Showing papers by "Atsushi Tsunekawa published in 2019"

Analysis of long-term gully dynamics in different agro-ecology settings

Abstract: Gully erosion is one of the main causes of land degradation, particularly in the drought-prone regions of Ethiopia. This study assessed spatio-temporal changes of gully length and density in watershed pairs in Guder, Aba Gerima, and Dibatie sites, which are representative highland, midland, and lowland agro-ecologies in the Upper Blue Nile basin of Ethiopia. Aerial photographs (1957, 1982) and very high resolution satellite images (QuickBird, IKONOS, Worldview-2, SPOT-7, and Pleiades) of the six watersheds, along with field survey results, were used in the analyses. The aerial photographs were scanned and orthorectified using ENVI 4.3 image analysis software, and gullies were mapped by visual image interpretation in the ArcGIS environment. Rates of increase in gully length in Guder (36.9 m yr−1) and Aba Gerima (33.6 m yr−1) were almost double the rate in Dibatie (17.8 m yr−1) from 1957 to 2016 or 2017, and over the same period, gully density similarly increased by 5.9, 5.4, and 3.7 m ha−1 in Guder, Aba Gerima, and Dibatie, respectively. The higher rates in Guder and Aba Gerima reflect the long history of cultivation and human settlement in those sites, whereas agricultural activity became widespread in Dibatie only after implementation of the national resettlement program in the 1980s. Moreover, although gully density tended to increase over time in all six watersheds, in the three watersheds (one in each paired watershed) where soil and water conservation measures had been introduced, the rate of increase was lower than in those where no such measures were implemented. In addition, gully distribution was linked to land use and landscape position; gully density was higher in cultivated areas and where slope gradients were gentle. The results of this study indicate that careful site-specific identification of factors controlling gully initiation and development is crucial so that appropriate management strategies can be developed for these three sites and for other areas with similar agro-ecologies in the Upper Blue Nile basin.

Exploring Drivers of Livelihood Diversification and Its Effect on Adoption of Sustainable Land Management Practices in the Upper Blue Nile Basin, Ethiopia

Abstract: Land degradation poses a major threat to agricultural production and food security in Ethiopia, and sustainable land management (SLM) is key in dealing with its adverse impacts. This paper examines the covariates that shape rural livelihood diversification and examines their effects on the intensity of adoption of SLM practices. Household-level data were collected in 2017 from 270 households in three drought-prone watersheds located in northwestern Ethiopia. We used the Herfindahl–Simpson diversity index to explore the extent of livelihood diversification. A stochastic dominance ordering was also employed to identify remunerative livelihood activities. A multivariate probit model was employed to estimate the probability of choosing simultaneous livelihood strategies, and an ordered probit model was estimated to examine the effect of livelihood diversification on the adoption intensity of SLM practices. In addition to mixed cropping and livestock production, the production of emerging cash crops (e.g., Acacia decurrens for charcoal, and khat) dominated the overall income generation of the majority of farmers. Stress/shock experience, extent of agricultural intensification, and agro-ecology significantly affected the probability of choosing certain livelihood strategies. Livelihood diversification at the household level was significantly associated with the dependency ratio, market distance, credit access, extension services, membership in community organizations, level of income, and livestock ownership. A greater extent of livelihood diversification had a significant negative effect on adopting a greater number of SLM practices, whereas it had a positive effect on lower SLM adoption intensity. Overall, we found evidence that having greater livelihood diversification could prompt households not to adopt more SLM practices. Livelihood initiatives that focus on increasing shock resilience, access to financial support mechanisms, improving livestock production, and providing quality extension services, while also considering agro-ecological differences, are needed. In addition, development planners should take into account the livelihood portfolios of rural households when trying to implement SLM policies and programs.

Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

Abstract: Ethiopia has experienced more than 10 major drought episodes since the 1970s. Evidence has shown that climate change exacerbates the situation and presents a daunting challenge to predominantly rain-fed agricultural livelihoods. The aim of this study was to analyze the extent and sources of smallholder famers’ livelihood vulnerability to climate change/variability in the Upper Blue Nile basin. We conducted a household survey (n = 391) across three distinct agroecological communities and a formative composite index of livelihood vulnerability (LVI) was constructed. The Mann–Kendall test and the standard precipitation index (SPI) were employed to analyze trends of rainfall, temperature, and drought prevalence for the period from 1982 to 2016. The communities across watersheds showed a relative difference in the overall livelihood vulnerability index. Aba Gerima (midland) was found to be more vulnerable, with a score of 0.37, while Guder (highland) had a relatively lower LVI with a 0.34 index score. Given similar exposure to climate variability and drought episodes, communities’ livelihood vulnerability was mainly attributed to their low adaptive capacity and higher sensitivity indicators. Adaptive capacity was largely constrained by a lack of participation in community-based organizations and a lack of income diversification. This study will have practical implications for policy development in heterogeneous agroecological regions for sustainable livelihood development and climate change adaptation programs.

Quantifying Grazing Intensity Using Remote Sensing in Alpine Meadows on Qinghai-Tibetan Plateau

Abstract: Remote sensing data have been widely used in the study of large-scale vegetation activities, which have important significance in estimating grassland yields, determining grassland carrying capacity, and strengthening the scientific management of grasslands. Remote sensing data are also used for estimating grazing intensity. Unfortunately, the spatial distribution of grazing-induced degradation remains undocumented by field observation, and most previous studies on grazing intensity have been qualitative. In our study, we tried to quantify grazing intensity using remote sensing techniques. To achieve this goal, we conducted field experiments at Gansu Province, China, which included a meadow steppe and a semi-arid region. The correlation between a vegetation index and grazing intensity was simulated, and the results demonstrated that there was a significant negative correlation between NDVI and relative grazing intensity (p < 0.05). The relative grazing intensity increased with a decrease in NDVI, and when the relative grazing intensity reached a certain level, the response of NDVI to relative grazing intensity was no longer sensitive. This study shows that the NDVI model can illustrate the feasibility of using a vegetation index to monitor the grazing intensity of livestock in free-grazing mode. Notably, it is feasible to use the remote sensing vegetation index to obtain the thresholds of livestock grazing intensity.

A New Application of Random Forest Algorithm to Estimate Coverage of Moss-Dominated Biological Soil Crusts in Semi-Arid Mu Us Sandy Land, China

Abstract: Biological soil crusts (BSCs) play an essential role in desert ecosystems. Knowledge of the distribution and disappearance of BSCs is vital for the management of ecosystems and for desertification researches. However, the major remote sensing approaches used to extract BSCs are multispectral indices, which lack accuracy, and hyperspectral indices, which have lower data availability and require a higher computational effort. This study employs random forest (RF) models to optimize the extraction of BSCs using band combinations similar to the two multispectral BSC indices (Crust Index-CI; Biological Soil Crust Index-BSCI), but covering all possible band combinations. Simulated multispectral datasets resampled from in-situ hyperspectral data were used to extract BSC information. Multispectral datasets (Landsat-8 and Sentinel-2 datasets) were then used to detect BSC coverage in Mu Us Sandy Land, located in northern China, where BSCs dominated by moss are widely distributed. The results show that (i) the spectral curves of moss-dominated BSCs are different from those of other typical land surfaces, (ii) the BSC coverage can be predicted using the simulated multispectral data (mean square error (MSE) < 0.01), (iii) Sentinel-2 satellite datasets with CI-based band combinations provided a reliable RF model for detecting moss-dominated BSCs (10-fold validation, R2 = 0.947; ground validation, R2 = 0.906). In conclusion, application of the RF algorithm to the Sentinel-2 dataset can precisely and effectively map BSCs dominated by moss. This new application can be used as a theoretical basis for detecting BSCs in other arid and semi-arid lands within desert ecosystems.

Influence of raindrop size on rainfall intensity, kinetic energy, and erosivity in a sub-humid tropical area: a case study in the northern highlands of Ethiopia

Abstract: Rainfall kinetic energy (KE) is an important factor in soil erosion models. Particle detachment from the soil surface depends on raindrop KE. Therefore, it is essential to evaluate the drop-size distribution (DSD) and KE of rainfall to understand soil erosion and runoff generation. In this study, we used an optical disdrometer to investigate the influence of DSD on the intensity (I), KE, and erosivity of rainfall at Bahir Dar, in northwestern Ethiopia. We recorded 1-min rainfall observations during 42 events, with I ranging from 0.82 to 46.27 mm h−1. The median raindrop diameter (D50), which ranged between 1.14 and 4.33 mm, was significantly correlated with I (R2 = 0.96; P < 0.001). We developed indices of rainfall KE as a function of time (KEtime) and of the KE content (KEcon). The best-fit relationships between KEtime and I were equally strong: R2 = 0.96 (P < 0.001) for both a linear function and a polynomial function. KEcon and I were most strongly related for a logarithmic function (R2 = 0.98; P < 0.001), followed by power (R2 = 0.95; P < 0.001) and polynomial (R2 = 0.93; P < 0.001) functions. The KEcon measured at Bahir Dar ranged from 7.4 to 32.43 J m −2 mm−1, whereas KEtime ranged from 38.34 to 1992.64 J m−2 h−1 for the observed range of I. The potential erosivity of rainfall events was found to be well correlated to smaller rainfalls depths (R2 = 0.60, P < 0.05). Our results suggest that, though empirical models are easy to use since they require readily available rainfall data, KE rather than rainfall depth should be used to estimate erosivity in the study area and regions of northwestern Ethiopia with similar characteristics. Moreover, the reasons why different measuring methods in the same area and similar methods in different areas provide different kinetic energy results are analyzed and discussed.

Effects of the Diet Inclusion of Common Vetch Hay Versus Alfalfa Hay on the Body Weight Gain, Nitrogen Utilization Efficiency, Energy Balance, and Enteric Methane Emissions of Crossbred Simmental Cattle.

Abstract: A low nitrogen utilization efficiency (NUE, the ratio of retained N to N intake) and high methane (CH4) emissions of ruminants can lead to potentially high diet protein wastage and directly contribute to global warming. Diet manipulation is the most effective way to improve NUE or reduce CH4 emissions. This study investigated how replacing oat hay with alfalfa hay (AH) or common vetch hay (CVH) with different proportions (20% (20) and 40% (40) of the total dry matter (DM) allowance) affects the body weight gain (BWG), NUE, and CH4 emissions of crossbred Simmental cattle. The forage dry matter intake (DMI) and the total DMI of cattle fed on a CVH40 diet were significantly higher than the values for those fed on AH20 or AH40 diets (p < 0.05). There were no differences in the BWG for the four treatments observed, however, nutrient digestibility significantly decreased in the AH40 diet as compared with the AH20 diet (p < 0.05). The NUE was significantly lower in AH40 than in CVH20. The CH4 emissions were significantly lower for the CVH40 diet than with the AH20 diet (p < 0.05). Our findings suggest that a 20% AH and 40% CVH substitution for oat hay are the optimal proportions to maintain the BWG, NUE, nutrient digestibility, and reduce the CH4 emissions of crossbred Simmental cattle. Overall, CVH has a greater potential to reduce CH4 emissions than AH.

A New Application of Random Forest Algorithm to Estimate Coverage of Moss-Dominated Biological Soil Crusts in Semi-Arid Mu Us Sandy Land, China

Abstract: Biological soil crusts (BSCs) play an essential role in desert ecosystems. Knowledge of the distribution and disappearance of BSCs is vital for the management of ecosystems and for desertification researches. However, the major remote sensing approaches used to extract BSCs are multispectral indices, which lack accuracy, and hyperspectral indices, which have lower data availability and require a higher computational effort. This study employs random forest (RF) models to optimize the extraction of BSCs using band combinations similar to the two multispectral BSC indices (Crust Index-CI; Biological Soil Crust Index-BSCI), but covering all possible band combinations. Simulated multispectral datasets resampled from in-situ hyperspectral data were used to extract BSC information. Multispectral datasets (Landsat-8 and Sentinel-2 datasets) were then used to detect BSC coverage in Mu Us Sandy Land, located in northern China, where BSCs dominated by moss are widely distributed. The results show that (i) the spectral curves of moss-dominated BSCs are different from those of other typical land surfaces, (ii) the BSC coverage can be predicted using the simulated multispectral data (mean square error (MSE) < 0.01), (iii) Sentinel-2 satellite datasets with CI-based band combinations provided a reliable RF model for detecting moss-dominated BSCs (10-fold validation, R2 = 0.947; ground validation, R2 = 0.906). In conclusion, application of the RF algorithm to the Sentinel-2 dataset can precisely and effectively map BSCs dominated by moss. This new application can be used as a theoretical basis for detecting BSCs in other arid and semi-arid lands within desert ecosystems.

Method for Classifying Behavior of Livestock on Fenced Temperate Rangeland in Northern China.

Abstract: Different livestock behaviors have distinct effects on grassland degradation. However, because direct observation of livestock behavior is time- and labor-intensive, an automated methodology to classify livestock behavior according to animal position and posture is necessary. We applied the Random Forest algorithm to predict livestock behaviors in the Horqin Sand Land by using Global Positioning System (GPS) and tri-axis accelerometer data and then confirmed the results through field observations. The overall accuracy of GPS models was 85% to 90% when the time interval was greater than 300-800 s, which was approximated to the tri-axis model (96%) and GPS-tri models (96%). In the GPS model, the linear backward or forward distance were the most important determinants of behavior classification, and nongrazing was less than 30% when livestock travelled more than 30-50 m over a 5-min interval. For the tri-axis accelerometer model, the anteroposterior acceleration (-3 m/s2) of neck movement was the most accurate determinant of livestock behavior classification. Using instantaneous acceleration of livestock body movement more precisely classified livestock behaviors than did GPS location-based distance metrics. When a tri-axis model is unavailable, GPS models will yield sufficiently reliable classification accuracy when an appropriate time interval is defined.

Conservation payments, off-farm employment and household welfare for farmers participating in the “Grain for Green” program in China: Empirical evidence from the Loess Plateau

Abstract: The purpose of this paper is to examine the factors (including conservation payments) that influence household decisions to participate in off-farm work and estimate the impact of participation on household welfare under the auspices of the Grain for Green (GfG) program.,The authors used survey data from 225 farm households on the Loess Plateau and addressed the possible sample selection and endogeneity problems by employing a jointly estimated endogenous switching regression (ESR) model.,The findings of this paper are as follows: off-farm participation is positively related to households’ educational attainment and negatively related to their land resource endowment and the presence of children; participation in off-farm work exerts positive effects on household income and per capita household income, but negative effects on farm productivity; and conservation payments show no significant impact on off-farm participation, no significant impact on any of the three household welfare indicators for off-farm non-participant households, but a significantly negative impact for off-farm participant households.,This paper makes two contributions. First, the authors address the selection bias and endogeneity problem of GfG participating households by employing the ESR method and explicitly estimating the treatment effects of off-farm participation on their household welfare. Neglecting these problems leads to biased estimates and misleading policy implications. Second, this analysis stresses the important role of government in reducing market or institutional failure and other barriers that impede farmers’ efficient allocation choices instead of compensating households for conserving sloping land, shedding new light on the most effective policy options to achieve the program’s goals.

Nomadic Movement of Mongolian Gazelles Identified through the Net Squared Displacement Approach

Abstract: The Mongolian gazelles (Procapra gutturosa) that inhabit Mongolia's steppe and semi-desert travel several hundred kilometers each year. Their movement pattern has been considered nomadic, but the details of their movement patterns remain unclear. The aim of this study is to gain an overall perspective of the movement of Mongolian gazelles, which experience diverse environmental conditions with large interannual variations across their continuous distribution range. Based on net squared displacement (NSD) modeling approach, the mixed migration type was the most observed type in the statistical assignment among five movement types, and some movements were assigned into the migration or sedentary. However, NSD seasonal change was irregular in the most annual movements of gazelles, suggesting the nomadic movements of individuals. Most gazelles tracked for more than a year changed their movement types annually, and the movement period differed among individuals. These results also support nomadic movement of the species, although some difficulties of modeling nomadism by the NSD approach were revealed.

Conservation Payments and Technical Efficiency of farm Households Participating in the Grain for Green Program on the Loess Plateau of China

Abstract: This study provides an empirical analysis of household technical efficiency and its determinant factors (especially conservation payments) in the context of the Grain for Green program. On the basis of a sample of 225 farm households on the Loess Plateau in 2007, we estimate household technical efficiency using the data envelopment analysis method. In addition to a traditional ordinary least square (OLS) analysis, quantile regression (QR) analysis is also deployed to explore the possible heterogeneous effects of conservation payments and other variables on the technical efficiency across the quantiles. The results suggest that when off-farm activities are taken into account, households have considerable potential for improving their technical efficiency; OLS analysis shows that conservation payments decrease household efficiency, and the QR analysis suggests that the negative impact is significant only for higher performance households; The presence of children, access of households to leased land markets, credit markets, and extension services all show heterogeneous impacts on household efficiency. On the basis of the findings of the study, policies suggestions to improve the program’s effectiveness are provided.