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• Global warming is a statistically confirmed long-term phenomenon. • Somewhat surprisingly, its most visible consequence is: – not the warming itself but – the increased climate variability. • In this talk, we explain why increased climate variability is more visible than the global warming itself. • In this explanation, use general system theory ideas. A Simplified System-... Towards the Second..

Optimal Sensor Placement in Environmental Research: Designing a Sensor Network under Uncertainty

Abstract. One of our main challenges in meteorology and environment research is that in many important remote areas, sensor coverage is sparse, leaving us with numerous blind spots. Placement and maintenance of sensors in these areas are expensive. It is therefore desirable to find out how, within a given budget, we can design a sensor network are important activities was developing reasonable techniques for sensor that would provide us with the largest amount of useful information while minimizing the size of the “blind spot ” areas which is not covered by the sensors. This problem is very difficult even to formulate in precise terms because of the huge uncertainty. There are two important aspects of this problem: (1) how to best distribute the sensors over the large area, and (2) what is the best location of each sensor in the corresponding zone. There is some researcj on the first aspect of the problem. In this paper, we illustrate the second aspect of the problem, on the example of optimal selection of locations for the Eddy towers, an important micrometeorological instrument

Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling

The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH4) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH4 fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH4 fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH4 fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH4 fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km2 domain around the tower and the footprint-weighted mean) was between mid51mid% and mid18mid% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content

Water, Climate, and Social Change in a Fragile Landscape

We present here and in the companion papers an analysis of sustainability in the Middle Rio Grande region of the U.S.-Mexico border and propose an interdisciplinary research agenda focused on the coupled human and natural dimensions of water resources sustainability in the face of climate and social change in an international border region. Key threats to water sustainability in the Middle Rio Grande River region include: (1) increasing salinization of surface and ground water, (2) increasing water demand from a growing population in the El Paso/Ciudad Juarez area on top of an already high base demand from irrigated agriculture, (3) water quality impacts from agricultural, municipal, and industrial discharges to the river, (4) changing regional climate that portends increased frequency and intensity of droughts interspersed with more intensive rainfall and flooding events, and (5) disparate water planning and management systems between different states in the U.S. and between the U.S. and Mexico. In addition to these challenges, there is an increasing demand from a significant regional population who is (and has been historically) underserved in terms of access to affordable potable water. To address these challenges to water resources sustainability, we have focused on: (1) the determinants of resilience and transformability in an ecological/social setting on an international border and how they can be measured and predicted; and (2) the drivers of change ... what are they (climate, social, etc.) and how are they impacting the coupled human and natural dimensions of water sustainability on the border? To tackle these challenges, we propose a research agenda based on a complex systems approach that focuses on the linkages and feedbacks of the natural, built/managed, and social dimensions of the surface and groundwater budget of the region. The approach that we propose incorporates elements of systems analysis, complexity science, and the use of modeling tools such as scenario planning and back-casting to link the quantitative with the qualitative. This approach is unique for our region, as are our bi-national focus and our conceptualization of water capital . In particular, the concept of water capital provides the basis for a new interdisciplinary paradigm that integrates social, economic, and natural sectors within a systems framework in order to understand and characterize water resources sustainability. This proposed approach would not only provide a framework for water sustainability decision making for our bi-national region at the local, state, and federal levels, but could serve as a model for similar border regions and/or international rivers in arid and semi-arid regions in the Middle East, Africa, Asia, and Latin America

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes

Warming experiments elucidate the drivers of observed directional changes in tundra vegetation

Few studies have clearly linked long-term monitoring with insitu experiments to clarify potential drivers of observed change at a given site. This is especially necessary when findings from a site are applied to a much broader geographic area. Here, we document vegetation change at Barrow and Atqasuk, Alaska, occurring naturally and due to experimental warming over nearly two decades. An examination of plant cover, canopy height, and community indices showed more significant differences between years than due to experimental warming. However, changes with warming were more consistent than changes between years and were cumulative in many cases. Most cases of directional change observed in the control plots over time corresponded with a directional change in response to experimental warming. These included increases in canopy height and decreases in lichen cover. Experimental warming resulted in additional increases in evergreen shrub cover and decreases in diversity and bryophyte cover. This study suggests that the directional changes occurring at the sites are primarily due to warming and indicates that further changes are likely in the next two decades if the regional warming trend continues. These findings provide an example of the utility of coupling insitu experiments with long-term monitoring to accurately document vegetation change in response to global change and to identify the underlying mechanisms driving observed changes