Understanding traditional agro-ecosystem dynamics in response to systematic transition processes and rainfall variability patterns at watershed-scale in Southern Ethiopia
Introduction
Land cover changes are dynamic processes that occur at varying rates and spatial scales, primarily as a response to socioeconomic forces by human-environment interactions, while less frequently by natural hazards such as floods and wildfires (Campbell and Wynne, 2011, Mölders, 2011). Such human-induced changes are caused by land management decisions principally made at local-scales. Land cover changes (hereafter LCC) can range from modification of its characteristics (an alteration of the cover extent and/or shift in location) without affecting the number of previous information classes, to the extreme case of complete replacement by other cover types, referred to as land conversion (Mölders, 2011).
The terms ‘land cover’ and ‘land use’ are fundamentally different although they are usually used coining both terms together (Lillesand et al., 2015). While ‘land cover’ designates the discernable physical features on the earth’s surface, ‘land use’ defines the economic use of those land cover types (Campbell and Wynne, 2011, Lillesand et al., 2015). Since the study employs remote sensing data and methods, the term ‘land cover’ has been frequently used throughout the paper instead of coining it with the term ‘land use’.
The present study was conducted on a predominantly traditional agroforestry land cover in Southern Ethiopia. This agroforestry principally comprises perennial crops, combined with scattered native and exotic trees. As such, it supports biodiversity conservation, environmental protection and also serves as a potential for carbon sequestration (Kanshie, 2002, Tesemma, 2013). Generally, agroforestry appears to be a favorable land cover, particularly under the phenomenon of global climate change (Verchot et al., 2007). More specifically, the traditional agroforestry in the present study area offers various ecosystem services due to the combination of annual and perennial crops, as well as native and exotic tree species (Abebe and Bongers, 2012, Abebe et al., 2010, Gebrehiwot, 2013, Kanshie, 2002, Mellisse et al., 2018). However, despite its multipurpose environmental and socioeconomic benefits, a growing transition to mono-cropping culture has started to influence the sustainability of this environment-friendly agricultural production system (Abebe and Bongers, 2012, Abebe et al., 2010, Gebrehiwot, 2013, Mellisse et al., 2018). This has occurred due to the cultivation of new cash crops (mainly khat/Catha edulis), eucalyptus plantation (Abebe and Bongers, 2012, Gebrehiwot, 2013, Negash, 2002), and expansion of open-field crops (Abebe and Bongers, 2012). The densely inhabited and rapidly growing population, particularly in the highland parts of the study area has led to a declining farmland size per household, enforcing farmers to increase the proportion of open-field crops, by replacing the more sustainable agroforestry system, to meet their immediate subsistence needs (Abebe and Bongers, 2012). In contrast, while several survey-based studies have indicated a growing land cover transition in this area (Abebe and Bongers, 2012, Abebe et al., 2010, Gebrehiwot, 2013, Mellisse et al., 2018), remote sensing-based spatiotemporal information on land cover dynamics has been lacking. Therefore, the ongoing LCC coupled with the lack of up-to-date information on its spatiotemporal dynamics, calls for multi-temporal evaluation along with examining the underlying systematic or random processes triggering the change.
On the other hand, since the launch of the Landsat program in the 1970s, satellite remote sensing has played a leading role in monitoring land cover dynamics at varying spatiotemporal scales. This has been enhanced by the growing access to the increasing archives of earth observation data and image processing platforms (Keenan et al., 2015, Zhang et al., 2013). Moreover, the growing multi-sensor satellite image data has augmented the availability of satellite-derived rainfall estimates useful for monitoring rainfall dynamics and characterizing meteorological drought events (Bayissa et al., 2017, Sein et al., 2018, Tesfamariam et al., 2019b). Remote sensing has thus become suitable both for land cover change analysis and for the assessment of rainfall variability and drought conditions. Attributed to its repeated imaging of the earth’s surface, remote sensing offers a unique capability in monitoring LCC by tracking gradual processes occurred over time. In addition, analysis of long-term rainfall variability and meteorological drought events based on satellite rainfall products can help to understand its spatial correlation with the patterns of land cover change, with more emphasis on vegetation cover dynamics. Such integrated biophysical information may help to distinguish direct human impacts and climate variability influences, enhancing to gain useful insights on the development of mitigation strategies to alleviate undesired land cover change.
Therefore, based on remotely sensed tools, the main objective of this study was to evaluate multi-temporal land cover change resulted by a random or systematic process, along with assessing the impact of rainfall variability and meteorological drought events on vegetation cover dynamics, in the upper catchment of the Gidabo river basin, Southeastern escarpment of the Ethiopian Rift Valley Lakes Basin. Accordingly, the study has first evaluated inter-category land cover transitions over the last three decades (1985–2018). Then using a post-classification change analysis approach, we have tried to reasonably associate the observed land cover changes with a random or a systematic process. Finally, by correlating their spatiotemporal distribution patterns, the possible effect of rainfall variability and historical meteorological drought events on vegetation cover change was assessed.
Section snippets
Study area
This study was conducted in the upper catchment of the Gidabo river basin, located in the Southeastern Escarpment of the Main Ethiopian Rift. More precisely, it occupies the geographic location from 6.52° to 6.94° north and from 38.24° to 38.64° east. As depicted by the one-arc-second Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM Fig. 1), it is characterized by a wide altitudinal variation, ranging from 1397 to 3213 m above sea level. Since the catchment is dominantly
Multi-temporal evaluation of land cover dynamics
Based on the ground reference data collected for each information class, the multi-temporal Landsat images were subsequently classified into seven land cover types. While the six land cover classes consisting of grassland, forest, annual crops, agroforestry, urban, and wetland were found in the initial time image (i.e. 1985), eucalyptus plantation has emerged as the seventh land cover category since 2000 (Fig. 2).
Land cover classification accuracy assessment
To assess and validate the accuracy of the land cover classification, independent
Agroforestry dynamics and patterns of change
Since the study landscape is part of the extensive traditional agroforestry area in Southern Ethiopia, agroforestry has been found to be the dominant land cover class throughout the study period (1985–2018). It has also exhibited a greater likelihood of persistence, as revealed by its larger gain-to-persistence than its loss-to-persistence ratios (Table 8). However, despite the observed higher proportion of persistence, a discernible reduction in its extent has been detected in some parts of
Conclusions
In this study we evaluated a multi-temporal land cover change that occurred over the last three decades between 1985 and 2018, with more emphasis on the assessment of vegetation cover dynamics as a response to population pressure and rainfall variability patterns. Multi-temporal Landsat images were used for the land cover change analysis, while the assessment of rainfall variability and meteorological drought was performed based on a bias-corrected CHIRPS rainfall product. The study has
Competing interests
The authors declare that they have no competing interests.
Acknowledgments
We are grateful to the Landsat and CHIRPS data providers and to the National Meteorological Agency of Ethiopia (NMA) for availing the required datasets at no cost. We also acknowledge the Ethiopian Space Science and Technology Institute (ESSTI), Entoto Observatory and Research Center (EORC) for the overall institutional support provided throughout the study.
References (55)
- et al.
Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: a case study in Woleka sub-basin
Weather Clim. Extrem.
(2018) Random and systematic land-cover transitions in northern Ghana
Agric. Ecosyst. Environ.
(2006)- et al.
Dynamics of global forest area: results from the FAO Global Forest Resources Assessment 2015
For. Ecol. Manag.
(2015) - et al.
Changes of ecosystem service values in response to land use/land cover dynamics in Munessa–Shashemene landscape of the Ethiopian highlands
Sci. Total Environ.
(2016) - et al.
Analysis of twenty years of categorical land transitions in the Lower Hunter of New South Wales, Australia
Agric. Ecosyst. Environ.
(2010) - et al.
Comparing global vegetation maps with the Kappa statistic
Ecol. Model.
(1992) - et al.
Detecting important categorical land changes while accounting for persistence
Agric. Ecosyst. Environ.
(2004) - et al.
Characterizing the spatiotemporal distribution of meteorological drought as a response to climate variability: the case of rift valley lakes basin of Ethiopia
Weather Clim. Extrem.
(2019) - et al.
Land-use dynamics in enset-based agroforestry homegardens in Ethiopia
- et al.
Spatial and temporal variation in crop diversity in agroforestry homegardens of southern Ethiopia
Agrofor. Syst.
(2010)
Accuracy assessment of land use land cover classification using Google Earth
Am. J. Environ. Prot.
Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico
Appl. Geogr.
Fit-for-purpose: species distribution model performance depends on evaluation criteria – Dutch hoverflies as a case study
PLoS ONE
Identifying systematic land-cover transitions using remote sensing and GIS: the fate of forests inside and outside protected areas of Southwestern Ghana
Environ. Plan. B Plan. Des.
Geographical distributions of spiny pocket mice in South America: insights from predictive models
Glob. Ecol. Biogeogr.
Land cover changes as impacted by spatio-temporal rainfall variability along the Ethiopian Rift Valley escarpment
Reg. Environ. Chang.
Evaluation of satellite-based rainfall estimates and application to monitor meteorological drought for the Upper Blue Nile Basin, Ethiopia
Remote Sens.
Deforestation and land degradation in the Ethiopian highlands: a strategy for physical recovery
Northeast Afr. Stud.
Introduction to Remote Sensing
A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data
Photogramm. Eng. Remote Sens.
The 2007 Population and Housing Census of Ethiopia
Dagucho [Podocarpus falcatus] Is Abbo!’ Wonsho Sacred Sites, Sidama, Ethiopia: Origins, Maintenance Motives, Consequences and Conservation Threats
Aspects of Climate and Water Budget in Ethiopia
Digital Analysis of Remotely Sensed Imagery
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ORCID: 0000-0002-2819-7875.