Aldabra Atoll has the largest population of giant tortoises (Aldabrachelys gigantea) in the world... more Aldabra Atoll has the largest population of giant tortoises (Aldabrachelys gigantea) in the world. As such an important biological resource, it is necessary to understand how the effects of climate change will impact this keystone species; in particular the frequency of drought, which is likely to affect tortoise habitat. To assess whether drought frequency has changed over the last 50 years on Aldabra, we calculated the standardized precipitation index (SPI) to identify drought periods using monthly rainfall data collected during 1969–2013. We found that drought frequency has increased to more than six drought months per year today compared with about two months per year in the 1970s (t = 2.884, p = 0.006). We used MODIS normalized difference vegetation index (NDVI) as a proxy for vegetation activity, to determine how vegetation has responded to the changing drought frequency between 2000 and 2013. We found that Aldabra's vegetation is highly responsive to changes in rainfall: anomalies in long-term mean monthly NDVI across Aldabra were found to decrease below the mean during most drought periods and increase above the mean during most non-drought periods. To investigate the response of tortoise habitat to rainfall, we extracted mean NDVI anomalies for three key habitat types. Open mixed scrub and grasslands, the preferred habitat of tortoises, showed the greatest decrease in vegetation activity during drought periods, and the greatest increase in average greenness during non-drought periods. Recent analysis has shown vegetation changes on Aldabra in recent decades. If these changes are caused by decreased precipitation, then the increased frequency of drought could impact the tortoise population, in both the short and long term, by limiting the quality and quantity of forage and/or shade availability within favoured habitats, and by changing the habitat composition across the atoll.
An increasing demand for full spatio-temporal coverage of soil information drives the growing use... more An increasing demand for full spatio-temporal coverage of soil information drives the growing use of soil spectroscopy. Soil spectroscopy application performed under laboratory conditions or in-field studies in semi-arid areas have shown promising results. However, when acquiring data in temperate zones, limitations by vegetation-free coverage, variation in soil moisture and management are driving coherent spatio-temporal data collection. This study explores the use of multi-temporal imaging spectroscopy data to increase the total mapping area of bare soils in a heterogeneous agricultural landscape. Spectrally and spatially high-resolution data from the Airborne Prism Experiment (APEX) were collected in September 2013, April 2014 and April 2015. Bare soils in all acquisitions were identified. To eliminate short-term differences in soil moisture and soil surface roughness, the empirical line method was used to calibrate the reflectance values of the singular images (2013 and 2015) towards the singular image with most bare soil pixels (2014). Difference indicators show that the calibration was successful (decrease in root mean square difference and angle difference, increase in R 2 and gain and offset close to one and zero). Finally, the multi-temporal composite image contained more than double the amount of bare soil pixels as compared to a singular acquisition. Summary statistics show that reflectance values of the multi-temporal composite approximate the single image data of 2014 (mean and standard deviation of 2014: 24.2 ± 8.9 vs. 24.0 ± 9.5 for the multi-temporal composite of 2013, 2014 and 2015). This indicates that global differences in soil moisture and land management have been corrected for. As a result, an improved spatial representation of soil parameters can be retrieved from the composite data. Spatial distribution of the correction factors and analysis of the spatial variability of all images, however, indicate that non-linear, short-term differences like variation in soil moisture and land management largely influence the result of the multi-temporal composite. Quantification and attribution of those factors will be required in the future to allow correcting for them.
—Agroecosystems play an important role in providing economic and ecosystem services, which direct... more —Agroecosystems play an important role in providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding, and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional land management model (LMM) to improve the assessment of spatially explicit nutrient balances for agroecosystems. Remotely sensed data and an optimized parameter set contributed to an improved LMM output, allowing for a better land allocation within the model. The best input parameter combination was based on two different land cover classifications with overall accuracies of 98%, improving the land allocation performance compared with using nonspatially explicit input. We conclude that the combined use of remote sensing data and the LMM has the potential to provide valuable guidance for farm practices. It further helps to generate a spatial description of farm-level nutrient balance, a crucial ability when choosing policy options related to sustainable management of agricultural soils. Index Terms—Agroecosystems, land allocation, land use classification , nutrient balancing, remote sensing (RS).
Considerable evidence exists that current global temperatures are higher than at any time during ... more 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.
Abstract–Continuous global time series of vegetation indices, which are available since early 198... more Abstract–Continuous global time series of vegetation indices, which are available since early 1980s, are of great value to detect changes in vegetation status at large spatial scales. Most change detection methods, however, assume a fixed change trajectory–defined by the start and end of the time series–and a linear or monotonic trend. Here, we apply a change detection method which detects abrupt changes within the time series. This Breaks For Additive Season and Trend (BFAST) approach showed that large parts of the world are ...
Description BFAST integrates the decomposition of time series into trend, seasonal, and remainder... more Description BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt changes within the trend and seasonal components. BFAST can be used to analyze different types of satellite image time series and can be applied to other disciplines dealing with seasonal or non-seasonal time series, such as hydrology, climatology, and econometrics. The algorithm can be extended to label detected changes with information on the parameters of the fitted ...
Monitoring land surface phenology (LSP) is important for understanding both the responses and fee... more 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.
EGU General Assembly 2010, held 2-7 May, 2010 in Vienna, Austria, p. 14800, May 1, 2010
Maintaining and enhancing the quality of land is of major importance to sustain future production... more Maintaining and enhancing the quality of land is of major importance to sustain future production capacity for food and other agriculture based products like fibers and wood, and for maintaining ecosystems services, including below and above ground biodiversity, provision of soil water and sequestration of carbon. Deterioration of this production base will be detrimental to the provision of the foreseen dramatic increase in human needs for goods and services. For this reason, land degradation, defined as a long ...
The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial... more The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial ecosystems and their role in carbon cycle. We used a combination of the most recent NDVI and model-based NPP estimates (from five models of the TRENDY project) for the period 1982–2012, to study the role of terrestrial ecosystems in carbon cycle under the prevailing climate conditions. We found that 80% and 67% of the global land area showed positive NPP and NDVI values, respectively, for this period. The global NPP was estimated to be about 63 Pg C¨y´1 , with an increase of 0.214 Pg C¨y´1¨y´1. Similarly, the global mean NDVI was estimated to be 0.33, with an increasing trend of 0.00041 y ´1. The spatial patterns of NPP and NDVI demonstrated substantial variability, especially at the regional level, for most part of the globe. However, on temporal scale, both global NPP and NDVI showed a corresponding pattern of increase (decrease) for the duration of this study except for few years (e.g., 1990 and 1995–1998). Generally, the Northern Hemisphere showed stronger NDVI and NPP increasing trends over time compared to the Southern Hemisphere; however, NDVI showed larger trends in Temperate regions while NPP showed larger trends in Boreal regions. Among the five models, the maximum and minimum NPP were produced by JULES (72.4 Pg C¨y´1) and LPJ (53.72 Pg C¨y´1) models, respectively. At latitudinal level, the NDVI and NPP ranges were ~0.035 y ´1 to ~´0.016 y ´1 and ~0.10 Pg C¨y´1¨y´1 to ~´0.047 Pg C¨y´1¨y´1 , respectively. Overall, the results of this study suggest that the modeled NPP generally correspond to the NDVI trends in the temporal dimension. The significant variability in spatial patterns of NPP and NDVI trends points to a need for research to understand the causes of these discrepancies between molded and observed ecosystem dynamics, and the carbon cycle.
Evaluating vegetation phenology is crucial for a better understanding of the effects of climate c... more Evaluating vegetation phenology is crucial for a better understanding of the effects of climate change on the terrestrial ecosystem. The scientific community has used various vegetation index data sets from different sensors to quantify vegetation phenology from regional to global scales. The normalized difference vegetation index (NDVI) related to photosynthetic activities is the most widely used index. Recently, a number of published articles have used the Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index (MTCI) to measure vegetation phenology. MTCI can closely represent the red-edge position (REP). Unlike NDVI, MTCI is more sensitive to high values of chlorophyll content. However, the consistency of vegetation phenological metrics derived from MTCI and NDVI needs to be further explored. This study compared two phenological metrics, i.e. onset of greenness (OG) and end of senescence (ES), extracted from MERIS MTCI data and Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) first generation NDVI (NDVIg) data, which has the longest time records, at nine regions in China from 2003 to 2006. The results showed that the differences of OG and ES vary between different vegetation types, regions, and years, although both NDVI and MTCI time series capture the growth patterns well for most vegetation types. Compared to ES, the OG estimates are more consistent. NDVI yields in general later ES estimates than MTCI.
The biosphere plays a large role in the global carbon cycle and as such in the climate system. Th... more The biosphere plays a large role in the global carbon cycle and as such in the climate system. The other way around, climatologies constrain vegetation growth. This feedback mechanism expresses itself in the phenology of the land surface (LSP) and is a crucial but uncertain component in Earth system models. An important defi- ciency is the decomposition of the natural and the anthropogenic signals in this land-atmosphere carbon cycle.
We studied the changes in yearly vegetation activity and LSP met- rics, and linked these to changes in potential climatological growth constraints (temperature, precipi- tation, radiation), both at global scale and in more detail for Swit- zerland. With this, we aim at im- proved attribution of detected bio- spheric changes to underlying drivers, both climatological and from other origin.
Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegeta... more 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 paper 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 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.
Imaging spectroscopy allows us to analyze the abundances of different materials on the glacier su... more Imaging spectroscopy allows us to analyze the abundances of different materials on the glacier surface on the pixel scale. These abundances are important information to improve the understanding of the spatial distribution of glacier ablation, which appears to depend strongly on surface albedo.
Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegeta... more Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegetated land surfaces as observed from satellite imagery. As such, LSP plays a key role in characterizing land surface fluxes, understanding the terrestrial carbon budget and the response of terrestrial ecosystems to environmental change. Various studies have highlighted significant increases in vegetation activity over time (i.e. greening) over Europe in recent decades, associated both with climatic changes and with large-scale human interventions, including land-use change. In this study we assess trends in LSP in Pan-Europe over the last 30 years. We found significant shifts in NDVI-derived GSL over the last 30 years for approx. 18-30% of terrestrial Pan-Europe, with an average GS lengthening quantified at 0.63-0.82 days/year. The LANMAP stratification reveals large spatial variation in LSP trends, both between climatic zones and landscape classes (Figures 3 and 4). Hotspot areas for GS lengthening are the continental and boreal climatic zones, whereas negative GSL trends occur mostly in Western France, the Italian Po valley and West of the Caspian Sea. Results reveal an assymetrically strong role of EOS delay/advance on the overall shifts found.
The 20th century was a pivotal period at high northern latitudes as it marked the onset of a rapi... more The 20th century was a pivotal period at high northern latitudes as it marked the onset of a 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 record. 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 datasets were used to explore the relationships between vegetation productivity and Arctic sea ice concentration and extent, and temperatures. Results indicate that an unusually large amount of black spruce (Picea mariana) trees entered into a period of growth decline during the late 20th century (68% 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 the 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 43 drought stress and tree mortality with ongoing climatic changes.
Consumer-grade digital cameras are recognized as a cost-effective method of monitoring plant heal... more Consumer-grade digital cameras are recognized as a cost-effective method of monitoring plant healthand phenology. The capacity to use these cameras to produce time series information contributes to abetter understanding of relationships between environmental conditions, vegetation health, and produc-tivity. In this study we evaluate the use of consumer grade digital cameras modified to capture infraredwavelengths for monitoring vegetation. The use of infrared imagery is very common in satellite remotesensing, while most current near sensing studies are limited to visible wavelengths only. The use ofinfrared-visible observations is theoretically superior over the use of just visible observation due to thestrong contrast between infrared and visible reflection of vegetation, the high correlation of the threevisible bands and the possibilities to use spectral indices like the Normalized Difference Vegetation Index. This paper presents two experiments: the first study compares infrared modified and true color camerasto detect seasonal development of understory plants species in a forest; the second is aimed at evaluation of spectrometer and camera data collected during a laboratory plant stress experiment. The main goal ofthe experiments is to evaluate the utility of infrared modified cameras for the monitoring of plant healthand phenology. Results show that infrared converted cameras perform less than standard color cameras in a monitoringsetting. Comparison of the infrared camera response to spectrometer data points at limits in dynamicrange, and poor band separation as the main weaknesses of converted consumer cameras. Our resultssupport the use of standard color cameras as simple and affordable tools for the monitoring of plant stressand phenology.
Consumer-grade cameras (CGC) have advantageous characteristics for close-range vegetation monitor... more Consumer-grade cameras (CGC) have advantageous characteristics for close-range vegetation monitoring, although there are limitations for many scientific applications. We discuss four categories of constraints, as well as potential modifications for effective vegetation monitoring.
Aldabra Atoll has the largest population of giant tortoises (Aldabrachelys gigantea) in the world... more Aldabra Atoll has the largest population of giant tortoises (Aldabrachelys gigantea) in the world. As such an important biological resource, it is necessary to understand how the effects of climate change will impact this keystone species; in particular the frequency of drought, which is likely to affect tortoise habitat. To assess whether drought frequency has changed over the last 50 years on Aldabra, we calculated the standardized precipitation index (SPI) to identify drought periods using monthly rainfall data collected during 1969–2013. We found that drought frequency has increased to more than six drought months per year today compared with about two months per year in the 1970s (t = 2.884, p = 0.006). We used MODIS normalized difference vegetation index (NDVI) as a proxy for vegetation activity, to determine how vegetation has responded to the changing drought frequency between 2000 and 2013. We found that Aldabra's vegetation is highly responsive to changes in rainfall: anomalies in long-term mean monthly NDVI across Aldabra were found to decrease below the mean during most drought periods and increase above the mean during most non-drought periods. To investigate the response of tortoise habitat to rainfall, we extracted mean NDVI anomalies for three key habitat types. Open mixed scrub and grasslands, the preferred habitat of tortoises, showed the greatest decrease in vegetation activity during drought periods, and the greatest increase in average greenness during non-drought periods. Recent analysis has shown vegetation changes on Aldabra in recent decades. If these changes are caused by decreased precipitation, then the increased frequency of drought could impact the tortoise population, in both the short and long term, by limiting the quality and quantity of forage and/or shade availability within favoured habitats, and by changing the habitat composition across the atoll.
An increasing demand for full spatio-temporal coverage of soil information drives the growing use... more An increasing demand for full spatio-temporal coverage of soil information drives the growing use of soil spectroscopy. Soil spectroscopy application performed under laboratory conditions or in-field studies in semi-arid areas have shown promising results. However, when acquiring data in temperate zones, limitations by vegetation-free coverage, variation in soil moisture and management are driving coherent spatio-temporal data collection. This study explores the use of multi-temporal imaging spectroscopy data to increase the total mapping area of bare soils in a heterogeneous agricultural landscape. Spectrally and spatially high-resolution data from the Airborne Prism Experiment (APEX) were collected in September 2013, April 2014 and April 2015. Bare soils in all acquisitions were identified. To eliminate short-term differences in soil moisture and soil surface roughness, the empirical line method was used to calibrate the reflectance values of the singular images (2013 and 2015) towards the singular image with most bare soil pixels (2014). Difference indicators show that the calibration was successful (decrease in root mean square difference and angle difference, increase in R 2 and gain and offset close to one and zero). Finally, the multi-temporal composite image contained more than double the amount of bare soil pixels as compared to a singular acquisition. Summary statistics show that reflectance values of the multi-temporal composite approximate the single image data of 2014 (mean and standard deviation of 2014: 24.2 ± 8.9 vs. 24.0 ± 9.5 for the multi-temporal composite of 2013, 2014 and 2015). This indicates that global differences in soil moisture and land management have been corrected for. As a result, an improved spatial representation of soil parameters can be retrieved from the composite data. Spatial distribution of the correction factors and analysis of the spatial variability of all images, however, indicate that non-linear, short-term differences like variation in soil moisture and land management largely influence the result of the multi-temporal composite. Quantification and attribution of those factors will be required in the future to allow correcting for them.
—Agroecosystems play an important role in providing economic and ecosystem services, which direct... more —Agroecosystems play an important role in providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding, and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional land management model (LMM) to improve the assessment of spatially explicit nutrient balances for agroecosystems. Remotely sensed data and an optimized parameter set contributed to an improved LMM output, allowing for a better land allocation within the model. The best input parameter combination was based on two different land cover classifications with overall accuracies of 98%, improving the land allocation performance compared with using nonspatially explicit input. We conclude that the combined use of remote sensing data and the LMM has the potential to provide valuable guidance for farm practices. It further helps to generate a spatial description of farm-level nutrient balance, a crucial ability when choosing policy options related to sustainable management of agricultural soils. Index Terms—Agroecosystems, land allocation, land use classification , nutrient balancing, remote sensing (RS).
Considerable evidence exists that current global temperatures are higher than at any time during ... more 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.
Abstract–Continuous global time series of vegetation indices, which are available since early 198... more Abstract–Continuous global time series of vegetation indices, which are available since early 1980s, are of great value to detect changes in vegetation status at large spatial scales. Most change detection methods, however, assume a fixed change trajectory–defined by the start and end of the time series–and a linear or monotonic trend. Here, we apply a change detection method which detects abrupt changes within the time series. This Breaks For Additive Season and Trend (BFAST) approach showed that large parts of the world are ...
Description BFAST integrates the decomposition of time series into trend, seasonal, and remainder... more Description BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt changes within the trend and seasonal components. BFAST can be used to analyze different types of satellite image time series and can be applied to other disciplines dealing with seasonal or non-seasonal time series, such as hydrology, climatology, and econometrics. The algorithm can be extended to label detected changes with information on the parameters of the fitted ...
Monitoring land surface phenology (LSP) is important for understanding both the responses and fee... more 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.
EGU General Assembly 2010, held 2-7 May, 2010 in Vienna, Austria, p. 14800, May 1, 2010
Maintaining and enhancing the quality of land is of major importance to sustain future production... more Maintaining and enhancing the quality of land is of major importance to sustain future production capacity for food and other agriculture based products like fibers and wood, and for maintaining ecosystems services, including below and above ground biodiversity, provision of soil water and sequestration of carbon. Deterioration of this production base will be detrimental to the provision of the foreseen dramatic increase in human needs for goods and services. For this reason, land degradation, defined as a long ...
The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial... more The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial ecosystems and their role in carbon cycle. We used a combination of the most recent NDVI and model-based NPP estimates (from five models of the TRENDY project) for the period 1982–2012, to study the role of terrestrial ecosystems in carbon cycle under the prevailing climate conditions. We found that 80% and 67% of the global land area showed positive NPP and NDVI values, respectively, for this period. The global NPP was estimated to be about 63 Pg C¨y´1 , with an increase of 0.214 Pg C¨y´1¨y´1. Similarly, the global mean NDVI was estimated to be 0.33, with an increasing trend of 0.00041 y ´1. The spatial patterns of NPP and NDVI demonstrated substantial variability, especially at the regional level, for most part of the globe. However, on temporal scale, both global NPP and NDVI showed a corresponding pattern of increase (decrease) for the duration of this study except for few years (e.g., 1990 and 1995–1998). Generally, the Northern Hemisphere showed stronger NDVI and NPP increasing trends over time compared to the Southern Hemisphere; however, NDVI showed larger trends in Temperate regions while NPP showed larger trends in Boreal regions. Among the five models, the maximum and minimum NPP were produced by JULES (72.4 Pg C¨y´1) and LPJ (53.72 Pg C¨y´1) models, respectively. At latitudinal level, the NDVI and NPP ranges were ~0.035 y ´1 to ~´0.016 y ´1 and ~0.10 Pg C¨y´1¨y´1 to ~´0.047 Pg C¨y´1¨y´1 , respectively. Overall, the results of this study suggest that the modeled NPP generally correspond to the NDVI trends in the temporal dimension. The significant variability in spatial patterns of NPP and NDVI trends points to a need for research to understand the causes of these discrepancies between molded and observed ecosystem dynamics, and the carbon cycle.
Evaluating vegetation phenology is crucial for a better understanding of the effects of climate c... more Evaluating vegetation phenology is crucial for a better understanding of the effects of climate change on the terrestrial ecosystem. The scientific community has used various vegetation index data sets from different sensors to quantify vegetation phenology from regional to global scales. The normalized difference vegetation index (NDVI) related to photosynthetic activities is the most widely used index. Recently, a number of published articles have used the Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index (MTCI) to measure vegetation phenology. MTCI can closely represent the red-edge position (REP). Unlike NDVI, MTCI is more sensitive to high values of chlorophyll content. However, the consistency of vegetation phenological metrics derived from MTCI and NDVI needs to be further explored. This study compared two phenological metrics, i.e. onset of greenness (OG) and end of senescence (ES), extracted from MERIS MTCI data and Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) first generation NDVI (NDVIg) data, which has the longest time records, at nine regions in China from 2003 to 2006. The results showed that the differences of OG and ES vary between different vegetation types, regions, and years, although both NDVI and MTCI time series capture the growth patterns well for most vegetation types. Compared to ES, the OG estimates are more consistent. NDVI yields in general later ES estimates than MTCI.
The biosphere plays a large role in the global carbon cycle and as such in the climate system. Th... more The biosphere plays a large role in the global carbon cycle and as such in the climate system. The other way around, climatologies constrain vegetation growth. This feedback mechanism expresses itself in the phenology of the land surface (LSP) and is a crucial but uncertain component in Earth system models. An important defi- ciency is the decomposition of the natural and the anthropogenic signals in this land-atmosphere carbon cycle.
We studied the changes in yearly vegetation activity and LSP met- rics, and linked these to changes in potential climatological growth constraints (temperature, precipi- tation, radiation), both at global scale and in more detail for Swit- zerland. With this, we aim at im- proved attribution of detected bio- spheric changes to underlying drivers, both climatological and from other origin.
Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegeta... more 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 paper 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 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.
Imaging spectroscopy allows us to analyze the abundances of different materials on the glacier su... more Imaging spectroscopy allows us to analyze the abundances of different materials on the glacier surface on the pixel scale. These abundances are important information to improve the understanding of the spatial distribution of glacier ablation, which appears to depend strongly on surface albedo.
Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegeta... more Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegetated land surfaces as observed from satellite imagery. As such, LSP plays a key role in characterizing land surface fluxes, understanding the terrestrial carbon budget and the response of terrestrial ecosystems to environmental change. Various studies have highlighted significant increases in vegetation activity over time (i.e. greening) over Europe in recent decades, associated both with climatic changes and with large-scale human interventions, including land-use change. In this study we assess trends in LSP in Pan-Europe over the last 30 years. We found significant shifts in NDVI-derived GSL over the last 30 years for approx. 18-30% of terrestrial Pan-Europe, with an average GS lengthening quantified at 0.63-0.82 days/year. The LANMAP stratification reveals large spatial variation in LSP trends, both between climatic zones and landscape classes (Figures 3 and 4). Hotspot areas for GS lengthening are the continental and boreal climatic zones, whereas negative GSL trends occur mostly in Western France, the Italian Po valley and West of the Caspian Sea. Results reveal an assymetrically strong role of EOS delay/advance on the overall shifts found.
The 20th century was a pivotal period at high northern latitudes as it marked the onset of a rapi... more The 20th century was a pivotal period at high northern latitudes as it marked the onset of a 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 record. 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 datasets were used to explore the relationships between vegetation productivity and Arctic sea ice concentration and extent, and temperatures. Results indicate that an unusually large amount of black spruce (Picea mariana) trees entered into a period of growth decline during the late 20th century (68% 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 the 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 43 drought stress and tree mortality with ongoing climatic changes.
Consumer-grade digital cameras are recognized as a cost-effective method of monitoring plant heal... more Consumer-grade digital cameras are recognized as a cost-effective method of monitoring plant healthand phenology. The capacity to use these cameras to produce time series information contributes to abetter understanding of relationships between environmental conditions, vegetation health, and produc-tivity. In this study we evaluate the use of consumer grade digital cameras modified to capture infraredwavelengths for monitoring vegetation. The use of infrared imagery is very common in satellite remotesensing, while most current near sensing studies are limited to visible wavelengths only. The use ofinfrared-visible observations is theoretically superior over the use of just visible observation due to thestrong contrast between infrared and visible reflection of vegetation, the high correlation of the threevisible bands and the possibilities to use spectral indices like the Normalized Difference Vegetation Index. This paper presents two experiments: the first study compares infrared modified and true color camerasto detect seasonal development of understory plants species in a forest; the second is aimed at evaluation of spectrometer and camera data collected during a laboratory plant stress experiment. The main goal ofthe experiments is to evaluate the utility of infrared modified cameras for the monitoring of plant healthand phenology. Results show that infrared converted cameras perform less than standard color cameras in a monitoringsetting. Comparison of the infrared camera response to spectrometer data points at limits in dynamicrange, and poor band separation as the main weaknesses of converted consumer cameras. Our resultssupport the use of standard color cameras as simple and affordable tools for the monitoring of plant stressand phenology.
Consumer-grade cameras (CGC) have advantageous characteristics for close-range vegetation monitor... more Consumer-grade cameras (CGC) have advantageous characteristics for close-range vegetation monitoring, although there are limitations for many scientific applications. We discuss four categories of constraints, as well as potential modifications for effective vegetation monitoring.
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Papers by Rogier de Jong
We studied the changes in yearly vegetation activity and LSP met- rics, and linked these to changes in potential climatological growth constraints (temperature, precipi- tation, radiation), both at global scale and in more detail for Swit- zerland. With this, we aim at im- proved attribution of detected bio- spheric changes to underlying drivers, both climatological and from other origin.
GSL increased significantly by 18–24 days/decade 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.
We studied the changes in yearly vegetation activity and LSP met- rics, and linked these to changes in potential climatological growth constraints (temperature, precipi- tation, radiation), both at global scale and in more detail for Swit- zerland. With this, we aim at im- proved attribution of detected bio- spheric changes to underlying drivers, both climatological and from other origin.
GSL increased significantly by 18–24 days/decade 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.