Environmental change in the Sahel, Research results

Tree cover promoted in semi-arid Sahelian farms – new publication in Nature Geoscience

More people equal more trees in semi-arid West Africa – Our new study published in Nature Geoscience questions ‘received wisdom’ as concerns the relationship between human agency and woody vegetation of West Africa. We demonstrate that in low-rainfall areas woody cover is denser in cultivated areas than in savannas, and close to settlements rather that further away, thus rejecting simplistic Malthusian ideas of a negative relationship between population density and woody cover.

These findings challenge the traditional view on agricultural expansion in semi-arid lands and this has implications for the understanding of effects of agricultural expansion on ecosystem services, including carbon sequestration. Also, these findings throw light upon the process of land degradation/desertification which contradicts commonly believed narratives on human expansion in drylands causing fuel-wood crisis, deforestation, soil depletion, erosion and desertification.

 The study is part of an unprecedented NASA project (lead by CJ Tucker), which aims at applying commercial DigitalGlobe satellite imagery with a spatial resolution of 50 cm to map the size of each individual tree and shrub in African dryland ecosystems. Our team had access to thousands of these images, and this study is the first allowing a wall-to-wall map of woody cover based on individual trees.

In contrast to traditional case studies prone to sampling errors and bias by the prevailing societal discourse, the woody cover map includes 40,000 villages, passing a technical tipping point in dryland environmental research.

Article in Nature Geoscience:

Brandt, M., Rasmussen, K., Hiernaux, P., Herrmann, S., Tucker, C.J., Tong, X., Tian, F., Mertz, O., Kergoat, L., Mbow, C., David, J.L., Melocik, K.A., Dendoncker, M., Vincke, C., Fensholt, R., 2018. Reduction of tree cover in West African woodlands and promotion in semi-arid farmlands. Nature Geoscience 1. https://doi.org/10.1038/s41561-018-0092-x

Further read in Nature Geoscience News (summary by Niall Hanan):

https://www.nature.com/articles/s41561-018-0112-x

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Research results

A new tool to monitor aboveground vegetation carbon stocks: first application to the African continent

Our new study uses unprecedented data sources to measure vegetation carbon stock dynamics at continental scale. The study demonstrates that over the African continent, the net carbon balance is negative for 2010-2016, and that most of the carbon losses occurred in dryland savannahs. The results were published in the journal Nature Ecology and Evolution.

The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances from both human pressure and climate change threaten vegetation carbon stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics.

Continental scale monitoring of vegetation carbon dynamics requires satellite based techniques, however, conventional satellites are limited to sensing the upper canopy layer. Consequently, the monitoring of vegetation dynamics is limited to the top green parts of the canopies which are not directly linked to aboveground biomass carbon.

Our French colleagues around Jean Pierre Wigneron (CEA, CNES, CNRS, INRA) have produced a new data set retrieved from space-borne observations of the SMOS satellite starting in 2010. The data set is based on low frequency passive microwave emissions, which are insensitive to cloud cover and green vegetation and thus able to quantify aboveground biomass carbon of the entire vegetation layer, including stems and branches, even when the vegetation is dense.

Our group had the chance to be the first group testing these new data, with groundbreaking results. For the first time, scientists were able to monitor large scale carbon stock dynamics at annual scale. The groups expect this tool to be a key in future monitoring of carbon losses and gains for national reports and large-scale efforts, such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Intergovernmental Panel on Climate Change (IPCC).

A first application to the African continent showed highly dynamic carbon stocks, and especially dryland savannahs showed surprisingly high gross losses which were caused by recent drought years. The study concludes that the new tool is close to be operational and highlights the importance of drylands in the global carbon balance.

Screenshot from 2018-03-27 15-03-42.png
Changes in aboveground vegetation carbon stocks in sub-Saharan Africa over 2010–2016. Regions with significant negative (carbon source) or positive (carbon sink) carbon changes are shown, respectively, in red or green.

© M. Brandt – Université de Copenhagen

Article at Nature Ecology and Evolution:

Brandt M, Wigneron J-P, Chave J, Tagesson T, Penuelas J, Ciais P, Rasmussen K, Tian F, Mbow C, Al-Yaari A, Rodriguez-Fernandez N, Schurgers G, Zhang W, Chang J, Kerr Y, Verger A, Tucker C, Mialon A, Rasmussen LV, Fan L, Fensholt R. 2018. Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands. Nature Ecology & Evolution 1. DOI: 10.1038/s41559-018-0530-6

Further reading:

Mongabay: new remote sensing technique used to determine carbon losses in sub-saharan africa

Article at Carbon Brief

SMOS

Environmental change in the Sahel, Research results

New publications!

woody-plants-workshop-in-copenhagen19_01_2017_group-photo-2

Our fantastic team had some new publications within the past half year, they are all worth to have a look:

This one deals with the question if agricultural intensification in Sahel causes an increase or decrease in NDVI trends. Surprisingly, we find a negative NDVI trend coupled with an increase in cropped areas which means that fallowed fields have a substantially higher NDVI than cropped fields.

Open access! Here we use great data sources to document dynamics in woody vegetation in central Senegal. Field data from 2000 to 2015, fantastic aerial photos from 1994, repeat photography from 1994 and 2015, satellite imagery at 50 cm resolution from 2005-2015, and finally MODIS time series. We find a high spatial and temporal dynamic, encroachment, die off, etc. It’s a very a colourfully illustrated study which will make you feel like travelling to Senegal..

A great story as well: We document how conservation projects in Southern China are able to impact on vegetation trends and propose an index which allows to put the invested money (for conservation projects) in relation with vegetation trends to be able to determine the project effectiveness.

A very clever way to combine optical and passive microwave satellite data: We assume that optical satellite data senses the green part of the vegetation and the passive microwaves the green plus non-green parts. So we combine both to estimate the non green vegetation (i.e. the wood) and look at global trends from 2000 to 2012 which allows us to map gradual gains and losses in woody cover.

Research results

Integrating meteorological data in biomass prediction models

Diouf, A.A.; Hiernaux, P.; Brandt, M.; Faye, G.; Djaby, B.; Diop, M.B.; Ndione, J.A.; Tychon, B. Do Agrometeorological Data Improve Optical Satellite-Based Estimations of the Herbaceous Yield in Sahelian Semi-Arid Ecosystems? Remote Sens. 2016, 8, 668.

Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for about 40 years.

This study combines traditional FAPAR-based assessments with agrometeorological variables computed by the geospatial water balance program, GeoWRSI, using rainfall and potential evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal.

It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483 kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase in relative inter-annual variation. In particular, the additional use of agrometeorological information mitigated the saturation effects that characterize the plant indices of areas with high plant productivity.

The date of the onset of the growing season derived from smoothed FAPAR seasonal dynamics showed no significant relationship (0.05 p-level) with the annual herbaceous yield across the whole studied area. The date of the onset of rainfall was significantly related to the herbaceous yield and its inclusion in fodder biomass models could constitute a significant improvement in forecasting risks of a mass herbaceous deficit at an early stage of the year.

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Environmental change in the Sahel, Research results

Recent woody vegetation trends in Sahel

Our new paper looks at recent dynamics in woody vegetation in Sahel and finds some interesting patterns which are mainly controlled by human population density.

Martin Brandt, Pierre Hiernaux, Kjeld Rasmussen, Cheikh Mbow, Laurent Kergoat, Torbern Tagesson, Yahaya Ibrahim, Abdoulaye Wele, Compton J. Tucker, Rasmus Fensholt. Assessing woody vegetation trends in Sahelian drylands using MODIS based seasonal metrics. Remote Sensing of Environment, 2016, 183, 215-225.

  • Woody cover trends are estimated for Sahel based on MODIS dry season metrics.
  • Interannual fluctuations in foliage density are attenuated to monitor woody plant trends.
  • Increases (decreases) are seen in areas of low (high) human population.
  • Recent decreases only partially offset a general post-drought increase in Sahelian woody cover.

Woody plants play a major role for the resilience of drylands and in peoples’ livelihoods. However, due to their scattered distribution, quantifying and monitoring woody cover over space and time is challenging. We develop a phenology driven model and train/validate MODIS (MCD43A4, 500 m) derived metrics with 178 ground observations from Niger, Senegal and Mali to estimate woody cover trends from 2000 to 2014 over the entire Sahel at 500 m scale.

Over the 15 year period we observed an average increase of 1.7 (± 5.0) woody cover (%) with large spatial differences: No clear change can be observed in densely populated areas (0.2 ± 4.2), whereas a positive change is seen in sparsely populated areas (2.1 ± 5.2). Woody cover is generally stable in cropland areas (0.9 ± 4.6), reflecting the protective management of parkland trees by the farmers. Positive changes are observed in savannas (2.5 ± 5.4) and woodland areas (3.9 ± 7.3).

The major pattern of woody cover change reveals strong increases in the sparsely populated Sahel zones of eastern Senegal, western Mali and central Chad, but a decreasing trend is observed in the densely populated western parts of Senegal, northern Nigeria, Sudan and southwestern Niger. This decrease is often local and limited to woodlands, being an indication of ongoing expansion of cultivated areas and selective logging.

We show that an overall positive trend is found in areas of low anthropogenic pressure demonstrating the potential of these ecosystems to provide services such as carbon storage, if not over-utilized. Taken together, our results provide an unprecedented synthesis of woody cover dynamics in the Sahel, and point to land use and human population density as important drivers, however only partially and locally offsetting a general post-drought increase.

graph_abstract

Research results

Assessing Future Vegetation Trends and Restoration Prospects in the Karst Regions of Southwest China

Our latest article is not located in the Sahel, however, the method to assess the future persistence of vegetation trends is highly interesting in the context of ecosystem stability and resistance. The article is open access and freely available.

Tong, Xiaowei; Wang, Kelin; Brandt, Martin; Yue, Yuemin; Liao, Chujie; Fensholt, Rasmus. 2016. “Assessing Future Vegetation Trends and Restoration Prospects in the Karst Regions of Southwest China.” Remote Sens. 8, no. 5: 357.

 

To alleviate the severe rocky desertification and improve the ecological conditions in Southwest China, the national and local Chinese governments have implemented a series of Ecological Restoration Projects since the late 1990s. In this context, remote sensing can be a valuable tool for conservation management by monitoring vegetation dynamics, projecting the persistence of vegetation trends and identifying areas of interest for upcoming restoration measures.

In this study, we use MODIS satellite time series (2001–2013) and the Hurst exponent to classify the study area (Guizhou and Guangxi Provinces) according to the persistence of future vegetation trends (positive, anti-persistent positive, negative, anti-persistent negative, stable or uncertain). The persistence of trends is interrelated with terrain conditions (elevation and slope angle) and results in an index providing information on the restoration prospects and associated uncertainty of different terrain classes found in the study area.

The results show that 69% of the observed trends are persistent beyond 2013, with 57% being stable, 10% positive, 5% anti-persistent positive, 3% negative, 1% anti-persistent negative and 24% uncertain. Most negative development is found in areas of high anthropogenic influence (low elevation and slope), as compared to areas of rough terrain. We further show that the uncertainty increases with the elevation and slope angle, and areas characterized by both high elevation and slope angle need special attention to prevent degradation. Whereas areas with a low elevation and slope angle appear to be less susceptible and relevant for restoration efforts (also having a high uncertainty), we identify large areas of medium elevation and slope where positive future trends are likely to happen if adequate measures are utilized.

The proposed framework of this analysis has been proven to work well for assessing restoration prospects in the study area, and due to the generic design, the method is expected to be applicable for other areas of complex landscapes in the world to explore future trends of vegetation.

graphical_abstract

The Hurst exponent, a measure of the persistence of a time series, can be easily calculated on a raster time series in R:

library(raster)
library(rgdal)
library(pracma)

# set working directory with the raster files, here in TIF format, 
# and load the files in a rasterbrick

setwd("/media/2016_Xiaowei/")
gsn = brick(list.files(pattern='*.tif'))
# test on the average of the study area

g=cellStats(gsn, stat='mean')
gsn.ts = ts(g, start=c(2001,1), end=c(2013,1), frequency=1)
plot(gsn.ts)

h=hurstexp(gsn.ts)$Hs
h

# run the function on the rasterbrick gsn

fun=function(x) { 
  v=as.vector(x)
  if (is.na(v[1])){ NA } else
  gsn.ts = ts(v, start=c(2001,1), end=c(2013,1), frequency=1)
  x=hurstexp(gsn.ts, display=F)$Hs 
}
h <- calc(gsn, fun)
plot(h)

Research results

Remote sensing of vegetation in drylands: Evaluating vegetation optical depth (VOD) using NDVI and in situ data over Sahel

Tian, F.; Brandt, M.; Liu, Y. Y.; Verger, A.; Tagesson, T.; Diouf, A. A.; Rasmussen, K.; Mbow, C.; Wang, Y.; Fensholt, R. Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel. Remote Sensing of Environment 2016, 177, 265–276.

 

  •  A Long-term VOD dataset is evaluated against NDVI and in situ biomass observations.
  • Both VOD and NDVI reflect the spatio-temporal patterns of biomass in West Sahel.
  • VOD captures variations of woody plant foliage biomass better than NDVI.
  • VOD and NDVI seasonal metrics differ for optimal long-term monitoring of biomass.

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages.

In this study, we assess the capability of a long-term VOD dataset (1992–2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel.

Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r2 = 0.90).

Overall, in spite of the coarse resolution of 25 km, the study shows that VOD is an efficient proxy for estimating biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas.

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