Timo Kumpula

High resilience in the Yamal-Nenets social–ecological system, West Siberian Arctic, Russia

Tundra ecosystems are vulnerable to hydrocarbon development, in part because small-scale, low-intensity disturbances can affect vegetation, permafrost soils, and wildlife out of proportion to their spatial extent. Scaling up to include human residents, tightly integrated arctic social-ecological systems (SESs) are believed similarly susceptible to industrial impacts and climate change. In contrast to northern Alaska and Canada, most terrestrial and aquatic components of West Siberian oil and gas fields are seasonally exploited by migratory herders, hunters, fishers, and domesticated reindeer (Rangifer tarandus L.). Despite anthropogenic fragmentation and transformation of a large proportion of the environment, recent socioeconomic upheaval, and pronounced climate warming, we find the Yamal-Nenets SES highly resilient according to a few key measures. We detail the remarkable extent to which the system has successfully reorganized in response to recent shocks and evaluate the limits of the systems capacity to respond. Our analytical approach combines quantitative methods with participant observation to understand the overall effects of rapid land use and climate change at the level of the entire Yamal system, detect thresholds crossed using surrogates, and identify potential traps. Institutional constraints and drivers were as important as the documented ecological changes. Particularly crucial to success is the unfettered movement of people and animals in space and time, which allows them to alternately avoid or exploit a wide range of natural and anthropogenic habitats. However, expansion of infrastructure, concomitant terrestrial and freshwater ecosystem degradation, climate change, and a massive influx of workers underway present a looming threat to future resilience.

Spatial and temporal patterns of greenness on the Yamal Peninsula, Russia: interactions of ecological and social factors affecting the Arctic normalized difference vegetation index

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

Detection of snow surface thawing and refreezing in the Eurasian Arctic with QuikSCAT: implications for reindeer herding.

Snow conditions play an important role for reindeer herding. In particular, the formation of ice crusts after rain-on-snow (ROS) events or general surface thawing with subsequent refreezing impedes foraging. Such events can be monitored using satellite data. A monitoring scheme has been developed for observation at the circumpolar scale based on data from the active microwave sensor SeaWinds on QuikSCAT (Ku-band), which is sensitive to changes on the snow surface. Ground observations on Yamal Peninsula were used for algorithm development. Snow refreezing patterns are presented for northern Eurasia above 60 degrees N from autumn 2001 to spring 2008. Western Siberia is more affected than Central and Eastern Siberia in accordance with climate data, and most events occur in November and April. Ice layers in late winter have an especially negative effect on reindeer as they are already weakened. Yamal Peninsula is located within a transition zone between high and low frequency of events. Refreezing was observed more than once a winter across the entire peninsula during recent years. The southern part experienced refreezing events on average four times each winter. Currently, herders can migrate laterally or north-south, depending on where and when a given event occurs. However, formation of ice crusts in the northern part of the peninsula may become as common as they are now in the southern part. Such a development would further constrain the possibility to migrate on the peninsula.

Sea ice, rain-on-snow and tundra reindeer nomadism in Arctic Russia

Sea ice loss is accelerating in the Barents and Kara Seas (BKS). Assessing potential linkages between sea ice retreat/thinning and the regions ancient and unique social–ecological systems is a pressing task. Tundra nomadism remains a vitally important livelihood for indigenous Nenets and their large reindeer herds. Warming summer air temperatures have been linked to more frequent and sustained summer high-pressure systems over West Siberia, Russia, but not to sea ice retreat. At the same time, autumn/winter rain-on-snow (ROS) events have become more frequent and intense. Here, we review evidence for autumn atmospheric warming and precipitation increases over Arctic coastal lands in proximity to BKS ice loss. Two major ROS events during November 2006 and 2013 led to massive winter reindeer mortality episodes on the Yamal Peninsula. Fieldwork with migratory herders has revealed that the ecological and socio-economic impacts from the catastrophic 2013 event will unfold for years to come. The suggested link between sea ice loss, more frequent and intense ROS events and high reindeer mortality has serious implications for the future of tundra Nenets nomadism.

Training Area Concept in a Two-Phase Biomass Inventory Using Airborne Laser Scanning and RapidEye Satellite Data

This study evaluated the accuracy of boreal forest above-ground biomass (AGB) and volume estimates obtained using airborne laser scanning (ALS) and RapidEye data in a two-phase sampling method. Linear regression-based estimation was employed using an independent validation dataset and the performance was evaluated by assessing the bias and the root mean square error (RMSE). In the phase I, ALS data from 50 field plots were used to predict AGB and volume for the 200 surrogate plots. In the phase II, the ALS-simulated surrogate plots were used as a ground-truth to estimate AGB and volume from the RapidEye data for the study area. The resulting RapidEye models were validated against a separate set of 28 plots. The RapidEye models showed a promising accuracy with a relative RMSE of 19%–20% for both volume and AGB. The evaluated concept of biomass inventory would be useful to support future forest monitoring and decision making for sustainable use of forest resources.

Cumulative Effects of Rapid Land-Cover and Land-Use Changes on the Yamal Peninsula, Russia

The Yamal Peninsula in northwest Siberia is undergoing some of the most rapid land-cover and land-use changes in the Arctic due to a combination of gas development, reindeer herding, and climate change. Unusual geological condi- tions (nutrient-poor sands, massive ground ice and extensive landslides) exacerbate the impacts. These changes will likely increase markedly as transportation corridors are built to transport the gas to market. Understanding the nature, extent, causes and consequences (i.e., the cumulative effects) of the past and ongoing rapid changes on the Yamal is important for effective, long-term decision-making and planning. The cumulative effects to vegetation are the focus of this chapter because the plants are a critical component of the Yamal landscape that support the indigenous Nenets people and their reindeer and also protect the underlying ice-rich permafrost from melting. We are using a combination of ground-based studies (a transect of five loca- tions across the Yamal), remote-sensing studies, and analyses of Nenets land-use activities to develop vegetation-change models that can be used to help anticipate future states of the tundra and how those changes might affect traditional reindeer herding practices and the thermal state of the permafrost. This chapter provides an overview of the approach, some early results, and recommendations for expanding the concept of cumulative-effects analysis to include examining the simultaneous and interactive effects of multiple drivers of change.

Do the classification of areas and distance matter to the assessment results of achieving the treatment targets among type 2 diabetes patients

BackgroundType 2 diabetes is a major health concern all over the world. The prevention of diabetes is important but so is well-balanced diabetes care. Diabetes care can be influenced by individual and neighborhood socio-economic factors and geographical accessibility to health care services. The aim of the study is to find out whether two different area classifications of urban and rural areas give different area-level results of achieving the targets of control and treatment among type 2 diabetes patients exemplified by a Finnish region. The study exploits geo-referenced patient data from a regional primary health care patient database combined with postal code area-level socio-economic variables, digital road data and two grid based classifications of areas: an urban–rural dichotomy and a classification with seven area types.MethodsThe achievement of control and treatment targets were assessed using the patient’s individual laboratory data among 9606 type 2 diabetes patients. It was assessed whether hemoglobin A1c (HbA1c) was controlled and whether the recommended level of HbA1c was achieved in patients by different area classes and as a function of distance. Chi square test and logistic regression analysis were used for testing.ResultsThe study reveals that area-level inequalities exist in the care of type 2 diabetes in a detailed 7-class area classification but if the simple dichotomy of urban and rural is applied differences vanish. The patient’s gender and age, area-level education and the area class they belonged to were associated with achievements of control and treatment targets. Longer distance to health care services was not a barrier to good achievements of control or treatment targets.ConclusionsA more detailed grid-based area classification is better for showing spatial differences in the care of type 2 diabetes patients. Inequalities exist but it would be misleading to state that the differences are simply due to urban or rural location or due to distance. From a planning point of view findings suggest that detailed geo-coded patient information could be utilized more in resourcing and targeting the health care services to find the area-level needs of care and to improve the cost-efficient allocation of resources.

Environmental assessing of reindeer herding in changing landscapes on different scales

This paper is based on an interdisciplinary analysis of reindeer management systems in the subarctic and boreal regions of Fennoscandia. The aim was to develop sustainable strategies for the future utilization of the limited natural resources in these northern regions. Here, reindeer herding is competing with powerful land use forms like forestry, energy conversion, mining, and tourism. Problems arise because the ecological conditions of the natural pastures are basic prerequisites for reindeer husbandry, and because the welfare of the reindeer herders is strongly connected to the socioeconomical circum- stances in the area. Intensive land use can cause a deteoriation of natural pastures and thus, lead to losses in reindeer husbandry. The described invest- tigations took place in the reindeer husbandry region of northern Finland with the two herding districts of Nakkala and Lappi, where reindeer herding traditionally has been the main form of land use. The integrative assessment consisted of comprehensive field studies, applications of remote sensing techniques, data analysis, expert interviews, and modeling. Results are designed to support sustainable decision-making in landscape management.

Publisher Correction to: Background invertebrate herbivory on dwarf birch (Betula glandulosa-nana complex) increases with temperature and precipitation across the tundra biome

The above mentioned article was originally scheduled for publication in the special issue on Ecology of Tundra Arthropods with guest editors Toke T. Høye . Lauren E. Culler. Erroneously, the article was published in Polar Biology, Volume 40, Issue 11, November, 2017. The publisher sincerely apologizes to the guest editors and the authors for the inconvenience caused.

The role of lake size and local phenomena for monitoring ground-fast lake ice

ABSTRACT In this study, we assess the effect of the lake size on the accuracy of a threshold-based classification of ground-fast and floating lake ice from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. For that purpose, two new methods (flood-fill and watershed method) are introduced and the results between the three classification approaches are compared regarding different lake size classes for a study area covering most of the Yamal Peninsula in Western Siberia. The focus is on April, the stage of maximum lake ice thickness, for the years 2016 and 2017. The results indicate that the largest lakes are likely most prone to errors by the threshold classification. The newly introduced methods seem to improve classification results. The results also show differences in fractions of ground-fast lake ice between 2016 and 2017, which might reflect differences in temperatures between the winters with severe impact on wildlife and freshwater fish resources in the region. Patterns of low backscatter responsible for the classification errors in the centre of the lakes were investigated and compared to the optical Sentinel-2 imagery of late-winter. Strong similarities between some patterns in the optical and SAR data were identified. They might be zones of thin ice, but further research is required for clarification of this phenomenon and its causes.