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

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

Spatial distribution of arable and abandoned land across former Soviet Union countries

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others

Evaluation of land surface models in reproducing satellite-derived LAI over the high-latitude northern hemisphere. Part I: Uncoupled DGVMs

PublishedJournal ArticleLeaf Area Index (LAI) represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN) from the latest version (third generation) of GIMMS AVHRR NDVI data over the period 1986-2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees. © 2013 by the authors.The corresponding author also thanks the CONACYT-CECTI and the University of Exeter for their funding during the PhD studies. The National Center for Atmospheric Research is sponsored by the National Science Foundation

Data descriptor: Spatial distribution of arable and abandoned land across former Soviet Union countries

© The Author(s) 2018. Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others

Ecological engineering projects increased vegetation cover, production, and biomass in semiarid and subhumid Northern China

Multiple ecological engineering projects have been implemented in semiarid and subhumid Northern China since 1978 with the purpose to combat desertification, control dust storms, and improve vegetation cover. Although a plethora of local studies exist, the effectiveness of these projects has not been studied in a systematic and comprehensive way. Here, we used multiple satellite-based time-series data as well as breakpoint analysis to assess shifts in leaf area index (a proxy for green vegetation cover), gross primary production, and aboveground biomass in Northern China. We documented increased vegetation growth in northwest and southeastern parts of the region, despite drought anomalies as documented by the standardized precipitation-evapotranspiration index during 1982–2016. Significant breakpoints in leaf area index were observed for over 72.5% of the southeastern and northwestern regions, and 70.6% of these breakpoints were detected after 1999, which correspond well to the areas with the highest ecological engineering efforts. Areas with negative trends were mainly located in the Inner Mongolian Plateau, Hulun Biur, Horqin Sand Land, and urban areas. The Loess Plateau had the largest increase in vegetation growth, followed by the north parts of Northern China where biomass increased more in the provinces of Shanxi, Liaoning, Shannxi, Hebei, and Beijing than Xinjiang, Inner Mongolia, Tianjin, and Qinghai. Our results show that multiple ecological engineering projects in the region have increased vegetation cover, production, and aboveground biomass that have led to improved environmental conditions in the study area

EU-Trees4F, a dataset on the future distribution of European tree species

We present "EU-Trees4F", a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. "EU-Trees4F", can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking.Peer reviewe

African dryland ecosystem changes controlled by soil water

Monitoring long‐term vegetation dynamics in African drylands is of great importance for both ecosystem degradation studies and carbon‐cycle modelling. Here, we exploited the complementary use of optical and passive microwave satellite data— normalized difference vegetation index (NDVI) and vegetation optical depth (VOD)—to provide new insights of ecosystem changes in African drylands. During 1993–2012, 54% of African drylands experienced a significant increase of VOD, mainly located in southern Africa and west and central Africa, with an average rate of increase of (1.2 ± 2.7) × 10−3 yr−1. However, a significant decreasing NDVI was observed over 43% of the African drylands, in particular in western Niger and eastern Africa, with an average browning rate of (−0.13 ± 1.5) × 10−3 yr−1. The contrasting vegetation trends (increasing VOD and decreasing NDVI) were largely caused by an increase in the relative proportion of the woody component of the vegetation, as a result of the prevailing woody encroachment in African drylands during the study period. Soil water emerges as the dominant driver of ecosystem changes in African drylands, in particular in arid and semiarid areas. This is evidenced by a strong spatio‐temporal correlation between soil water and vegetation, where soil water changes explain about 48% of vegetation variations. This study emphasizes the potential of utilizing multiple satellite products with different strengths in monitoring different characteristics of ecosystems to evaluate ecosystem changes and reveal the underlying mechanisms of the observed changes

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

Aim: Changes in dryland ecosystem functioning are threatening the well‐being of human populations worldwide, and land degradation, exacerbated by climate change, contributes to biodiversity loss and puts pressures on sustainable livelihoods. Here, abrupt changes in ecosystem functioning [so‐called turning points (TPs)] were detected using time series of Earth observation data. Hotspot areas of high TP occurrence were identified, observed changes characterized and insights gained on potential drivers for these changes.Location: Arid and semi‐arid regions.Time period: 1982–2015.Methods: We used a time series segmentation technique (breaks for additive season and trend) to detect breakpoints in rain‐use efficiency as a means of analysing changes in ecosystem functioning. A new typology to characterize the detected changes was proposed and evaluated, at regional to local scales, for a set of case studies. Ancillary data on population and drought were used to provide insights on potential drivers of TP occurrence.Results: Turning points in ecosystem functioning were found in 13.6% (c. 2.1 × 106 km2) of global drylands. Turning point hotspots were primarily observed in North America, the Sahel, Central Asia and Australia. In North America, the majority of TPs (62.6%) were characterized by a decreasing trend in ecosystem functioning, whereas for the other regions, a positive reversal in ecosystem functioning was prevalent. Further analysis showed that: (a) both climatic and anthropogenic pressure influenced the occurrence of TPs in North America; (b) Sahelian grasslands were primarily characterized by drought‐induced TPs; and (c) high anthropogenic pressure coincided with the occurrence of TPs in Asia and Australia.Main conclusions: By developing a new typology targeting the categorization of abrupt and gradual changes in ecosystem functioning, we detected and characterized TPs in global drylands. This TP characterization is a first crucial step towards understanding the drivers of change and supporting better decision‐making for ecosystem conservation and management in drylands

A Remote Sensing-Based Inventory of West Africa Tropical Forest Patches: A Basis for Enhancing Their Conservation and Sustainable Use

The rate of tropical deforestation is increasing globally, and the fragmentation of remaining forests is particularly high in arable landscapes of West Africa. As such, there is an urgent need to map and monitor these remnant forest patches/fragments and so identify their multiple benefits and values. Indeed, recognizing their existence will help ensure their continued provision of ecosystem services while facilitating their conservation and sustainable use. The aim of this study is therefore to inventory and characterise the current extent and change of remnant forest patches of West Africa, using multi-source remote sensing products, time-series analyses, and ancillary datasets. Specifically, we collate and analyse descriptive and change metrics to provide estimates of fragment size, age, biophysical conditions, and relation to social-ecological change drivers, which together provide novel insights into forest fragment change dynamics for over four decades. We map forests patches outside protected areas with a tree cover ≥30%, a tree height of ≥5 m, an area ≥1 km2 and ≤10 km2. Appended to each patch are descriptive and change dynamics attributes. We find that most fragments are small, secondary forest patches and these cumulatively underwent the most forest loss. However, on average, larger patches experience more loss than smaller ones, suggesting that small patches persist in the landscape. Primary forest patches are scarce and underwent fewer losses, as they may be less accessible. In 1975 most patches were mapped as secondary, degraded forests, savanna, woodland, and mangrove, and relatively few comprised cropland, settlements, and agriculture, suggesting that new forest patches rarely emerged from arable land over the past 45 years (1975–2020), but rather are remnants of previously forested landscapes. Greening is widespread in larger secondary fragments possibly due to regrowth from land abandonment and migration to urban areas. Forest loss and gain are greater across fragments lying in more modified landscapes of secondary forests, while forest loss increases with distance to roads. Finally, larger forest patches harbour a denser tree cover and higher trees as they may be less impacted by human pressures. The number and extent of West African forest patches are expected to further decline, with a concurrent heightening of forest fragmentation and accompanying edge effects. Lacking any conservation status, and subject to increasing extractive demands, their protection and sustainable use is imperative

Improved detection of abrupt change in vegetation reveals dominant fractional woody cover decline in Eastern Africa

While cropland expansion and demand for woodfuel exert increasing pressure on woody vegetation in East Africa, climate change is inducing woody cover gain. It is however unclear if these contrasting patterns have led to net fractional woody cover loss or gain. Here we used non-parametric fractional woody cover (WC) predictions and breakpoint detection algorithms driven by satellite observations (Landsat and MODIS) and airborne laser scanning to unveil the net fractional WC change during 2001-2019 over Ethiopia and Kenya. Our results show that total WC loss was 4-times higher than total gain, leading to net loss. The contribution of abrupt WC loss (59%) was higher than gradual losses (41%). We estimated an annual WC loss rate of up to 5% locally, with cropland expansion contributing to 57% of the total loss in the region. Major hotspots of WC loss and degradation corridors were identified inside as well as surrounding protected areas, in agricultural lands located close to agropastoral and pastoral livelihood zones, and near highly populated areas. As the dominant vegetation type in the region, Acacia-Commiphora bushlands and thickets ecosystem was the most threatened, accounting 69% of the total WC loss, followed by montane forest (12%). Although highly outweighed by loss, relatively more gain was observed in woody savanna than in other ecosystems. These results reveal the marked impact of human activities on woody vegetation and highlight the importance of protecting endangered ecosystems from increased human activities for mitigating impacts on climate and supporting sustainable ecosystem service provision in East Africa.Peer reviewe