Social Indicators for Arctic Mining

This paper reviews and assesses the state of the data to describe and monitor mining trends in the pan-Arctic. It constructs a mining index and discusses its value as a social impact indicator and discusses drivers of change in Arctic mining. The widely available measures of mineral production and value are poor proxies for economic effects on Arctic communities. Trends in mining activity can be characterized as stasis or decline in mature regions of the Arctic, with strong growth in the frontier regions. World prices and the availability of large, undiscovered and untapped resources with favorable access and low political risk are the biggest drivers for Arctic mining, while climate change is a minor and locally variable factor. Historical data on mineral production and value is unavailable in electronic format for much of the Arctic, specifically Scandinavia and Russia; completing the historical record back to 1980 will require work with paper archives. The most critically needed improvement in data collection and reporting is to develop comparable measures of employment: the eight Arctic countries each use different definitions of employment, and different methodologies to collect the data. Furthermore, many countries do not report employment by county and industry, so the Arctic share of mining employment cannot be identified. More work needs to be done to develop indicator measures for ecosystem service flows. More work also needs to be done developing conceptual models of effects of mining activities on fate control, cultural continuity and ties to nature for local Arctic communities

Climate Change – Refining the Impacts for Ireland: STRIVE Report (2001-CD-C3-M1) ISBN: 978-1-84095-297-1

International Context: As a mid-latitude country Ireland can expect its future temperature changes to mirror quite closely those of the globe as a whole. Best estimates of global temperature change by the end of the present century are currently in the region 1.8–4.0°C1. Regional Context: Weighted Ensemble Downscaling from Global Climate Models Global climate models (GCMs) have greatly improved in reliability and resolution as computing power has increased and better inputs from earth observation have become available. Despite this, they remain too coarse in terms of their grid size to enable climate scenarios at the scale necessary for impact analysis to be achieved. This study employs a statistical downscaling approach to overcome these difficulties and also to provide new information on model uncertainty with a view to reducing uncertainty in key sectors such as water resource management, agriculture and biodiversity

ASSESSING THE RELATIVE INFLUENCES OF ABIOTIC AND BIOTIC FACTORS ON A SPECIES’ DISTRIBUTION USING PSEUDO-ABSENCE AND FUNCTIONAL TRAIT DATA: A CASE STUDY WITH THE AMERICAN EEL (Anguilla rostrata)

Species’ distributions are influenced by abiotic and biotic factors but direct comparison of their relative importance is difficult, particularly when working with complex, multi-species datasets. Here, we present a flexible method to compare abiotic and biotic influences at common scales. First, data representing abiotic and biotic factors are collected using a combination of geographic information system, remotely sensed, and species’ functional trait data. Next, the relative influences of each predictor variable on the occurrence of a focal species are compared. Specifically, ‘sample’ data from sites of known occurrence are compared with ‘background’ data (i.e. pseudo-absence data collected at sites where occurrence is unknown, combined with sample data). Predictor variables that may have the strongest influence on the focal species are identified as those where sample data are clearly distinct from the corresponding background distribution. To demonstrate the method, effects of hydrology, physical habitat, and co-occurring fish functional traits are assessed relative to the contemporary (1950 – 1990) distribution of the American Eel (Anguilla rostrata) in six Mid-Atlantic (USA) rivers. We find that Eel distribution has likely been influenced by the functional characteristics of co-occurring fishes and by local dam density, but not by other physical habitat or hydrologic factors

Winners and Losers: Climate Change Impacts on Biodiversity in Ireland

The climate envelope modelling described in this report represents a staged investigation into the possible impacts of climate change on the nature conservation resources of Ireland. It represents a significant piece of original research applying state-ofthe- art methods for the first time in Ireland, and is an important step in trying to understand the complex interactions between climate, climate change, and species and habitats across the island. The work is one part of the wider research programme Co-ordination, Communication and Adaptation for Climate Change in Ireland: an Integrated Approach (COCOADAPT) funded by the Environmental Protection Agency (EPA)

Increasing the resilience of the Australian alpine flora to climate change

 The alpine region around Australia’s highest mountain, Mt Kosciuszko, is part of one of the three most at risk ecosystems in Australia from climate change. With higher temperatures and decreased precipitation, snow cover is already declining with even greater reductions predicted in the short to medium term (2020 to 2050). Consequently the distribution of many native plants and animals may contract, while the distribution of weeds and feral animals may expand. Wildfires in the region are also likely to be more frequent and intense. To contribute to our understanding of how changes in the environment alter plant composition and ecological process, we conducted a series of functional trait analyses of existing composition datasets. We collected trait data in the field for 220 species including canopy height, leaf area, leaf dry matter content and specific leaf area (SLA). Variation in traits among the alpine flora was not related to species distributional ranges. Traits were strongly associated with growth forms, with shrubs often taller than herbs and graminoids, but often had small, tough, long-lasting leaves. Species traits were combined with relative cover values to calculate community trait weighted means, a commonly used measure of functional diversity. Functional diversity varied with altitude/duration of snow cover. For example, shrubs which are taller with small tough leaves dominated lower altitude summits, while at higher altitude summits, large, soft leaved herbs and graminoids dominated. Late lying snowpatches areas with short growing seasons were dominated by low growing herbs and graminoids with small leaves while areas with longer growing seasons were dominated by herbs and graminoids that were taller and had larger leaves. Recovery from fire differed among plant communities. The composition and functional diversity of recovering tall alpine herbfield is trending towards that of equivalent unburnt sites, while burnt windswept feldmark was colonised by graminoids and herbs that are often found in tall alpine herbfield species, with limited shrub recovery in the first nine years post fire. Grazing by feral hares had no effect on composition or functional diversity, while vegetation recovering from cattle grazing showed clear changes in composition and functional diversity even 43 years later. Prioritising management for this high value conservation region, therefore, involves enhancing resilience by minimising existing threats, particularly those from fire, weeds and hard-hooved grazing animals which will be exacerbate by climate change.Please cite as: Pickering, C, & Venn, S, 2013 Increasing the resilience of the Australian flora to climate change and associated threats: a plant functional traits approach National Climate Change Adaptation Research Facility, Gold Coast, pp. 94 Abstract The alpine region around Australia’s highest mountain, Mt Kosciuszko, is part of one of the three most at risk ecosystems in Australia from climate change. With higher temperatures and decreased precipitation, snow cover is already declining with even greater reductions predicted in the short to medium term (2020 to 2050). Consequently the distribution of many native plants and animals may contract, while the distribution of weeds and feral animals may expand. Wildfires in the region are also likely to be more frequent and intense. To contribute to our understanding of how changes in the environment alter plant composition and ecological process, we conducted a series of functional trait analyses of existing composition datasets. We collected trait data in the field for 220 species including canopy height, leaf area, leaf dry matter content and specific leaf area (SLA). Variation in traits among the alpine flora was not related to species distributional ranges. Traits were strongly associated with growth forms, with shrubs often taller than herbs and graminoids, but often had small, tough, long-lasting leaves. Species traits were combined with relative cover values to calculate community trait weighted means, a commonly used measure of functional diversity. Functional diversity varied with altitude/duration of snow cover. For example, shrubs which are taller with small tough leaves dominated lower altitude summits, while at higher altitude summits, large, soft leaved herbs and graminoids dominated. Late lying snowpatches areas with short growing seasons were dominated by low growing herbs and graminoids with small leaves while areas with longer growing seasons were dominated by herbs and graminoids that were taller and had larger leaves. Recovery from fire differed among plant communities. The composition and functional diversity of recovering tall alpine herbfield is trending towards that of equivalent unburnt sites, while burnt windswept feldmark was colonised by graminoids and herbs that are often found in tall alpine herbfield species, with limited shrub recovery in the first nine years post fire. Grazing by feral hares had no effect on composition or functional diversity, while vegetation recovering from cattle grazing showed clear changes in composition and functional diversity even 43 years later. Prioritising management for this high value conservation region, therefore, involves enhancing resilience by minimising existing threats, particularly those from fire, weeds and hard-hooved grazing animals which will be exacerbate by climate change

Bridging structure and function in semi-arid ecosystems by integrating remote sensing and ground based measurements

The Southwestern US is projected to continue the current significant warming trend, with increased variability in the timing and magnitude of rainfall events. The effects of these changes in climate are already evident in the form of multi-year droughts which have resulted in the widespread mortality of woody vegetation across the region. Therefore, the need to monitor and model forest mortality and carbon dynamics at the landscape and regional scale is an essential component of regional and global climate mitigation strategies, and critical if we are to understand how the imminent state transitions taking place in forests globally will affect climate forcing and feedbacks. Remote sensing offers the only solution to multitemporal regional observation, yet many challenges exist with employing modern remote sensing solutions in highly stressed vegetation characteristic of semi-arid biomes, making one of the most expansive biomes on the globe also one of the most difficult to accu- rately monitor and model. The goal of this research was to investigate how changes in the structure of semi-arid woodlands following forest mortality impacts ecosystem function, and to determine how this question can be addressed using remotely sensed data sets. I focused primarily on Pinus edulis and Juniperous monosperma (piñon-juniper) woodlands, and took advantage of an existing manipulation experiment where mortality was imposed on all of the large piñon (¡ 7 cm dbh) in a 4 ha PJ woodland in 2009 and the ecosystem functional responses have been quantified using eddy covariance. A nearby intact PJ woodland, also instrumented with eddy covariance, was used as a control for this experiment. I tested the ability of high resolution remote sensing data to mechanistically describe the patterns in overstory mortality and understory green-up in this manipulated woodland by comparing it to the intact woodland, and observed the heterogeneous response of the understory as a function of cover type. I also investigated the relationship between changes in soil water content and the greenness of the canopy, noting that in the disturbed woodland, I observed a decoupling between how the canopy was measured remotely (e.g., via vegetation indices, VI) and photosynthesis. This is significant in that it potentially represents a significant source of error in using existing light use efficiency models of carbon uptake in these disturbed woodlands. This research also suggested that leveraging remote sensing data which measures in the red-edge portion of reflected light can provide increased sensitivity to the low leaf area, ephemeral pulses of greenup that were identified in the disturbed woodland, post-canopy mortality. Given these findings, I developed a hierarchy of simple linear models to test how well vegetation indices acquired through different spatial resolution sensors (Land- sat and RapidEye) were able to predict carbon uptake in both intact and disturbed piñon-juniper woodlands. The vegetation indices used were a moisture sensitive VI, and a red-edge leveraging VI from these sensors, and I compared estimates of carbon uptake derived from these models to the Gross Primary Productivity estimated from tower-based eddy covariance at both the manipulated and intact piñon-juniper sites. I determined that the red-edge VI and the moisture sensitive VI both constrained uncertainty associated with carbon uptake, but that the variability in satellite view angle from scene to scene can impose a significant amount of noise in sparse canopy ecosystems. Finally, given the extent and prevalence of J. monosperma across the region, and its complex growth morphology, I tested the ability of aerial lidar to quantify the biomass of juniper. In this simplified case study, I developed a method- ology to relate the volume of canopy measured via lidar to the equivalent stem area at the root crown. By working in a single species ecosystem, I circumvented many challenges associated with driving allometries remotely, but also present a work-flow that I intend to adapt to more complex systems, namely piñon-juniper woodlands. Together, this work describes and addresses existing challenges with respect to us- ing remote sensing to understand both the structure and function of piñon-juniper woodlands, and how it changes in response to widespread piñon mortality. It provides several new techniques to mitigate the difficulties associated with monitoring mortality / recovery dynamics, predicting canopy function, and determining ecosystem state parameters in these complex, sensitive biomes

Influence of topography and moisture and nutrient availability on green alder function on the low arctic tundra, NT

The Arctic has warmed by at least 3°C over the past 50 years and this rapid warming is expected to continue. Climate warming is driving the proliferation of shrubs across the tundra biome with implications for energy balance, climate, hydrology, nutrient cycling, and biodiversity. Changes in tundra plant water use attributable to shrub expansion are predicted to increase evapotranspirative water loss which may amplify local warming and reduce run-off. However, little is known about the extent to which shrubs will enhance evapotranspirative water loss in these systems. Direct measures of shrub water use are needed to accurately predict evapotranspiration rates and the associated hydrological and energetic impacts. In addition, it is crucial that we understand the abiotic factors that drive shrub distribution and physiological function to forecast further changes in tundra ecosystem function. Shrubs are expanding in areas that have a higher potential of accumulating moisture, such as drainage channels and hill slopes. Shrub expansion may be limited by variation in water and nutrient availability across topographic gradients. Nevertheless, the associations between shrub function and abiotic limitations remain understudied. To address these knowledge gaps, we measured sap flow, stem water potential, and a range of functional traits of green alder (Alnus viridis) shrubs and quantified water and nutrient availability in shrub patches on the low arctic tundra of the Northwest Territories. Frost table depth was a significant negative driver of sap flow and underlies decreased surface water availability with thaw. This was further supported through significantly lower stem water potential values as the growing season progressed. Shrubs in upslope locations had significantly lower water potentials relative to shrubs in downslope locations, demonstrating topographic variation in shrub water status. Shrubs in channels and at the tops of patch slopes significantly differed in leaf functional traits representing leaf investment, productivity, and water use efficiency. Channel shrubs reflected traits associated with higher resource availability and productivity whereas shrubs at the tops of patches reflected the opposite. This work provides insight into the abiotic drivers of tall shrub water use and productivity, both of which will be essential for predicting ecosystem function

Projected climate change impacts on upland heaths in Ireland

Heathland habitats in Ireland occur primarily in an oceanic setting which is strongly influenced by changes in the climate. As a consequence of the oceanic environment, Ireland has a high proportion of the northern Atlantic wet and alpine and boreal heaths of high conservation value within Europe. Future climate change is widely expected to place additional pressure on these systems. Seven bioclimatic envelope modelling techniques implemented in the BIOMOD modelling framework were used to model Wet and Alpine and Boreal heath distributions in Ireland. The 1961 to 1990 baseline models closely matched the observed distribution, and emphasise the strong dependency on climate. Mean winter precipitation, mean winter temperature and elevation were found to be important model components. The fitted models discrimination ability was assessed using the area under the curve (range 0.874 to 0.929, Wet heath; 0.858 to 0.936, Alpine and Boreal heath) of a receiver operating characteristic plot; the true skill statistic (range 0.648 to 0.713, Wet heath; 0.666 to 0.737, Alpine and Boreal heath); and Cohen’s kappa (range 0.652 to 0.714, Wet heath; 0.641 to 0.738, Alpine and Boreal heath). A BIOMOD ensemble prediction from all the models was used to project changes based on a climate change scenario for 2031 to 2060 dynamically downscaled from the Hadley Centre HadCM3-Q16 global climate model. The climate change projections for the individual models change markedly from the consistent baseline predictions. Projected climate space losses (gains) from the BIOMOD consensus model are -40.84% (limited expansion) and -10.38% (full expansion) for Wet heath; and -18.31% (limited expansion) and +28.17% (full expansion) for Alpine and Boreal heath. Although the consensus models project gains in climate space for both habitats in other parts of the country, new habitat formation in these areas is unlikely as current (and hence near future) land use and other conditions are not likely to favour expansion