Global‐scale characterization of turning points in arid and semi‐arid ecosystem functioning

Bernardino, Paulo; Keersmaecker, Wanda De; Fensholt, Rasmus; Verbesselt, Jan; Somers, Ben; Horion, Stéphanie

doi:10.1111/geb.13099

Cited by 58 publications

(48 citation statements)

References 45 publications

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“…2. Abrupt changes or turning points in land cover (i.e., when the functioning of an ecosystem changes significantly, but not necessarily in an irreversible manner [38]) were identified over the areas in the past [9]. 3.…”

Section: Study Areamentioning

confidence: 99%

“…The area was considered to be under the imminent threat of desertification in the future [6]. Nevertheless, many studies indicated that since this period, the Sahel experienced significant re-greening, showing the resilient character of the region [7,8] and the existence of so-called turning points in the region [9]. Besides the influence of climatology, anthropogenic activities also strongly affect land cover and vegetation.…”

Section: Introductionmentioning

confidence: 99%

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Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series

et al. 2020

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Historical land cover maps are of high importance for scientists and policy makers studying the dynamic character of land cover change in the Sudano-Sahel, including anthropogenic and climatological drivers. Despite its relevance, an accurate high resolution record of historical land cover maps is currently lacking over the Sudano-Sahel. In this study, 30 m resolution historically consistent land cover and cover fraction maps are provided over the Sudano-Sahel for the period 1986–2015. These land cover/cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification/regression model, while historical consistency is achieved using the hidden Markov model. Using these historical maps, a multitude of variability in the dynamic Sudano-Sahel region over the past 30 years is revealed. On the one hand, Sahel-wide cropland expansion and the re-greening of the Sahel is observed in the discrete land cover classification. On the other hand, subtle changes such as forest degradation are detected based on the cover fraction maps. Additionally, exploiting the 30 m spatial resolution, fine-scale changes, such as smallholder or subsistence farming, can be detected. The historical land cover/cover fraction maps presented in this study are made available via an open-access platform.

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Section: Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series

et al. 2020

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“…For example, the methods in the first category aim to control the influence of precipitation and/or temperature trends to detect permanent degradation [7,23]. The rain use efficiency (RUE) as proposed by [19]-the ratio of NPP to rainfall-has been used as an indicator of degradation [7,17,20,26,27] and ecosystem functioning [18,28]. The residual trend analysis (RESTREND) method as proposed by [11] was used frequently to estimate changes in productivity by relating annual maximum NDVI and precipitation [11,13,25,29].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)

2021

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Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984–2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM’s grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM’s drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM’s vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity.

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“…In rainfall limited ecosystems, interpreting vegetation dynamics requires decoupling NDVI from rainfall variability. This can be achieved using the Rain Use Efficiency (RUE): the NPP per unit of rainfall [22][23][24][25]. The basis of this measure is that if vegetation declines in synchrony with rainfall, then the RUE will remain constant-indicating stable ecosystem condition.…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, if NPP declines under constant rainfall, the RUE would decline-indicating deteriorating ecosystem condition. Trends in RUE have been used to assess broad level ecosystem condition, while shifts in RUE have been related to the linkages of human and climatic drivers on ecosystem function [20,23,25].…”

Section: Introductionmentioning

confidence: 99%

Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data

Higginbottom

Symeonakis

2020

Remote Sensing

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Time-series of vegetation greenness data, derived from Earth-observation imagery, have become a key source of information for studying large-scale environmental change. The ever increasing length of such series allows for a range of indicators to be derived and for increasingly complex analyses to be applied. This study presents an analysis of trends in vegetation productivity—measured using the Global Inventory Monitoring and Modelling System third generation (GIMMS3g) Normalised Difference Vegetation Index (NDVI) data—for African savannahs, over the 1982–2015 period. Two annual metrics were derived from the 34 year dataset: the monthly, smoothed NDVI (the aggregated growth season NDVI) and the associated Rain Use Efficiency (growth season NDVI divided by annual rainfall). These indicators were then used in a BFAST-based change-point analysis, allowing the direction of change over time to change and the detection of one major break in the time-series. We also analysed the role of land cover type and climate zone as associations of the observed changes. Both methods agree that vegetation greening was pervasive across African savannahs, although RUE displayed less significant changes than NDVI. Monotonically increasing trends were the most common trend type for both indicators. The continental scale of the greening may suggest global processes as key drivers, such as carbon fertilization. That NDVI trends were more dynamic than RUE suggests that a large component of vegetation trends is driven by precipitation variability. Areas of negative trends were conspicuous by their minimalism. However, some patterns were apparent. In the southern Sahel and West Africa, declining NDVI and RUE overlapped with intensive population and agricultural regions. Dynamic trend reversals, in RUE and NDVI, located in Angola, Zambia and Tanzania, coincide with areas where a long-term trend of forest degradation and agricultural expansion has recently given way to increases in woody biomass. Meanwhile in southern Africa, monotonic increases in RUE with varying NDVI trend types may be indicative of shrub encroachment. However, all these processes are small-scale relative to the GIMMS NDVI data, and reconciling these conflicting drivers is not a trivial task. Our study highlights the importance of considering multiple options when undertaking trend analyses, as different inputs and methods can reveal divergent patterns.

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Global‐scale characterization of turning points in arid and semi‐arid ecosystem functioning

Cited by 58 publications

References 45 publications

Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series

Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series

Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)

Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data

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