Wanda De Keersmaecker

How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems

Increasing frequency of extreme climate events is likely to impose increased stress on ecosystems and to jeopardize the services that ecosystems provide. Therefore, it is of major importance to assess the effects of extreme climate events on the temporal stability (i.e., the resistance, the resilience, and the variance) of ecosystem properties. Most time series of ecosystem properties are, however, affected by varying data characteristics, uncertainties, and noise, which complicate the comparison of ecosystem stability metrics (ESMs) between locations. Therefore, there is a strong need for a more comprehensive understanding regarding the reliability of stability metrics and how they can be used to compare ecosystem stability globally. The objective of this study was to evaluate the performance of temporal ESMs based on time series of the Moderate Resolution Imaging Spectroradiometer derived Normalized Difference Vegetation Index of 15 global land-cover types. We provide a framework (i) to assess the reliability of ESMs in function of data characteristics, uncertainties and noise and (ii) to integrate reliability estimates in future global ecosystem stability studies against climate disturbances. The performance of our framework was tested through (i) a global ecosystem comparison and (ii) an comparison of ecosystem stability in response to the 2003 drought. The results show the influence of data quality on the accuracy of ecosystem stability. White noise, biased noise, and trends have a stronger effect on the accuracy of stability metrics than the length of the time series, temporal resolution, or amount of missing values. Moreover, we demonstrate the importance of integrating reliability estimates to interpret stability metrics within confidence limits. Based on these confidence limits, other studies dealing with specific ecosystem types or locations can be put into context, and a more reliable assessment of ecosystem stability against environmental disturbances can be obtained.

Species-rich semi-natural grasslands have a higher resistance but a lower resilience than intensively managed agricultural grasslands in response to climate anomalies

The stable delivery of ecosystem services provided by grasslands is strongly dependent on the stability of grassland ecosystem functions such as biomass production. Biomass production is in turn strongly affected by the frequency and intensity of climate extremes. The aim of this study is to evaluate to what extent species-poor intensively managed agricultural grasslands can maintain their biomass productivity under climate anomalies, as compared to species-rich, semi-natural grasslands. Our hypothesis is that species richness stabilizes biomass production over time. Biomass production stability was assessed in response to drought and temperature anomalies using 14 years of the Normalized Difference Vegetation Index (NDVI), temperature and drought index time series. More specifically, vegetation resistance (i.e. the ability to withstand the climate anomaly) and resilience (i.e. the recovery rate) were derived using an auto-regressive model with external input variables (ARx). The stability metrics for both grasslands were subsequently compared. We found that semi-natural grasslands exhibited a higher resistance but lower resilience than agricultural grasslands in the Netherlands. Furthermore, the difference in stability between semi-natural and agricultural grasslands was dependent on the physical geography: the most significant differences in resistance were observed in coastal dunes and riverine areas, whereas the differences in resilience were the most significant in coastal dunes and fens. Synthesis and applications. We conclude that semi-natural grasslands show a higher resistance to drought and temperature anomalies compared to agricultural grasslands. These results underline the need to reassess the ways agricultural practices are performed. More specifically, increasing the plant species richness of agricultural grasslands and lowering their mowing and grazing frequency may contribute to buffer their biomass production stability against climate extremes.

Assessment of Regional Vegetation Response to Climate Anomalies: A Case Study for Australia Using GIMMS NDVI Time Series between 1982 and 2006

Within the context of climate change, it is of utmost importance to quantify the stability of ecosystems with respect to climate anomalies. It is well acknowledged that ecosystem stability may change over time. As these temporal stability changes may provide a warning for increased vulnerability of the system, this study provides a methodology to quantify and assess these temporal changes in vegetation stability. Within this framework, vegetation stability changes were quantified over Australia from 1982 to 2006 using GIMMS NDVI and climate time series (i.e., SPEI (Standardized Precipitation and Evaporation Index)). Starting from a stability assessment on the complete time series, we aim to assess: (i) the magnitude and direction of stability changes; and (ii) the similarity in these changes for different stability metrics, i.e., the standard deviation of the NDVI anomaly (SD), auto-correlation at lag one of the NDVI anomaly (AC) and the correlation of NDVI anomaly with SPEI (CS). Results show high variability in magnitude and direction for the different stability metrics. Large areas and types of Australian vegetation showed an increase in variability (SD) over time; however, vegetation memory (AC) decreased. The association of NDVI anomalies with drought events (CS) showed a mixed response: the association increased in the western part, while it decreased in the eastern part. This methodology shows the potential for quantifying vegetation responses to major climate shifts and land use change, but results could be enhanced with higher resolution time series data.

Plant Species Diversity Mediates Ecosystem Stability of Natural Dune Grasslands in Response to Drought

How plant species diversity can mediate the temporal stability of ecosystem functioning during periods of environmental stress is still a pressing question in ecology, certainly in the context of predicted increasing frequencies and intensities of climate extremes, such as drought. The vast majority of empirical research in this context is based on relatively small-scaled experiments, where plant species composition is manipulated and ecosystem functions, such as biomass production, are monitored through time. Results of these studies have generally shown that ecosystem functioning is more stable in more species-diverse communities. Yet, there is very little evidence so far that these relations also hold in naturally assembled plant communities. In this study, we combined historical vegetation and climate data with time series of remotely sensed indicators of aboveground biomass production (MODIS NDVI), to quantify how plant species diversity and plant functional diversity correlate with the temporal stability of biomass production in naturally assembled Dutch dune grasslands under the influence of fluctuating drought. We found that the negative NDVI response to drought of grasslands with a higher plant species richness and diversity was significantly lower than the response of less species rich and species-diverse grasslands, indicating a stabilizing role of plant species richness and diversity on biomass production through time. We found no relation between plant functional diversity and NDVI response to drought. This is the first study to generalize experimentally established relations between species diversity and stability of ecosystem functioning to naturally assembled grasslands across a large spatial and temporal scale.

Linking NDVI and climate-based ecosystem stability with land cover in Europe

Changing climate conditions are expected to affect vegetation health globally, further emphasizing the importance to assess vegetation response to climate anomalies on a large scale and to understand its driving factors. Within this context, vegetation resilience and resistance against drought and temperature anomalies were assessed using an autoregressive model based on GIMMS NDVI and climate time series over Europe. The extracted vegetation stability metrics were subsequently related to Corine Land Cover classes. The model (i) allowed for exclusion of spurious results and (ii) provided vegetation resistance and resilience metrics normalized for climate variability. These ecosystem stability metrics further showed a clear correspondence with vegetation types in Europe.

Shape-based unmixing for vegetation mapping

Spectral mixture analyses (SMA) is often used as a tool to map complex/mixed (semi-)natural ecosystems. Yet, the performance of SMA, which traditionally uses the amplitude-based RMSE as the objective function, is often hampered by the high spectral similarity among co-occurring plant species. Experiments, based on ray-tracing simulations, in situ measured reflectance data and AVIRIS imagery demonstrated the added value of implementing shape-based error metrics in the unmixing of forests and orchards. The approach allowed to highlight the subtle spectral differences among co-occurring plant species resulting in an overall improvement of species specific mapping (i. e. decrease in MSE ≈ 40%).