfire, during which time NDSI is highest for AR sites and lowest for RF. Although seasonality was important with regard to distinguishing among AR, IR and RF index values, the timing of phenological events such as start and end of season did not differ significantly among the sites

Increasing fire and logging disturbances in Siberian boreal forests: a case study of the Angara region

Forest disturbances are a critical environmental issue globally and within the boreal biome, yet detailed attribution and trends in disturbances are lacking for many Siberian regions. The Angara region located in the southern taiga of Central Siberia has experienced significant disturbances during the past several decades and is a hotspot of change in Eurasia. Here we estimated fire and logging disturbances using MODIS and Landsat data for the period 2002–2020 across the Angara region and analyzed the resulting trends. Average annual burned and logged area was about 220 and 31 thousand ha or 2 and 0.3% of the study area, respectively. In total, about 4.1 million ha (38% of the region) and 0.6 million ha (6% of the region) were disturbed by fires and logging, respectively. Spatial analysis showed that almost 50% of fires were ignited within 2 km of anthropogenic features such as settlements, roads and logged areas. Almost 5% of the Angara region was burned two or more times during the 19 years of observations. Improved and strictly-enforced conservation and management policies are required to halt continued forest degradation in the Angara region and similarly-affected boreal forests in Siberia

Increasing Fuel Loads, Fire Hazard, and Carbon Emissions from Fires in Central Siberia

The vast Angara region, with an area of 13.8 million ha, is located in the southern taiga of central Siberia, Russia. This is one of the most disturbed regions by both fire and logging in northern Asia. We have developed surface and ground fuel-load maps by integrating satellite and ground-based data with respect to the forest-growing conditions and the disturbance of the territory by anthropogenic and natural factors (fires and logging). We found that from 2001 to 2020, fuel loads increased by 8% in the study region, mainly due to a large amount of down woody debris at clearcuts and burned sites. The expansion of the disturbed areas in the Angara region resulted in an increase in natural fire hazards in spring and summer. Annual carbon emissions from fires varied from 0.06 to 6.18 Mt, with summer emissions accounting for more than 95% in extreme fire years and 31–68% in the years of low fire activity. While the trend in the increase in annual carbon emissions from fires is not statistically significant due to its high interannual variability and a large disturbance of the study area, there are significantly increasing trends in mean carbon emissions from fires per unit area (p p p p p < 0.025) forests. This indicates deeper burning and loss of legacy carbon that impacts on the carbon cycle resulting in climate feedback

Assessment of post-fire vegetation recovery in Southern Siberia using remote sensing observations

Wildfire is one of the main disturbances affecting forest dynamics, succession, and the carbon cycle in Siberian forests. The Zabaikal region in southern Siberia is characterized by one of the highest levels of fire activity in Russia. Time series of Landsat data and field measurements of the reforestation state were analyzed in order to estimate post-fire vegetation recovery. The results showed that the normalized burn ratio time series can be used to estimate forest recovery in the pine- and larch-dominated forests of the Zabaikal region. Multiple factors determine a forest's recovery rate after a wildfire, including fire severity, tree species characteristics, topography, hydrology, soil properties, and climate. Assessing these factors is important if we are to understand the effects of fire on forest succession and to implement sustainable forest management strategies. In this work we used the field data and Landsat data to estimate post-fire vegetation dynamics as a function of several environmental factors. These factors include fire severity, pre-fire forest state, topography, and positive surface temperature anomalies. A regression model showed that fire frequency, fire severity, and surface temperature anomalies are the primary factors, explaining about 58% of the variance in post-fire recovery. High frequency of fire and positive surface temperature anomalies hamper the post-fire reforestation process, while more severe burns are followed by higher recovery rates. Further studies are necessary to consider other important factors such as soil properties, moisture, and precipitation, for better explanation of post-fire vegetation recovery

Direct and longer-term carbon emissions from arctic-boreal fires: A short review of recent advances

Increases in arctic-boreal fires can switch these biomes from a long-term carbon (C) sink to a source of atmospheric C through direct fire emissions and longer-term emissions from soil respiration. We here review advances made by the arctic-boreal fire science community over the last three years. Landscapes of intermediate drainage tend to experience the highest C combustion, dominated by soil C emissions, because of relatively thick and periodically dry organic soils. These landscapes may also induce a climate warming feedback through combustion and postfire respiration of legacy C, including from permafrost thaw and degradation. Legacy C is soil C that had escaped burning in the previous fire. Data shortages from fires in tundra ecosystems and Eurasian boreal forests limit our understanding of C emissions from arctic-boreal fires. Interactions between fire, topography, vegetation, soil, and permafrost need to be considered when estimating climate feedbacks of arctic-boreal fires

Mapping Forest Stability within Major Biomes Using Canopy Indices Derived from MODIS Time Series

Deforestation and forest degradation from human land use, including primary forest loss, are of growing concern. The conservation of old-growth and other forests with important environmental values is central to many international initiatives aimed at protecting biodiversity, mitigating climate change impacts, and supporting sustainable livelihoods. Current remote-sensing products largely focus on deforestation rather than forest degradation and are dependent on machine learning, calibrated with extensive field measurements. To help address this, we developed a novel approach for mapping forest ecosystem stability, defined in terms of constancy, which is a key characteristic of long-undisturbed (including primary) forests. Our approach categorizes forests into stability classes based on satellite-data time series related to plant water–carbon relationships. Specifically, we used long-term dynamics of the fraction of photosynthetically active radiation intercepted by the canopy (fPAR) and shortwave infrared water stress index (SIWSI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2003–2018. We calculated a set of variables from annual time series of fPAR and SIWSI for representative forest regions at opposite ends of Earth’s climatic and latitudinal gradients: boreal forests of Siberia (southern taiga, Russia) and tropical rainforests of the Amazon basin (Kayapó territory, Brazil). Independent validation drew upon high-resolution Landsat imagery and forest cover change data. The results indicate that the proposed approach is accurate and applicable across forest biomes and, thereby, provides a timely and transferrable method to aid in the identification and conservation of stable forests. Information on the location of less stable forests is equally relevant for ecological restoration, reforestation, and proforestation activities

Climate change, fire return intervals and the growing risk of permanent forest loss in boreal Eurasia

Climate change has driven an increase in the frequency and severity of fires in Eurasian boreal forests. A growing number of field studies have linked the change in fire regime to post-fire recruitment failure and permanent forest loss. In this study we used four burned area and two forest loss datasets to calculate the landscape-scale fire return interval (FRI) and associated risk of permanent forest loss. We then used machine learning to predict how the FRI will change under a high emissions scenario (SSP3–7.0) by the end of the century. We found that there are currently 133,000 km2 forest at high, or extreme, risk of fire-induced forest loss, with a further 3 M km2 at risk by the end of the century. This has the potential to degrade or destroy some of the largest remaining intact forests in the world, negatively impact the health and economic wellbeing of people living in the region, as well as accelerate global climate change