Quantitative land-cover change in West Africa over the Holocene: case study in Cameroon

2020 ◽  
Author(s):  
Esther Githumbi ◽  
Marie-Jose Gaillard ◽  
Anne-Marie Lezine ◽  
Gaston Achoundong ◽  
Christelle Hély ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Spatial Scales ◽  
Reconstruction Algorithm ◽  
Second Phase ◽  
Climate Modelling ◽  
The Past ◽  
Landscape Reconstruction ◽  
Pollen Productivity ◽  
Pollen Records

<p>Currently interaction between climate and land-cover change in the past across the globe, and whether drivers are anthropogenic or natural are among the biggest debates. The impacts of climate and land-cover change are having significant consequences on biodiversity and ecosystems. Wide ranging palaeoenvironmental methods have contributed to this debate by providing long-term records of both climate and land-cover change. This provide the context for evaluating the effect of land-cover change on climate.  Inferred past land-cover and climate change from palaeoecological proxies therefore need to be quantified to provide reliable estimates of change; there are several methods of quantifying land-cover change in the past of which the Landscape Reconstruction Algorithm (LRA)  can estimate past land-cover change quantitatively at both regional and local spatial scales using fossil pollen records. The LRA includes two models (REVEALS and LOVE) and has already been tested and validated in Europe, North America, and China.</p><p>In this study, we apply the LRA on Holocene pollen records in Cameroon to estimate past land-cover change. This is the first pollen-based, quantitative land-cover reconstruction using LRA in Africa.  It will provide a comparison with land-cover change described from raw pollen data and useful information for climate modelling. The first phase involved the estimation of relative pollen productivity (RPP) for 13 taxa using the pollen-vegetation relationship described by the ERV model. The second phase involves the application of LRA using the RPPs from the 13 taxa.</p><p> </p><p><strong> </strong><strong>Acknowledgements</strong>: We thank the French ANR (National Research Agency; projects C3A ANR-09-PEXT-001 and VULPES ANR-15-MASC-0003) and the Belgian project BR/132/A1/AFRIFORD for financial support, IRD (France) and the Ministry of Research and National Herbarium of Cameroon for research facilities and authorizations, and A. Vincens, J.-P. Cazet, G. Buchet, L. Février, and K. Lemonnier (CNRS) for laboratory and field assistance. The study is a contribution to PAGES LandCover6k (www.pastglobalchanges.org/ini/wg/landcover6k/intro).</p>

scholarly journals Spatially Continuous Land-Cover Reconstructions Through the Holocene in Southern Sweden

Ecosystems ◽  
2021 ◽  
Author(s):  
Robert O’Dwyer ◽  
Laurent Marquer ◽  
Anna-Kari Trondman ◽  
Anna Maria Jönsson
Keyword(s):  
Land Cover ◽  
Regional Scale ◽  
Coniferous Forest ◽  
Reconstruction Algorithm ◽  
Fossil Pollen ◽  
Conifer Forest ◽  
Southern Sweden ◽  
The Holocene ◽  
Simple Kriging ◽  
Pollen Records

AbstractClimate change and human activities influence the development of ecosystems, with human demand of ecosystem services altering both land use and land cover. Fossil pollen records provide time series of vegetation characteristics, and the aim of this study was to create spatially continuous reconstructions of land cover through the Holocene in southern Sweden. The Landscape Reconstruction Algorithm (LRA) was applied to obtain quantitative reconstructions of pollen-based vegetation cover at local scales, accounting for pollen production, dispersal, and deposition mechanisms. Pollen-based local vegetation estimates were produced from 41 fossil pollen records available for the region. A comparison of 17 interpolation methods was made and evaluated by comparing with current land cover. Simple kriging with cokriging using elevation was selected to interpolate the local characteristics of past land cover, to generate more detailed reconstructions of trends and degree of variability in time and space than previous studies based on pollen data representing the regional scale. Since the Mesolithic, two main processes have acted to reshape the land cover of southern Sweden, originally mostly covered by broad-leaved forests. The natural distribution limit of coniferous forest has moved southward during periods with colder climate and retracted northward during warmer periods, and human expansion in the area and agrotechnological developments has led to a gradually more open landscape, reaching maximum openness at the beginning of the 20th century. The recent intensification of agriculture has led to abandonment of less fertile agricultural fields and afforestation with conifer forest.

scholarly journals Spatially explicit statistical modeling of random and systematic land cover transitions in the main grassland plain of Nech Sar National Park, Ethiopia

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Kiros Tsegay Deribew
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Statistical Modeling ◽  
National Park ◽  
Spatial Extent ◽  
Aerial Photographs ◽  
Woody Vegetation ◽  
Spatially Explicit ◽  
Strong Signal ◽  
The Past

AbstractThe main grassland plain of Nech Sar National Park (NSNP) is a federally managed protected area in Ethiopia designated to protect endemic and endangered species. However, like other national parks in Ethiopia, the park has experienced significant land cover change over the past few decades. Indeed, the livelihoods of local populations in such developing countries are entirely dependent upon natural resources and, as a result, both direct and indirect anthropogenic pressures have been placed on natural parks. While previous research has looked at land cover change in the region, these studies have not been spatially explicit and, as a result, knowledge gaps in identifying systematic transitions continue to exist. This study seeks to quantify the spatial extent and land cover change trends in NSNP, identify the strong signal transitions, and identify and quantify the location of determinants of change. To this end, the author classifies panchromatic aerial photographs in 1986, multispectral SPOT imagery in 2005, and Sentinel imagery in 2019. The spatial extent and trends of land cover change analysis between these time periods were conducted. The strong signal transitions were systematically identified and quantified. Then, the basic driving forces of the change were identified. The locations of these transitions were also identified and quantified using the spatially explicit statistical model. The analysis revealed that over the past three decades (1986–2019), nearly 52% of the study area experienced clear landscape change, out of which the net change and swap change attributed to 39% and 13%, respectively. The conversion of woody vegetation to grassland (~ 5%), subsequently grassland-to-open-overgrazed land (28.26%), and restoration of woody vegetation (0.76%) and grassland (0.72%) from riverine forest and open-overgrazed land, respectively, were found to be the fully systematic transitions whereas the rest transitions were recorded either partly systematic or random transitions. The location of these most systematic land cover transitions identified through the spatially explicit statistical modeling showed drivers due to biophysical conditions, accessibility, and urban/market expansions, coupled with successive government policies for biodiversity management, geo-politics, demographic, and socioeconomic factors. These findings provide important insights into biodiversity loss, land degradation, and ecosystem disruption. Therefore, the model for predicted probability generally suggests a 0.75 km and 0.72 km buffers which are likely to protect forest and grassland from conversion to grassland and open-overgrazed land, respectively.

scholarly journals Novel methods of estimating relative pollen productivity: A key parameter for reconstruction of past land cover from pollen records

2019 ◽  
Vol 43 (6) ◽  
pp. 731-753 ◽  
Author(s):  
Yiman Fang ◽  
Chunmei Ma ◽  
M Jane Bunting
Keyword(s):  
Land Cover ◽  
Empirical Data ◽  
Alternative Methods ◽  
Model Parameters ◽  
Value Analysis ◽  
Pollen Productivity ◽  
Tropical China ◽  
The Relationship ◽  
Pollen Records ◽  
Key Parameter

Reconstructing land cover from pollen data using mathematical models of the relationship between them has the potential to translate the many thousand pollen records produced over the last 100 years (over 2300 radiocarbon-dated pollen records exist for the UK alone) into formats relevant to ecologists, archaeologists and climate scientists. However, the reliability of these reconstructions depends on model parameters. A key parameter is Relative Pollen Productivity (RPP), usually estimated from empirical data using ‘Extended R Value analysis’ (ERV analysis). Lack of RPP estimates for many regions is currently a major limitation on reconstructing global land cover. We present two alternatives to ERV analysis, the Modified Davis Method and an iteration method, which use the same underlying model of the relationship between pollen and vegetation to estimate RPP from empirical data, but with different assumptions. We test them in simulation against ERV analysis, and use a case study of a problematic empirical dataset to determine whether they have the potential to increase the speed and geographic range of RPP estimation. The two alternative methods are shown to perform at least as well as ERV analysis in simulation. We also present new RPP estimates from southeastern sub-tropical China for nine taxa estimated using the Modified Davis Method. Adding these two methods to the ‘toolkit’ for land cover reconstruction from pollen records opens up the possibility to estimate a key parameter from existing datasets with less field time than using current methods. This can both speed up the inclusion of more of the globe in past land cover mapping exercises such as the PAGES Landcover6k working group and improve our understanding of how this parameter varies within a single taxon and the factors control that variation.

scholarly journals Synthesizing East African land-cover change over the past 6000 years

2016 ◽  
Vol 24 (1) ◽  
pp. 39-39 ◽  
Author(s):  
Rob Marchant ◽  
Stephen Rucina
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
East African ◽  
The Past

scholarly journals Quantifying Land Cover Change Due to Petroleum Exploration and Production in the Haynesville Shale Region Using Remote Sensing

2015 ◽  
Vol 6 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Daniel Unger ◽  
I-Kuai Hung ◽  
Kenneth Farrish ◽  
Darinda Dans
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Landscape Change ◽  
Oil And Gas ◽  
Agricultural Land ◽  
Landscape Fragmentation ◽  
Petroleum Exploration ◽  
Forest Land ◽  
The Past ◽  
Exploration And Production

The Haynesville Shale lies under areas of Louisiana and Texas and is one of the largest gas plays in the U.S. Encompassing approximately 2.9 million ha, this area has been subject to intensive exploration for oil and gas, while over 90% of it has traditionally been used for forestry and agriculture. In order to detect the landscape change in the past few decades, Landsat Thematic Mapper (TM) imagery for six years (1984, 1989, 1994, 2000, 2006, and 2011) was acquired. Unsupervised classifications were performed to classify each image into four cover types: agriculture, forest, well pad, and other. Change detection was then conducted between two classified maps of different years for a time series analysis. Finally, landscape metrics were calculated to assess landscape fragmentation. The overall classification accuracy ranged from 84.7% to 88.3%. The total amount of land cover change from 1984 to 2011 was 24%, with 0.9% of agricultural land and 0.4% of forest land changed to well pads. The results of Patch-Per-Unit area (PPU) index indicated that the well pad class was highly fragmented, while agriculture (4.4-8.6 per sq km) consistently showed a higher magnitude of fragmentation than forest (0.8-1.4 per sq km).

Goal and products of PAGES LandCover6k 2018-2020: Past Global Land Cover and Land Use for Climate Modelling

2020 ◽  
Author(s):  
Marie-Jose Gaillard ◽  
Andria Dawson ◽  
Ralph Fyfe ◽  
Esther Githumbi ◽  
Emily Hammer ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Carbon Cycle ◽  
Climate Model ◽  
Climate Modelling ◽  
Model Simulations ◽  
Lulc Changes ◽  
The Past ◽  
Per Capita ◽  
Past Land Use

<p>The question of whether prehistoric human impacts on land cover (i.e. anthropogenic land cover change due to land use, LULC) were sufficiently large to have a major impact on regional cli-mates is still a matter of debate. Climate model simulations have shown that LULC datasets can have large regional impacts on climate in recent and prehistoric time<sup> (1)</sup>. But there are major differences between the available LULC scenarios/datasets such as HYDE (History Database of the Global En-vironment) and Kaplan’s KK10 <sup>(2)</sup>, and diagnoses of inferred carbon-cycle impacts show that none of the scenarios are realistic <sup>(3)</sup>. The only way to provide a useful assessment of the potential for LULC changes to affect climate in the past, is to provide more realistic LULC data based on palaeovegetation and archaeological evidence to improve the LULC datasets used in climate modelling<sup>(4)</sup>. We use the REVEALS model to reconstruct LC from pollen data at a regional scale, and archaeological data to map LU types and distribution, and estimate per capita LU. The archaeology-based LU maps and per-capita LU estimates are used to improve LULC datasets. Pollen-based REVEALS LC estimates are then used to evaluate/validate the new, improved LULC datasets. These new datasets will be used to implement past land use in palaeoclimate and carbon cycle model simulations. Such simulations are necessary to assess the impact of LULC changes in the past and understand the effect of ecosys-tem management on future climate. We present results from five years of PAGES LandCover6k activities. </p><p>(1) Strandberg G, Kjellström E, Poska A, Wagner S, Gaillard M-J et al. (2014) Regional climate model sim-ulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation. Clim. Past 10, 661–680.<br>(2) Gaillard M-J, Sugita S, Mazier F et al (2010) Holocene land-cover reconstructions for studies on land cover-climate feedbacks. Clim. Past 6, 483-499.<br>(3) Stocker B, Yud Z, Massae C, Joos F (2017) Holocene peatland and ice-core data constraints on the tim-ing and magnitude of CO2 emissions from past land use. www.pnas.org/cgi/doi/10.1073/ pnas.1613889114.<br>(4) Harrison S P, Gaillard M-J, Stocker B D, Vander Linden M, Klein Goldewijk K, Boles O, Braconnot P, Dawson A, Fluet-Chouinard E, Kaplan J O, Kastner T, Pausata F S R, Robinson E, Whitehouse N J, Madella M, and Morrison K D (2019) Development and testing of scenarios for implementing Holocene LULC in Earth Sys-tem Model Experiments, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-125, in review, 2019.</p><p><sup> </sup></p><p> </p><p> </p>

scholarly journals Terminology as a key uncertainty in net land use and land cover change carbon flux estimates

2014 ◽  
Vol 5 (1) ◽  
pp. 177-195 ◽  
Author(s):  
J. Pongratz ◽  
C. H. Reick ◽  
R. A. Houghton ◽  
J. I. House
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Carbon Flux ◽  
Scientific Application ◽  
The Past ◽  
Different Types ◽  
Definition Of ◽  
Specific Definition ◽  
Terminological Confusion

Abstract. Reasons for the large uncertainty in land use and land cover change (LULCC) emissions go beyond recognized issues related to the available data on land cover change and the fact that model simulations rely on a simplified and incomplete description of the complexity of biological and LULCC processes. The large range across published LULCC emission estimates is also fundamentally driven by the fact that the net LULCC flux is defined and calculated in different ways across models. We introduce a conceptual framework that allows us to compare the different types of models and simulation setups used to derive land use fluxes. We find that published studies are based on at least nine different definitions of the net LULCC flux. Many multi-model syntheses lack a clear agreement on definition. Our analysis reveals three key processes that are accounted for in different ways: the land use feedback, the loss of additional sink capacity, and legacy (regrowth and decomposition) fluxes. We show that these terminological differences, alone, explain differences between published net LULCC flux estimates that are of the same order as the published estimates themselves. This has consequences for quantifications of the residual terrestrial sink: the spread in estimates caused by terminological differences is conveyed to those of the residual sink. Furthermore, the application of inconsistent definitions of net LULCC flux and residual sink has led to double-counting of fluxes in the past. While the decision to use a specific definition of the net LULCC flux will depend on the scientific application and potential political considerations, our analysis shows that the uncertainty of the net LULCC flux can be substantially reduced when the existing terminological confusion is resolved.

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