Juval Cohen

Where do the treeless tundra areas of northern highlands fit in the global biome system : toward an ecologically natural subdivision of the tundra biome

Abstract According to some treatises, arctic and alpine sub‐biomes are ecologically similar, whereas others find them highly dissimilar. Most peculiarly, large areas of northern tundra highlands fall outside of the two recent subdivisions of the tundra biome. We seek an ecologically natural resolution to this long‐standing and far‐reaching problem. We studied broad‐scale patterns in climate and vegetation along the gradient from Siberian tundra via northernmost Fennoscandia to the alpine habitats of European middle‐latitude mountains, as well as explored those patterns within Fennoscandian tundra based on climate–vegetation patterns obtained from a fine‐scale vegetation map. Our analyses reveal that ecologically meaningful January–February snow and thermal conditions differ between different types of tundra. High precipitation and mild winter temperatures prevail on middle‐latitude mountains, low precipitation and usually cold winters prevail on high‐latitude tundra, and Scandinavian mountains show intermediate conditions. Similarly, heath‐like plant communities differ clearly between middle latitude mountains (alpine) and high‐latitude tundra vegetation, including its altitudinal extension on Scandinavian mountains. Conversely, high abundance of snowbeds and large differences in the composition of dwarf shrub heaths distinguish the Scandinavian mountain tundra from its counterparts in Russia and the north Fennoscandian inland. The European tundra areas fall into three ecologically rather homogeneous categories: the arctic tundra, the oroarctic tundra of northern heights and mountains, and the genuinely alpine tundra of middle‐latitude mountains. Attempts to divide the tundra into two sub‐biomes have resulted in major discrepancies and confusions, as the oroarctic areas are included in the arctic tundra in some biogeographic maps and in the alpine tundra in others. Our analyses based on climate and vegetation criteria thus seem to resolve the long‐standing biome delimitation problem, help in consistent characterization of research sites, and create a basis for further biogeographic and ecological research in global tundra environments.

Long-term Impacts of Contrasting Management of Large Ungulates in the Arctic Tundra-Forest Ecotone: Ecosystem Structure and Climate Feedback

The arctic forest-tundra ecotone (FTE) represents a major transition zone between contrasting ecosystems, which can be strongly affected by climatic and biotic factors. Expected northward expansion and encroachment on arctic tundra in response to climate warming may be counteracted by natural and anthropogenic processes such as defoliating insect outbreaks and grazing/browsing regimes. Such natural and anthropogenic changes in land cover can substantially affect FTE dynamics, alter ground albedo (index of the amount of solar energy reflected back into the atmosphere) and provide important feedbacks into the climate system. We took advantage of a naturally occurring contrast between reindeer grazing regimes in a border region between northern Finland and Norway which was recently defoliated by an outbreak of the geometrid moth. We examined ecosystem-wide contrasts between potentially year-round (but mainly summer) grazed (YRG) regions in Finland and mainly winter grazed (WG) regions in Norway. We also used a remotely sensed vegetation index and albedo to quantify effects on local energy balance and potential climate feedbacks. Although differences in soil characteristics and ground vegetation cover were small, we found dramatic differences in the tree layer component of the ecosystem. Regeneration of mountain birch stands appears to have been severely hampered in the YRG regime, by limiting regeneration from basal shoots and reestablishment of individual trees from saplings. This has led to a more open forest structure and a significant 5% increase in spring albedo in the summer grazed compared to the winter grazed regions. This supports recent suggestions that ecosystem processes in the Arctic can significantly influence the climate system, and that such processes must be taken into account when developing climate change scenarios and adaptation strategies.

Observations and Simulation of Multifrequency SAR Data Over a Snow-Covered Boreal Forest

A significant part of the Earth affected by seasonal snow is covered by forest. Moreover, the presence of forest modifies the snow accumulation and its metamorphism during the winter season. Recent studies, which were carried out within the framework of ESAs CoReH2O Phase-A mission, demonstrate that multifrequency SAR data are able to quantify the amount of snow mass on land surfaces and or glaciers. On the other hand, the presence of forest has a significant impact on the propagation of the radar signal, depending on its structure, biomass, water content, and cover fraction. In particular, for dense forest scattering of vegetation strongly hides the signal from snow, and consequently, compromises the sensitivity to snow parameters. Within the development of the missions snow water equivalent (SWE) retrieval algorithm, a method to compensate the vegetation effect, and then to retrieve snow in sparse forested areas, was implemented. The method is based on the development of an e.m. model for simulating the backscattering of a snow-covered vegetated terrain and the availability of some ancillary data about forest characteristics. Model description and validation using real airborne and space-borne SAR data collected over a boreal test site in Finland are presented here. The use of the developed model in the SWE retrieval algorithm is also presented.

The Effect of Boreal Forest Canopy in Satellite Snow Mapping—A Multisensor Analysis

Satellite-based snow-cover monitoring is performed using optical, synthetic aperture radar (SAR), and passivemicrowave sensors. Effects of forest canopy on the observed signal need to be considered with all of these sensor types. Various models describing the interaction of electromagnetic radiation with forest canopy have been developed, but many of these are overly complex with high computational and ancillary data requirements. However, for retrieval purposes, simple models are preferred. This work aims at increasing the understanding of the effect of forest canopy on remote sensing observations of snow-covered terrain for both microwave and optical regimes and at quantifying the capability of simple zeroth-order models in simulating these effects. To achieve these goals, a spatial analysis of optical, SAR, and passive-microwave remote sensing data in the northern boreal forest region was performed. Model parameters for vegetation transmissivity as well as the properties of the underlying surface were optimized by utilizing lidar-ranging- and Landsat-based simplified proxy parameters describing forest canopy closure and stem volume. The results demonstrated that despite using these relatively simple proxies, a zeroth-order model can accurately estimate the extinction of electromagnetic signals in a forest, particularly for passive microwave and optical data. The SAR model successfully estimated the median of the observations, but larger scatter of the observations was reflected by a higher root mean square error and lower correlation between models and observations. Due to both good estimation accuracy and simplicity, the presented models can be considered to be applicable in existing snow retrieval algorithms.

New Snow Water Equivalent Processing System With Improved Resolution Over Europe and its Applications in Hydrology

The presence and amount of snow, given in terms of snow water equivalent (SWE), is an essential physical characteristic influencing climate and hydrological processes. For the recent decades, remote sensing has proven to be a valuable tool for deriving regional and global scale information on SWE. However, determining SWE reliably from remote sensing data for many local-scale applications remains a challenge. Microwave radiometers are currently the best option to determine SWE since they respond to snow depth and density. Further, weather phenomena and solar illumination are not of concern. However, for some purposes the typical spatial resolution of space-borne radiometers (in the order of tens of kilometers) is not sufficient. In this study, the spatial resolution of existing operational SWE products (GlobSnow and H-SAF product portfolios) is improved by performing assimilation of ground truth observations of snow depth and space borne derived SWE estimates in a resolution grid of 0.05° × 0.05° (approximately 5 km × 5 km). Some modifications to the SWE algorithm and the applied auxiliary data (such as an improved forest stem volume map) are introduced. We will present how the improved resolution enhances spatial details in the retrieved SWE, while the validation results show that in terms of accuracy, the new product is on similar level than the existing operational products. Finally, the gained new SWE estimates are ingested into the HOPS hydrological model in the Ounasjoki river basin. The results indicate that simulation of snow melt driven river discharge can be improved by ingesting the retrieved SWE data into a hydrological model.

Long term changes in Northern hemisphere snow cover from SWE timeseries constrained with SE data

Reliable information on snow cover across the Northern Hemisphere and Arctic and sub-Arctic regions is needed for climate monitoring, for understanding the Arctic climate system, and for the evaluation of the role of snow cover and its feedback in climate models. In addition to being of significant interest for climatological investigations, reliable information on snow cover is of high value for the purpose of hydrological forecasting and numerical weather prediction. Terrestrial snow covers up to 50 million km2 of the Northern Hemisphere in winter and is characterized by high spatial and temporal variability. Making satellite observations the only means for providing timely and complete observations of the global snow cover.

Assessing global satellite-based snow water equivalent datasets in ESA SnowPEx project

There is a significant difference in SWE retrieval performance between the different satellite-based products. The assessment using the Russian and Finnish snow transect data covers an extremely large and varied geographical region and spans a total of ten years (2002-2011). Additionally, the reference data are well suited for assessing coarse resolution data, as they are not point-wise measurements but distributed measurements from the snow transects or snow courses.

Hydrological applications of super resolution SWE processing system over Europe

Reliable global and regional scale SWE maps can be calculated by the assimilation of space borne derived SWE estimates and ground based SD observations. The spatial resolution of these products is ~25 km per pixel which is good enough for climate research but for hydrology a higher resolution is often optimal. A regional SWE processing system with nominal resolution of ~ 5 km per pixel over Europe is described in this paper. In addition the validation results show that the sensitivity to SWE is on the same level as with the lower resolution products. SWE data are also assimilated with HOPS hydrological model and the results show an improvement in river discharge estimates.

On the estimate of the microwave shadowing effect on sparse boreal forests

Different researches were addressed to the assessment of the boreal forest environment using active microwave remote sensing. Some of these activities were also devoted to estimate the ground parameters under the forest (i.e. soil moisture, snow mass) and, in order to understand the complex mechanisms which govern the radar backscattering, different electromagnetic models were developed for simulating the boreal scenario. An improvement of these models, for better characterizing the sparse forests, also considered the effect of shadow induced by the trees. Besides the computation of the attenuation caused by shadow on ground backscattering, the first needed parameter was the quantification of the percentage of the pixel affected by shadow. The estimation of this parameter can be obtained from high resolution optical images which are not always available at global scale. An alternative semi- empirical method based on 3D CAD modelling and ancillary information, which allow to quantify the amount of the shaded area is presented in the paper. Different forest profiles, height and densities and different geometry of observation were considered, and semi-empirical relationships between shadow area extension and these parameters were founded. The effect of electromagnetic shadowing was also quantified by performing model simulations. Finally a validation of the method was achieved by using high-resolution data collected from optical sensors in a forested area of Finland.