Ecosystem service change caused by climatological and non-climatological drivers: a Swiss case study.

Understanding the drivers of ecosystem change and their effects on ecosystem services are essential for management decisions and verification of progress towards national and international sustainability policies (e.g., Aichi Biodiversity Targets, Sustainable Development Goals). We aim to disentangle spatially the effect of climatological and non-climatological drivers on ecosystem service supply and trends. Therefore, we explored time series of three ecosystem services in Switzerland between 2004 and 2014: carbon dioxide regulation, soil erosion prevention, and air quality regulation. We applied additive models to describe the spatial variation attributed to climatological (i.e., temperature, precipitation and relative sunshine duration) and non-climatological drivers (i.e., random effects representing other spatially structured processes) that may affect ecosystem service change. Obtained results indicated strong influences of climatological drivers on ecosystem service trends in Switzerland. We identified equal contributions of all three climatological drivers on trends of carbon dioxide regulation and soil erosion prevention, while air quality regulation was more strongly influenced by temperature. Additionally, our results showed that climatological and non-climatological drivers affected ecosystem services both negatively and positively, depending on the regions (in particular lower and higher altitudinal areas), drivers, and services assessed. Our findings highlight stronger effects of climatological compared to non-climatological drivers on ecosystem service change in Switzerland. Furthermore, drivers of ecosystem change display a spatial heterogeneity in their influence on ecosystem service trends. We propose an approach building on an additive model to disentangle the effect of climatological and non-climatological drivers on ecosystem service trends. Such analyses should be extended in the future to ecosystem service flow and demand to complete ecosystem service assessments and to demonstrate and communicate more clearly the benefits of ecosystem services for human well-being.

No growth stimulation of Canada's boreal forest under half-century of combined warming and CO2 fertilization.

Considerable evidence exists that current global temperatures are higher than at any time during the past millennium. However, the long-term impacts of rising temperatures and associated shifts in the hydrological cycle on the productivity of ecosystems remain poorly understood for mid to high northern latitudes. Here, we quantify species-specific spatiotemporal variability in terrestrial aboveground biomass stem growth across Canada's boreal forests from 1950 to the present. We use 873 newly developed tree-ring chronologies from Canada's National Forest Inventory, representing an unprecedented degree of sampling standardization for a large-scale dendrochronological study. We find significant regional- and species-related trends in growth, but the positive and negative trends compensate each other to yield no strong overall trend in forest growth when averaged across the Canadian boreal forest. The spatial patterns of growth trends identified in our analysis were to some extent coherent with trends estimated by remote sensing, but there are wide areas where remote-sensing information did not match the forest growth trends. Quantifications of tree growth variability as a function of climate factors and atmospheric CO2 concentration reveal strong negative temperature and positive moisture controls on spatial patterns of tree growth rates, emphasizing the ecological sensitivity to regime shifts in the hydrological cycle. An enhanced dependence of forest growth on soil moisture during the late-20th century coincides with a rapid rise in summer temperatures and occurs despite potential compensating effects from increased atmospheric CO2 concentration.

Variability and evolution of global land surface phenology over the past three decades (1982-2012).

Monitoring land surface phenology (LSP) is important for understanding both the responses and feedbacks of ecosystems to the climate system, and for representing these accurately in terrestrial biosphere models. Moreover, by shedding light on phenological trends at a variety of scales, LSP provides the potential to fill the gap between traditional phenological (field) observations and the large-scale view of global models. In this study, we review and evaluate the variability and evolution of satellite-derived growing season length (GSL) globally and over the past three decades. We used the longest continuous record of Normalized Difference Vegetation Index data available to date at global scale to derive LSP metrics consistently over all vegetated land areas and for the period 1982-2012. We tested GSL, start- and end-of-season metrics (SOS and EOS, respectively) for linear trends as well as for significant trend shifts over the study period. We evaluated trends using global environmental stratification information in place of commonly used land cover maps to avoid circular findings. Our results confirmed an average lengthening of the growing season globally during 1982-2012 - averaging 0.22-0.34 days yr(-1), but with spatially heterogeneous trends. About 13-19% of global land areas displayed significant GSL change, and over 30% of trends occurred in the boreal/alpine biome of the Northern Hemisphere, which showed diverging GSL evolution over the past three decades. Within this biome, the 'Cold and Mesic' environmental zone appeared as an LSP change hotspot. We also examined the relative contribution of SOS and EOS to the overall changes, finding that EOS trends were generally stronger and more prevalent than SOS trends. These findings constitute a step towards the identification of large-scale phenological drivers of vegetated land surfaces, necessary for improving phenological representation in terrestrial biosphere models.

Unusual forest growth decline in boreal North America covaries with the retreat of Arctic sea ice.

The 20th century was a pivotal period at high northern latitudes as it marked the onset of rapid climatic warming brought on by major anthropogenic changes in global atmospheric composition. In parallel, Arctic sea ice extent has been decreasing over the period of available satellite data records. Here, we document how these changes influenced vegetation productivity in adjacent eastern boreal North America. To do this, we used normalized difference vegetation index (NDVI) data, model simulations of net primary productivity (NPP) and tree-ring width measurements covering the last 300 years. Climatic and proxy-climatic data sets were used to explore the relationships between vegetation productivity and Arctic sea ice concentration and extent, and temperatures. Results indicate that an unusually large number of black spruce (Picea mariana) trees entered into a period of growth decline during the late-20th century (62% of sampled trees; n = 724 cross sections of age >70 years). This finding is coherent with evidence encoded in NDVI and simulated NPP data. Analyses of climatic and vegetation productivity relationships indicate that the influence of recent climatic changes in the studied forests has been via the enhanced moisture stress (i.e. greater water demands) and autotrophic respiration amplified by the declining sea ice concentration in Hudson Bay and Hudson Strait. The recent decline strongly contrasts with other growth reduction events that occurred during the 19th century, which were associated with cooling and high sea ice severity. The recent decline of vegetation productivity is the first one to occur under circumstances related to excess heat in a 300-year period, and further culminates with an intensifying wildfire regime in the region. Our results concur with observations from other forest ecosystems about intensifying temperature-driven drought stress and tree mortality with ongoing climatic changes.

Strong contribution of autumn phenology to changes in satellite-derived growing season length estimates across Europe (1982-2011).

Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegetated land surfaces as observed from satellite imagery. LSP plays a key role in characterizing land-surface fluxes, and is central to accurately parameterizing terrestrial biosphere-atmosphere interactions, as well as climate models. In this article, we present an evaluation of Pan-European LSP and its changes over the past 30 years, using the longest continuous record of Normalized Difference Vegetation Index (NDVI) available to date in combination with a landscape-based aggregation scheme. We used indicators of Start-Of-Season, End-Of-Season and Growing Season Length (SOS, EOS and GSL, respectively) for the period 1982-2011 to test for temporal trends in activity of terrestrial vegetation and their spatial distribution. We aggregated pixels into ecologically representative spatial units using the European Landscape Classification (LANMAP) and assessed the relative contribution of spring and autumn phenology. GSL increased significantly by 18-24 days decade(-1) over 18-30% of the land area of Europe, depending on methodology. This trend varied extensively within and between climatic zones and landscape classes. The areas of greatest growing-season lengthening were the Continental and Boreal zones, with hotspots concentrated in southern Fennoscandia, Western Russia and pockets of continental Europe. For the Atlantic and Steppic zones, we found an average shortening of the growing season with hotspots in Western France, the Po valley, and around the Caspian Sea. In many zones, changes in the NDVI-derived end-of-season contributed more to the GSL trend than changes in spring green-up, resulting in asymmetric trends. This underlines the importance of investigating senescence and its underlying processes more closely as a driver of LSP and global change.

Land surface phenology and greenness in Alpine grasslands driven by seasonal snow and meteorological factors.

Snow accumulation and melt have multiple impacts on Land Surface Phenology (LSP) and greenness in Alpine grasslands. Our understanding of these impacts and their interactions with meteorological factors are still limited. In this study, we investigate this topic by analyzing LSP dynamics together with potential drivers, using satellite imagery and other data sources. LSP (start and end of season) and greenness metrics were extracted from time series of vegetation and leaf area index. As explanatory variables we used snow accumulation, snow cover melt date and meteorological factors. We tested for inter-annual co-variation of LSP and greenness metrics with seasonal snow and meteorological metrics across elevations and for four sub-regions of natural grasslands in the Swiss Alps over the period 2003-2014. We found strong positive correlations of snow cover melt date and snow accumulation with the start of season, especially at higher elevation. Autumn temperature was found to be important at the end of season below 2000 m above sea level (m asl), while autumn precipitation was relevant above 2000 m asl, indicating climatic growth limiting factors to be elevation dependent. The effects of snow and meteorological factors on greenness revealed that this metric tends to be influenced by temperatures at high elevations, and by snow melt date at low elevations. Given the high sensitivity of alpine grassland ecosystems, these results suggest that alpine grasslands may be particularly affected by future changes in seasonal snow, to varying degree depending on elevation.

Spatial variation of human influences on grassland biomass on the Qinghai-Tibetan plateau.

An improved understanding of increased human influence on ecosystems is needed for predicting ecosystem processes and sustainable ecosystem management. We studied spatial variation of human influence on grassland ecosystems at two scales across the Qinghai-Tibetan Plateau (QTP), where increased human activities may have led to ecosystem degradation. At the 10 km scale, we mapped human-influenced spatial patterns based on a hypothesis that spatial patterns of biomass that could not be attributed to environmental variables were likely correlated to human activities. In part this hypothesis could be supported via a positive correlation between biomass unexplained by environmental variables and livestock density. At the 500 m scale, using distance to settlements within a radius of 8 km as a proxy of human-influence intensity, we found both negatively human-influenced areas where biomass decreased closer to settlements (regions with higher livestock density) and positively human-influenced areas where biomass increased closer to settlements (regions with lower livestock density). These results suggest complex relationships between livestock grazing and biomass, varying between spatial scales and regions. Grazing may boost biomass production across the whole QTP at the 10 km scale. However, overgrazing may reduce it near settlements at the 500 m scale. Our approach of mapping and understanding human influence on ecosystems at different scales could guide pasture management to protect grassland in vulnerable regions on the QTP and beyond.

Spatial relationship between climatologies and changes in global vegetation activity.

Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982-2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate-associated effects and a spatially correlated field representing the combined influence of other factors, including land-use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large-scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land-cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology).