Soil Cover in the Eastern Part of the Dried Bed of the Aral Sea

The greatest environmental disaster in Central Asiathe drying up of the Aral Seahas led to the formation of a new terrain, extending over 2.7 million hectares in Uzbekistan. This newly formed terrain is dynamically developing, with emerging soil formations replacing bottom sediments. This paper analyzes the results of a study on soil formation in the eastern part of the dried-up seabed, focusing on the influence of natural processes occurring there.

Trends of Land Use and Land Cover Change in the Savannah Ecological of the Protected Area Reserve Partielle de Dosso, Niger

Information on the dynamics of savannah is important to a country's plan to overcome the problems of uncontrolled development and environmental hazards. Taking the reserve partielle de Dosso, Niger as the case study area, this paper analyzed the long-term land use land cover change from 2002 to 2022. Satellite images were processed by using Google Earth Engine (GEE). Therefore, four major land cover classes were identified based on spectral characteristics of Land sat, namely, built-up, vegetation, cropland, bare land and water. The result revealed that barren and built-up areas increased at the expense of vegetation and water. From the four major land use land cover the large area is covered by vegetation which comprises about 192963.5 hectares followed by cropland and water consisting of 32506.43 and 1596.4 hectares respectively. The built-up area gained substantial area (most) during the study period. The reduction in some of the land cover/uses underlines the dangerous trend of the pressure poised by population growth and the changing functionality. Land cover change is influenced by a variety of societal factors operating on several spatial and temporal levels. The area estimates and spatial distributions of the LULC classes produced from the current study will assist local authorities, managers, and other stakeholders in decision-making and planning regarding forest land cover and uses.

Analysis of a landfill cover without geomembrane using varied particle sizes of recycled concrete

Previous studies have demonstrated the effectiveness of a novel three-layer landfill cover system constructed with recycled concrete aggregates(RCAs)without geomembrane in both laboratory and field.However,no systematic investigation has been carried out to optimize the combination of the particle sizes for fine-grained RCAs(FRC)and coarse-grained RCAs(CRC)that can be used for the three-layer landfill cover system.The aim of this paper is to assist engineers in designing the three-layer landfill cover system under a rainfall of 100-year return period in humid climate conditions using an easily controlled soil parameter D10 of RCAs.The numerical study reveals that when D10 of FRC increases from 0.05 mm to 0.16 mm,its saturated permeability increases by 10 times.As a result,a larger amount of rainwater infiltrates into the cover system,causing a higher lateral diversion in both the top FRC and middle CRC layers.No further changes in the lateral diversion are observed when the D10 value of FRC is larger than 0.16 mm.Both the particle sizes of FRC and CRC layers are shown to have a minor influence on the percolation under the extreme rainfall event.This implies that the selection of particle sizes for the FRC and CRC layers can be based on the availability of materials.Although it is well known that the bottom layer of the cover system should be constructed with very fine-grained soils if possible,this study provides an upper limit to the particle size that can be used in the bottom layer(D10 not larger than 0.02 mm).With this limit,the three-layer system can still minimize the water percolation to meet the design criterion(30 mm/yr)even under a 100-year return period of rainfall in humid climates.

Uncovering the miRNA-mediated regulatory network involved in Ma bamboo(Dendrocalamus latiflorus)de novo shoot organogenesis

Bamboo is an important non-timber forest product and is well-known for its reluctance to regenerate.Recently we have established a de novo shoot organogenesis(DNSO)protocol in Ma bamboo(Dendrocalamus latiflorus)and revealed the transcriptomic dynamics during Ma bamboo regeneration,which suggested the potential roles of Ma bamboo microRNAs(DlamiRNAs)in this process.However,how DlamiRNAs regulate bamboo DNSO is poorly understood.Here we performed integrated analysis with sRNAome,degradome,and transcriptome sequencing by using samples covering the four stages of the bamboo DNSO process.A total of 727 DlamiRNAs showed differential expression during the bamboo DNSO process,and the core DlamiRNA-DlamRNA-mediated regulatory networks for bamboo DNSO were constructed.Based on the results,DlamiR156 was selected for further functional characterization of its potential roles in bamboo DNSO.Transgenic bamboos with increased DlamiR156 levels exhibited an enhancement in their regeneration efficiency.Conversely,when DlamiR156 levels were downregulated,the regeneration efficiencies of transgenic bamboos decreased.Our findings show that the DlamiRNA-mediated regulatory pathways are significant in the process of bamboo regeneration and will contribute to our understanding of the molecular mechanisms governing plant organogenesis in a more comprehensive manner.

The Research on the Psychological Tactic of Covering the Dagger With a Smile

Thirty-Six Stratagems is one of the most important military works of ancient China.As the name of the book,it totally includes 36 stratagems that can be used in many different fields such as military,business,and politics.Covering the dagger with a smile is one of the most common ones in these stratagems.At the same time,it is the most insidious one.As a kind of psychological tactic,it usually acts as the secret weapon of the weak.Though this stratagem should not be seen as a kind of predominant strategy,it is still worth being researched deeply,because knowing more about this psychological tactic will offer a good reference for the researchers of ancient art of war.

求解Covering问题的拟物方法——NP难度问题的一个处理途径

本文提出的算法模拟了由万有引力和屏蔽现象所引起的力学过程.这种拟物的方案可为许多NP难度的问题得出有价值的近似算法.该算法对拟物类型的选择与现代递归论中的有穷损害优先方法的精神是一致的.

Land use and cover change and influencing factor analysis in the Shiyang River Basin,China

Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and social economy.Rapid economic development and climate change have resulted in significant changes in land use and cover.The Shiyang River Basin,located in the eastern part of the Hexi Corridor in China,has undergone significant climate change and LUCC over the past few decades.In this study,we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991,1995,2000,2005,2010,2015,and 2020 based on Landsat images.We validated the land use and cover data in 2015 from the random forest classification results(this study),the high-resolution dataset of annual global land cover from 2000 to 2015(AGLC-2000-2015),the global 30 m land cover classification with a fine classification system(GLC_FCS30),and the first Landsat-derived annual China Land Cover Dataset(CLCD)against ground-truth classification results to evaluate the accuracy of the classification results in this study.Furthermore,we explored and compared the spatiotemporal patterns of LUCC in the upper,middle,and lower reaches of the Shiyang River Basin over the past 30 years,and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural(evapotranspiration,precipitation,temperature,and surface soil moisture)and anthropogenic(nighttime light,gross domestic product(GDP),and population)factors.The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015,GLC_FCS30,and CLCD datasets in both overall and partial validations.Moreover,the classification results in this study exhibited a high level of agreement with the ground truth features.From 1991 to 2020,the area of bare land exhibited a decreasing trend,with changes primarily occurring in the middle and lower reaches of the basin.The area of grassland initially decreased and then increased,with changes occurring mainly in the upper and middle reaches of the basin.In contrast,the area of cropland initially increased and then decreased,with changes occurring in the middle and lower reaches.The LUCC was influenced by both natural and anthropogenic factors.Climatic factors and population contributed significantly to LUCC,and the importance values of evapotranspiration,precipitation,temperature,and population were 22.12%,32.41%,21.89%,and 19.65%,respectively.Moreover,policy interventions also played an important role.Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years,with the ecological environment improving in the last 10 years.This suggests that governance efforts in the study area have had some effects,and the government can continue to move in this direction in the future.The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar arid and semi-arid areas.

Glacier area change (1993-2019) and its relationship to debris cover, proglacial lakes, and morphological parameters in the Chandra-Bhaga Basin, Western Himalaya, India

Glacier inventories serve as critical baseline data for understanding the impacts of climate change on glaciers.The present study maps the outlines of glaciers in the Chandra-Bhaga Basin(western Himalaya)for the years 1993,2000,2010,and 2019 using Landsat Thematic Mapper(TM),Enhanced Thematic Mapper(ETM),and Operational Land Imager(OLI)datasets.A total of 251 glaciers,each having an area above 0.5 km^(2),were identified,which include 216 clean-ice and 35 debris-covered glaciers.Area changes are estimated for three periods:1993-2000,2000-2010,and 2010-2019.The total glacierized area was 996±62 km^(2) in 1993,which decreased to 973±70 km^(2) in 2019.The mean rate of glacier area loss was higher in the recent decade(2010-2019),at 0.036 km^(2),compared to previous decades(0.029 km^(2) in 2000-2010 and 0.025 km^(2) in 1993-2000).Supraglacial debris cover changes are also mapped over the period of 1993 and 2019.It is found that the supraglacial debris cover increased by 14.12±2.54 km^(2)(15.2%)during 1993-2019.Extensive field surveys on Chhota Shigri,Panchi II,Patsio,Hamtah,Mulkila,and Yoche Lungpa glaciers were carried out to validate the glacier outlines and supraglacial debris cover estimated using satellite datasets.Controls of various morphological parameters on retreat were also analyzed.It is observed that small,clean ice,south oriented glaciers,and glaciers with proglacial lakes are losing area at faster rates than other glaciers in the basin.

Changes in Spring Snow Cover over the Eastern and Western Tibetan Plateau and Their Associated Mechanism

The spring snow cover(SC)over the western Tibetan Plateau(TP)(TPSC)(W_TPSC)and eastern TPSC(E_TPSC)have displayed remarkable decreasing and increasing trends,respectively,during 1985–2020.The current work investigates the possible mechanisms accounting for these distinct TPSC changes.Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures,while the increase in E_TPSC is closely linked to enhanced precipitation.Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP.The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP.Conversely,anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific,leading to an increase in snowfall over the eastern TP.Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions.Springtime warming of the subtropical North Atlantic(NA)sea surface temperature(SST)induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP.Furthermore,the decline in winter sea ice(SIC)over the Barents Sea exerts a persistent warming influence on the atmosphere,inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring.Additionally,an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia,which further promotes more snowfall over eastern TP.

Characteristics of the microbial communities regulate soil multi-functionality under different cover crop amendments in Ultisol

The use of cover crops is a promising strategy for influencing the soil microbial consortium,which is essential for the delivery of multiple soil functions(i.e.,soil multifunctionality).Nonetheless,relatively little is known about the role of the soil microbial consortium in mediating soil multifunctionality under different cover crop amendments in dryland Ultisols.Here,we assessed the multifunctionality of soils subjected to four cover crop amendments(control,non-amended treatment;RD,radish monoculture;HV,hairy vetch monoculture;and RDHV,radish-hairy vetch mixture),and we investigated the contributions of soil microbial richness,network complexity,and ecological clusters to soil multifunctionality.Our results demonstrated that cover crops whose chemical composition differed from that of the main plant crop promoted higher multifunctionality,and the radish-hairy vetch mixture rendered the highest enhancement.We obtained evidence that changes in soil microbial richness and network complexity triggered by the cover crops were associated with higher soil multifunctionality.Specifically,specialized microbes in a key ecological cluster(ecological cluster 2)of the soil microbial network were particularly important for maintaining soil multifunctionality.Our results highlight the importance of cover crop-induced variations in functionally important taxa for promoting the soil multifunctionality of dryland Ultisols.

Distribution assessment of soil erosion with revised RUSLE model in Tianshan Mountains

aSoil degradation caused by soil erosion is one of the world's most critical environmental issues.Soil erosion in the Tianshan Mountains has caused various environmental problems in the surrounding areas.This study used remote sensing data to analyze the distribution of the factors influencing soil erosion,and the revised universal soil loss equation(RUSLE)to calculate the total amount and distribution characteristics of soil erosion in the Tianshan Mountains in 2019.Due to the large error of RUSLE in soil erosion estimation in mountainous areas,this study modified RUSLE equation based on the characteristics of snow cover in the Tianshan Mountains.The results show that the average soil erosion was 1690.3 t/(km^(2)·year),of which insignificant erosion,slight erosion and moderate erosion accounted for 42,8%,22.4%and 9.9%,respectively.Severe erosion and above accounted for 13.3%.The accuracy of the soil erosion modulus calculated by the RUSLE was only 61.9%,with an average error of 1631.9 t/(km^(2)·year).The average error of the double-coefficient correction method was 1259.1 t/(km^(2)·year),and the average error of the modified formula method was reduced by 40.3%compared with the RUSLE,reaching 973.7 t/(km^(2)·year),and its accuracy reached 76.2%.Very severe erosion and catastrophic erosion are distributed on mountain ridges with higher elevation and on the northern area with higher precipitation.Snow cover has a certain inhibitory effect on soil erosion,and snow cover in alpine mountains is a factor that cannot be ignored in soil erosion research.

Persistent Variations in the East Asian Trough from March to April and the Possible Mechanism

The East Asian trough(EAT)profoundly influences the East Asian spring climate.In this study,the relationship of the EATs among the three spring months is investigated.Correlation analysis shows that the variation in March EAT is closely related to that of April EAT.Extended empirical orthogonal function(EEOF)analysis also confirms the co-variation of the March and April EATs.The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April.Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature(SST)pattern over the North Atlantic and the SST anomaly over the tropical Indian Ocean.The dipole SST pattern over the North Atlantic,with one center east of Newfoundland Island and another east of Bermuda,could trigger a Rossby wave train to influence the EAT in March−April.The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence the atmospheric circulation over the tropical western Pacific,subsequently impacting the southern part of the EAT in March−April.Besides the SST factors,the Northeast Asian snow cover could change the regional thermal conditions and lead to persistent EAT anomalies from March to April.These three impact factors are generally independent of each other,jointly explaining large variations in the EAT EEOF1.Moreover,the signals of the three factors could be traced back to February,consequently providing a potential prediction source for the EAT variation in March and April.

Comprehending drivers of land use land cover change from 1999 to 2021 in the Pithoragarh District,Kumaon Himalaya,Uttarakhand,India

The Himalayan region has been experiencing stark impacts of climate change,demographic and livelihood pattern changes.The analysis of land use and land cover(LULC)change provides insights into the shifts in spatial and temporal patterns of landscape.These changes are the combined effects of anthropogenic and natural/climatic factors.The present study attempts to monitor and comprehend the main drivers behind LULC changes(1999-2021)in the Himalayan region of Pithoragarh district,Uttarakhand.Pithoragarh district is a border district,remotely located in the north-east region of Uttarakhand,India.The study draws upon primary and secondary data sources.A total of 400 household surveys and five group discussions from 38 villages were conducted randomly to understand the climate perception of the local community and the drivers of change.Satellite imagery,CRU(Climatic Research Unit)climate data and climate perception data from the field have been used to comprehensively comprehend,analyze,and discuss the trends and reasons for LULC change.GIS and remote sensing techniques were used to construct LULC maps.This multifaceted approach ensures comprehensive and corroborated information.Five classes were identified and formed viz-cultivation,barren,settlement,snow,and vegetation.Results show that vegetation and builtup have increased whereas cultivation,barren land,and snow cover have decreased.The study further aims to elucidate the causes behind LULC changes in the spatially heterogeneous region,distinguishing between those attributed to human activities,climate shifts,and the interconnected impacts of both.The study provides a comprehensive picture of the study area and delivers a targeted understanding of local drivers and their potential remedies by offering a foundation for formulating sustainable adaptation policies in the region.

Multiscale Fusion Transformer Network for Hyperspectral Image Classification

Convolutional neural network(CNN)has excellent ability to model locally contextual information.However,CNNs face challenges for descripting long-range semantic features,which will lead to relatively low classification accuracy of hyperspectral images.To address this problem,this article proposes an algorithm based on multiscale fusion and transformer network for hyperspectral image classification.Firstly,the low-level spatial-spectral features are extracted by multi-scale residual structure.Secondly,an attention module is introduced to focus on the more important spatialspectral information.Finally,high-level semantic features are represented and learned by a token learner and an improved transformer encoder.The proposed algorithm is compared with six classical hyperspectral classification algorithms on real hyperspectral images.The experimental results show that the proposed algorithm effectively improves the land cover classification accuracy of hyperspectral images.

Changes in snow cover extent in the Central Taurus Mountains from 1981 to 2021 in relation to temperature, precipitation, and atmospheric teleconnections

The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. Results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.

Spatiotemporal Changes of Snow Depth in Western Jilin,China from 1987 to 2018

Seasonal snow cover is a key global climate and hydrological system component drawing considerable attention due to glob-al warming conditions.However,the spatiotemporal snow cover patterns are challenging in western Jilin,China due to natural condi-tions and sparse observation.Hence,this study investigated the spatiotemporal patterns of snow cover using fine-resolution passive mi-crowave(PMW)snow depth(SD)data from 1987 to 2018,and revealed the potential influence of climate factors on SD variations.The results indicated that the interannual range of SD was between 2.90 cm and 9.60 cm during the snowy winter seasons and the annual mean SD showed a slightly increasing trend(P>0.05)at a rate of 0.009 cm/yr.In snowmelt periods,the snow cover contributed to an increase in volumetric soil water,and the change in SD was significantly affected by air temperature.The correlation between SD and air temperature was negative,while the correlation between SD and precipitation was positive during December and March.In March,the correlation coefficient exceeded 0.5 in Zhenlai,Da’an,Qianan,and Qianguo counties.However,the SD and precipitation were neg-atively correlated over western Jilin in October,and several subregions presented a negative correlation between SD and precipitation in November and April.

Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Spatiotemporal characteristics and driving mechanisms of land use/land cover(LULC)changes in the Jinghe River Basin,China

Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.

Adding Value to Crop Production Systems by Integrating Forage Cover Crop Grazing

In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, NE, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd-1d-1. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd-1d-1. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd-1d-1. Based on the 3-year average animal gains valued at $1.32 kg-1, mean net return ($ ha-1 yr-1) was $62.15 for triticale and $22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA.

Modelling Land Use/Land Cover Change of River Rwizi Catchment, South-Western Uganda Using GIS and Markov Chain Model

Analysis of catchment Land use/Land cover (LULC) change is a vital tool in ensuring sustainable catchment management. The study analyzed land use/land cover changes in the Rwizi catchment, south western Uganda from 1989-2019 and projected the trend by 2040. Landsat images, field observations, key informant interviews and focus group discussions were used to collect data. Changes in cropland, forestland, built up area, grazing land, wetland and open water bodies were analyzed in ArcGIS version 10.2.2 and ERDAS IMAGINE 14 software and a Markov chain model. All the LULC classes increased in area except grazing land. Forest land and builtup area between 2009-2019 increased by 370.03% and 229.53% respectively. Projections revealed an increase in forest land and builtup area by 2030 and only built up area by 2040. LULCC in the catchment results from population pressure, reduced soil fertility and high value of agricultural products.