About 44%of the world’s cocoa is produced in one single country,Côte d’Ivoire.Providing this important raw material,most Ivorian cocoa farmers live in severe poverty,which,despite a multitude of sector interven...About 44%of the world’s cocoa is produced in one single country,Côte d’Ivoire.Providing this important raw material,most Ivorian cocoa farmers live in severe poverty,which,despite a multitude of sector interventions,is still widespread,affecting social and environmental sustainability in cocoa production.In this context,cocoa farmers are still often treated as a homogeneous group of small-scale producers(mainly males),resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’specific conditions appropriately into account.Applying a broader typology approach that combines farm characteristics with farmers’characteristics,this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income(LI)potentials.Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms.To assure gender sensitive analysis,a female-headed farm type was created artificially.The specific characteristics of the identified types were captured using descriptive analysis.Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes.Additionally,a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI.Finally,Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type.Three different types of male-headed farms are identified:type 1(the most productive and diversified farms with larger size),type 2(middle-sized farms with strong focus on cash crops),and type 3(small-sized farms with a good level of diversification for self-consumption).The artificially created type 4 represents female-headed farms with the smallest size.On average,none of these farm types achieves a LI.However,type 1 shows the smallest LI gap,while type 4 is by far the worst.Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms,most notably limited access to land and other material assets.The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system,thereby identifying the need for targeted support interventions.Type-specific recommendations are made,showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.展开更多
Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this stud...Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.展开更多
The biodegradability of chars derived from pyrolysis and hydrothermal carbonisation(HTC) was studied in short-term dynamic incubation experiments under controlled conditions. Carbon dioxide C(CO2) emissions from soil-...The biodegradability of chars derived from pyrolysis and hydrothermal carbonisation(HTC) was studied in short-term dynamic incubation experiments under controlled conditions. Carbon dioxide C(CO2) emissions from soil-char mixtures in combination with solid digestate or mineral nitrogen(N) fertiliser were measured in dynamic chambers for 10 d. Compared to the original material(maize straw), pyrolysis and HTC chars showed significantly lower CO2 emissions and slower decay dynamics; and compared to the soil control, HTC char increased soil respiration to a significant extent, while pyrolysis char did not. The addition of mineral N resulted in a delayed respiration dynamics for HTC char, while the addition of digestate resulted in an increase in the respired CO2 for pyrolysis char and a decrease for HTC char. For the first time, a peculiar two-stage decay kinetics was observed for HTC char,indicating a highly inhomogeneous substrate consisting at least of two C pools.展开更多
To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stok...To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was con- ducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear imple- mentation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale.展开更多
Verticillium dahliae induced wilt disease in strawberry can cause severe yield losses and thus lead to inevitable negative economic impacts. Inoculation of plants with non-pathogenic strains of Verticillium was conduc...Verticillium dahliae induced wilt disease in strawberry can cause severe yield losses and thus lead to inevitable negative economic impacts. Inoculation of plants with non-pathogenic strains of Verticillium was conducted as a biologic control agent (BCA) according to the concept that preoccupation of the ecologic niche rendered strawberry plants immune to infection with soil-borne pathogenic Verticillium. This concept was tested for economic viability in a field trial under commercial conditions. Results were reported for 2 years of field trials under practice conditions in two locations in Brandenburg, Germany. Inoculation was shown to have a positive effect of 20% of plants, while 30% of plants remain unaffected and of equally high vitality. However, 50%-0% of plants were impacted negatively, showing severe wilt symptoms up to total loss. The characteristic progression of wilt symptoms suggested an infestation caused by Phytophtora sp. and other pathogens. Further results showed that the main factor of the side effects was caused by different qualities of plant material in interaction to the inoculation with the BCA and only to a minor extent depended on pre-infestation of soils. We conclude that specific conditions, such as certified plant material or soil analysis for other pathogens besides Verticillium, avoided these side-effects relevant for commercial farming.展开更多
Endophytic bacteria of halophytic plants play essential roles in salt stress tolerance.Therefore,an understanding of the true nature of plant-microbe interactions under extreme conditions is essential.The current stud...Endophytic bacteria of halophytic plants play essential roles in salt stress tolerance.Therefore,an understanding of the true nature of plant-microbe interactions under extreme conditions is essential.The current study aimed to identify cultivable endophytic bacteria associated with the roots and shoots of Seidlitzia rosmarinus Ehrenb.ex Boiss.grown in the salt-affected soil in Uzbekistan and to evaluate their plant beneficial traits related to plant growth stimulation and stress tolerance.Bacteria were isolated from the roots and the shoots of S.rosmarinus using culture-dependent techniques and identified by the 16S rRNA gene.RFLP(Restriction Fragment Length Polymorphism)analysis was conducted to eliminate similar isolates.Results showed that the isolates from the roots of S.rosmarinus belonged to the genera Rothia,Kocuria,Pseudomonas,Staphylococcus,Paenibacillus and Brevibacterium.The bacterial isolates from the shoots of S.rosmarinus belonged to the genera Staphylococcus,Rothia,Stenotrophomonas,Brevibacterium,Halomonas,Planococcus,Planomicrobium and Pseudomonas,which differed from those of the roots.Notably,Staphylococcus,Rothia and Brevibacterium were detected in both roots and shoots,indicating possible migration of some species from roots to shoots.The root-associated bacteria showed higher levels of IAA(indole-3-acetic acid)synthesis compared with those isolated from the shoots,as well as the higher production of ACC(1-aminocyclopropane-1-carboxylate)deaminase.Our findings suggest that halophytic plants are valuable sources for the selection of microbes with a potential to improve plant fitness under saline soils.展开更多
As the COVID-19 pandemic unfolded,questions arose as to whether the pandemic would amplify or pacify tropical deforestation.Early reports warned of increased deforestation rates;however,these studies were limited to a...As the COVID-19 pandemic unfolded,questions arose as to whether the pandemic would amplify or pacify tropical deforestation.Early reports warned of increased deforestation rates;however,these studies were limited to a few months in 2020 or to selected regions.To better understand how the pandemic infl uenced tropical deforestation globally,this study used historical deforestation data(2004–2019)from the Terra-i pantropical land cover change monitoring system to project expected deforestation trends for 2020,which were used to determine whether observed deforestation deviated from expected trajectories after the fi rst COVID-19 cases were reported.Time series analyses were conducted at the regional level for the Americas,Africa and Asia and at the country level for Brazil,Colombia,Peru,the Democratic Republic of Congo and Indonesia.Our results suggest that the pandemic did not alter the course of deforestation trends in some countries(e.g.,Brazil,Indonesia),while it did in others(e.g.,Peru).We posit the importance of monitoring the long-term eff ects of the pandemic on deforestation trends as countries prioritize economic recovery in the aftermath of the pandemic.展开更多
Changes in major climatic elements such as temperature, precipitation and wind distribution have triggered weather-related and geophysical disasters. In recent years, the globe has experienced an increased number of f...Changes in major climatic elements such as temperature, precipitation and wind distribution have triggered weather-related and geophysical disasters. In recent years, the globe has experienced an increased number of floods and landslide events which are said to be the most common among other natural disasters. This study examines the influence of climatic elements on the geo-hydrological disaster which occurred in Hanang district-Tanzania on 3rd December 2023. The study used the primary data collected from 182 respondents. Also, the trend analysis (1981-2023) was conducted using average rainfall from 7 meteorological stations in the study area. Annual and seasonal rainfall as well as a number of rainy days were analyzed. The calculated rainfall data were then used to compute the dimensions of the standardized precipitation anomalies (SPA) which is designated as SPA = (P − P*)/σp. Besides, the temperature was analysed to investigate its trend and trend anomaly. Also, the wind rose statistics for the annual, March to May (MAM) and October to December (OND) for the climatology period of 1991-2020 were analysed so as to examine its contribution to rainfall distribution in Hanang district. The examination of annual rainfall data indicates an upward trend in precipitation levels, accompanied by notable variability in rainfall patterns, including seasonal anomalies and deviations from historical averages. The combination of elevated rainfall, anomalies in rainfall patterns, and potentially unfavourable terrain characteristics may have contributed to devastated geo-hydrological disaster risk. However, future research is recommended that could focus on integrating rainfall and temperature data with comprehensive geo-hydrological susceptibility assessments, considering factors such as terrain stability, land cover and land use practices.展开更多
Interspecific plant-soil feedback(PSF)-the influence of soil conditioned by one plant species on another-is key to ecosystem processes but remains challenging to predict due to complex factors like species origin and ...Interspecific plant-soil feedback(PSF)-the influence of soil conditioned by one plant species on another-is key to ecosystem processes but remains challenging to predict due to complex factors like species origin and phylogenetic relatedness.These aspects are underexplored,limiting our understanding of the mechanisms driving PSFs and their broader implications for ecosystem functioning and species coexistence.To shed light on the role of plant species origin and phylogenetic distance in interspecific PSFs,we conducted a greenhouse experiment with 10 native responding species and soils conditioned by 10 native and 10 exotic species resulting in 20 species pairs.These pairs represented a range of phylogenetic distances between both species,spanning up to 270 million years of evolutionary history since their last common ancestor.Conditioning by both native and exotic species reduced biomass production,with stronger inhibition observed for native-conditioned soils.Native-conditioned soils also exhibited lower phosphorus levels,higher basal and specific respiration,and greater cation exchange capacity,base saturation,and magnesium content compared to exotic-conditioned soils.Contrary to expectations,phylogenetic distance did not influence PSFs,regardless of conditioning species origin.Our findings suggest that co-evolution drives native plants to foster microbial communities with low carbon-use efficiency,highlighting soil biota’s critical role in PSFs.This advances our understanding of interactions between plant species origin and microbial communities and underlines the importance of microbial management for promoting native species and controlling invasives.The lack of phylogenetic distance effects aligns with prior studies,indicating evolutionary relatedness alone does not reliably predict PSF outcomes.展开更多
In this paper we introduce HOTSED,a novel,innovative GIS-based model designed for assessing potential hotspots of sediment dynamics at watershed scale.HOTSED integrates geomorphic spatial information with both structu...In this paper we introduce HOTSED,a novel,innovative GIS-based model designed for assessing potential hotspots of sediment dynamics at watershed scale.HOTSED integrates geomorphic spatial information with both structural and functional properties of connectivity.HOTSED provides a single and intuitive output that depicts the location of sediment source hotspots.Moreover,it enables the identification of“relative hazard”classes for sediment production and related effects.The general methodological framework is based on the initial elaboration of an Inventory Map(IM)of sediment-related landforms and processes,along with the implementation of a corresponding database.Subsequently,we used data stored in the IM to estimate the geomorphic Potential of Sediment Sources(PSS)through a relative scoring system.Furthermore,we computed Structural Sediment Connectivity(STC)and the Potential for Sediment Transport(PST)by combining terrain and hydrological parameters,vegetation roughness,and rainfall erosivity.Afterwards,PSS,STC,and PST components are integrated through a raster-based calculation method yielding the HOTSED model.We tested the HOTSED procedure in the upper Val d’Arda-Mignano watershed,which is a representative geomorphologically highly active Mediterranean area of the Northern Apennines(Italy).Through photointerpretation,terrain analysis,and fieldwork,we mapped sedimentrelated geomorphic features for a total of 4640 ha including:badlands and gullies(0.26%),rill-interrill erosion(15.03%),fluvial erosion(0.03%),landslides(70.06%),litho-structural erosional systems(0.87%),slope deposits(12.56%),and alluvial deposits(1.19%).HOTSED revealed hotspots with a very high hazard potential located near main channels or upstream of the reservoir.These areas are often linked with active landslides highly connected to the drainage system and frequently associated with other processes like bank erosion or surficial soil erosion.The model also highlighted linear hotspots corresponding to drainages flowing alongside or intersecting complex geomorphic systems such as landslides.Furthermore,HOTSED identified areas where sediments are stored in depositional landforms,exhibiting a low hazard potential,considering both low geomorphic potential and sediment connectivity.Our conceptual model is generally applicable but proves to be particularly effective in areas characterized by complex and polygenetic geomorphic systems,such as the Northern Apennines.HOTSED offers a valuable tool for watershed authorities to support sustainable watershed and reservoir management.展开更多
Microplastics are increasingly recognized as a factor of global change. By altering soil inherentproperties and processes, ripple-on effects on plants and their symbionts can be expected.Additionally, interactions wit...Microplastics are increasingly recognized as a factor of global change. By altering soil inherentproperties and processes, ripple-on effects on plants and their symbionts can be expected.Additionally, interactions with other factors of global change, such as drought, can influence theeffect of microplastics. We designed a greenhouse study to examine effects of polyester microfibers,arbuscular mycorrhizal (AM) fungi and drought on plant, microbial and soil responses. We found thatpolyester microfibers increased the aboveground biomass of Allium cepa under well-watered anddrought conditions, but under drought conditions the AM fungal-only treatment reached the highestbiomass. Colonization with AM fungi increased under microfiber contamination, however, plantbiomass did not increase when both AM fungi and fibers were present. The mean weight diameter ofsoil aggregates increased with AM fungal inoculation overall but decreased when the system wascontaminated with microfibers or drought stressed. Our study adds additional support to themounting evidence that microplastic fibers in soil can affect the plant–soil system by promoting plantgrowth, and favoring key root symbionts, AM fungi. Although soil aggregation is usually positivelyinfluenced by plant roots and AM fungi, and microplastic promotes both, our results show that plasticstill had a negative effect on soil aggregates. Even though there are concerns that microplastic mightinteract with other factors of global change, our study revealed no such effect for drought.展开更多
Tire particles(TPs)are a major source of microplastic on land,and considering their chemical composition,they represent a potential hazard for the terrestrial environment.We studied the effectsof TPs at environmentall...Tire particles(TPs)are a major source of microplastic on land,and considering their chemical composition,they represent a potential hazard for the terrestrial environment.We studied the effectsof TPs at environmentally relevant concentrations alongawide concentrationgradient(0–160 mg g^(-1))and tested the effects on plant growth,soil pH and the key ecosystem process of litter decomposition and soil respiration.The addition of TPs negatively affected shoot and root growth already at low concentrations.Tea litter decomposition slightly increased with lower additions of TPs but decreased later on.Soil pH increased until a TP concentration of 80 mg g^(-1) and leveled off afterwards.Soil respiration clearly increased with increasing concentration of added TPs.Plant growth was likely reduced with starting contamination and stopped when contamination reached a certain level in the soil.The presence of TPs altered a number of biogeochemical soil parameters that can have further effects on plant performance.Considering the quantities of yearly produced TPs,their persistence,and toxic potential,we assume that these particles will eventually have a significant impact on terrestrial ecosystems.展开更多
Artificial intelligence and machine learning have been increasingly applied for prediction in agricultural science.However,many models are typically black boxes,meaning we cannot explain what the models learned from t...Artificial intelligence and machine learning have been increasingly applied for prediction in agricultural science.However,many models are typically black boxes,meaning we cannot explain what the models learned from the data and the reasons behind predictions.To address this issue,I introduce an emerging subdomain of artificial intelligence,explainable artificial intelligence(XAI),and associated toolkits,interpretable machine learning.This study demonstrates the usefulness of several methods by applying them to an openly available dataset.The dataset includes the no-tillage effect on crop yield relative to conventional tillage and soil,climate,and management variables.Data analysis discovered that no-tillage management can increase maize crop yield where yield in conventional tillage is<5000 kg/ha and the maximum temperature is higher than 32°.These methods are useful to answer(i)which variables are important for prediction in regression/classification,(ii)which variable interactions are important for prediction,(iii)how important variables and their interactions are associated with the response variable,(iv)what are the reasons underlying a predicted value for a certain instance,and(v)whether different machine learning algorithms offer the same answer to these questions.I argue that the goodness of model fit is overly evaluated with model performance measures in the current practice,while these questions are unanswered.XAI and interpretable machine learning can enhance trust and explainability in AI.展开更多
Aims Plant-plant interactions,being positive or negative,are rec-ognized to be key factors in structuring plant communities.However,it is thought that root competition may be less impor-tant than shoot competition due...Aims Plant-plant interactions,being positive or negative,are rec-ognized to be key factors in structuring plant communities.However,it is thought that root competition may be less impor-tant than shoot competition due to greater size symmetry below-ground.Because direct experimental tests on the importance of root competition are scarce,we aim at elucidating whether root competition may have direct or indirect effects on commu-nity structure.Indirect effects may occur by altering the overall size asymmetry of competition through root-shoot competitive interactions.Methods We used a phytometer approach to examine the effects of root,shoot and total competition intensity and importance on evenness of experimental plant communities.Thereby two different phytom-eter species,Festuca brevipila and Dianthus carthusianorum,were grown in small communities of six grassland species over three levels of light and water availability,interacting with neighbouring shoots,roots,both or not at all.Important Findings We found variation in community evenness to be best explained if root and shoot(but not total)competition were considered.However,the effects were species specific:in Dianthus communities increasing root competition increased plant community evenness,while in Festuca communities shoot competition was the driving force of this evenness response.Competition intensities were influenced by environmental conditions in Dianthus,but not in Festuca phytometer plants.While we found no evidence for root-shoot interactions for neither phytom-eter species root competition in Dianthus communities led to increased allocation to shoots,thereby increasing the potential ability to perform in size-asymmetric competition for light.Our experiment demonstrates the potential role of root competition in structuring plant communities.展开更多
Background:Soil structure is a key indicator of the functioning of soil processes in grasslands,which is influenced by site conditions and management.Methods:In this study,we investigated soil structure and its relati...Background:Soil structure is a key indicator of the functioning of soil processes in grasslands,which is influenced by site conditions and management.Methods:In this study,we investigated soil structure and its relationship with root growth in 31 Leptosols under different grassland management intensities using X-ray microcomputed tomography.A close relationship between land use intensity,soil structure,and root growth was observed.Results:Our results show that land use type affects root development and soil structure.Pastures had more developed roots and more structured soils than meadows and mown pastures.However,all pastures were unfertilized,while meadows and mown pastures had both fertilized and unfertilized plots.Although no significant differences were found in the unfertilized plots,sample size was limited.In particular,fertilization negatively affected root growth and soil structure,resulting in significant differences between fertilized and unfertilized grasslands.Mowing frequency also had an effect on soil physics,but to a much lesser extent than fertilization.Conclusions:Increased land use intensity,characterized by increased fertilization and more frequent mowing,reduces root growth and adversely affects soil structure.Therefore,X-ray microcomputed tomography is a suitable method to investigate the relationship between soil structure and roots in the soil.展开更多
Deep learning and computer vision,using remote sensing and drones,are 2 promising nondestructive methods for plant monitoring and phenotyping.However,their applications are infeasible for many crop systems under tree ...Deep learning and computer vision,using remote sensing and drones,are 2 promising nondestructive methods for plant monitoring and phenotyping.However,their applications are infeasible for many crop systems under tree canopies,such as coffee crops,making it challenging to perform plant monitoring and phenotyping at a large spatial scale at a low cost.This study aims to develop a geographic-scale monitoring method for coffee cherry counting,supported by an artificial intelligence(AI)-powered citizen science approach.The approach uses basic smartphones to take a few pictures of coffee trees;2,968 trees were investigated with 8,904 pictures in Junin and Piura(Peru),Cauca,and Quindio(Colombia)in 2022,with the help of nearly 1,000 smallholder coffee farmers.Then,we trained and validated YOLO(You Only Look Once)v8 for detecting cherries in the dataset in Peru.An average number of cherries per picture was multiplied by the number of branches to estimate the total number of cherries per tree.The model's performance in Peru showed an R^(2)of 0.59.When the model was tested in Colombia,where different varieties are grown in different biogeoclimatic conditions,the model showed an R^(2)of 0.71.The overall performance in both countries reached an R^(2)of 0.72.The results suggest that the method can be applied to much broader scales and is transferable to other varieties,countries,and regions.To our knowledge,this is the first AI-powered method for counting coffee cherries and has the potential for a geographic-scale,multiyear,photo-based phenotypic monitoring for coffee crops in low-income countries worldwide.展开更多
Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can...Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems.We present the Digital Agricultural Knowledge and Information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture.To develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools.The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability levels.To overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources.The approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and settings.Ultimately,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands.展开更多
Adoption rates of soil and water conservation measures remain below the expected levels in Ethiopia despite the considerable investments in reducing land degradation and improving soil fertility.This constitutes one o...Adoption rates of soil and water conservation measures remain below the expected levels in Ethiopia despite the considerable investments in reducing land degradation and improving soil fertility.This constitutes one of the key research agendas in the country.This paper underscores the need for investigating the factors hindering or facilitating the adoption of soil and water conservation measures.The study results presented in this paper are based on cross-section data collected from 408 households in eastern Ethiopia,including field observations of 790 plots selected using a multi-stage sampling procedure.A multivariate probit model was employed to analyse the determinants of adoption of three soil and water conservation measures (stone bund,soil bund,and bench terracing) at the plot level.The study findings reveal that household,socioeconomic,and institution characteristics were the key factors that influenced the adoption of soil bund,stone bund,and bench terracing conservation measures.Furthermore,there was a significant correlation among the three soil and water conservation measures,indicating that the adoption of these measures is interrelated.In particular,the results show that there was a positive correlation between stone bunds and soil bunds.However,the correlations between bench terracing and stone bunds as well as bench terracing and soil bunds were negative (implying substitutability).These results imply that the Government and other relevant organizations that are responsible for reducing land degradation in order to increase agricultural production should support the establishment and strengthening of local institutions to facilitate the adoption of soil and water conservation measures.展开更多
Agriculture and forestry on drained peatlands contribute substantial amounts of anthropogenic greenhouse gas emissions.The transformation of peatland management toward“wet”land use takes on an increasingly critical ...Agriculture and forestry on drained peatlands contribute substantial amounts of anthropogenic greenhouse gas emissions.The transformation of peatland management toward“wet”land use takes on an increasingly critical role in achieving zero net carbon emissions by 2050.Yet,the translation of European Union climate target ambitions into peatland relevancy on emission reduction remains unclear.The study presents an analysis of the current status and future pathways of peatland transformation in European countries.Our data are collected by a survey with 60 experts in 8 countries and a workshop with 16 experts in 3 countries.The analysis shows expected trends for drained peatlands,indicating a shift from drainage-based cropland to grassland or wetland use.Although these trends support emission reduction,nations with lucrative peatland areas are likely to resist shifting to less profitable land uses.Three categories of management practices were identified based on water level.Among them,grassland paludiculture and grassland with elevated water tables are appreciated by experts.The transition pathways for Finland,Germany,and the Netherlands reflect the consensus that peatland emissions have to be reduced drastically.However,differences in soil types,geoclimatic zones,and diverse management approaches among countries pose a challenge when assessing and implementing the potential of mitigation.Experts highlighted the desirability and feasibility of spatial coordination to align the interests of land managers.Similar hurdles appear for the transition pathways,especially missing economic incentives.The transition demands wider public support,financial action,and reconciling differing stakeholder interests along transparent and stringent pathways.展开更多
基金This work was conducted in the frame of the accompanying research on strategies for improving farmer families’incomes and sustainable cocoa production funded by the German Federal Ministry for Economic Cooperation and Development(BMZ).
文摘About 44%of the world’s cocoa is produced in one single country,Côte d’Ivoire.Providing this important raw material,most Ivorian cocoa farmers live in severe poverty,which,despite a multitude of sector interventions,is still widespread,affecting social and environmental sustainability in cocoa production.In this context,cocoa farmers are still often treated as a homogeneous group of small-scale producers(mainly males),resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’specific conditions appropriately into account.Applying a broader typology approach that combines farm characteristics with farmers’characteristics,this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income(LI)potentials.Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms.To assure gender sensitive analysis,a female-headed farm type was created artificially.The specific characteristics of the identified types were captured using descriptive analysis.Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes.Additionally,a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI.Finally,Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type.Three different types of male-headed farms are identified:type 1(the most productive and diversified farms with larger size),type 2(middle-sized farms with strong focus on cash crops),and type 3(small-sized farms with a good level of diversification for self-consumption).The artificially created type 4 represents female-headed farms with the smallest size.On average,none of these farm types achieves a LI.However,type 1 shows the smallest LI gap,while type 4 is by far the worst.Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms,most notably limited access to land and other material assets.The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system,thereby identifying the need for targeted support interventions.Type-specific recommendations are made,showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.
文摘Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.
基金performed within the framework of the SAW project "Biochar in Agriculture:Perspectives for Germany and Malaysia" funded by the Leibniz Association,Germany,within the context of the "Joint Initiative for Research and Innovation"
文摘The biodegradability of chars derived from pyrolysis and hydrothermal carbonisation(HTC) was studied in short-term dynamic incubation experiments under controlled conditions. Carbon dioxide C(CO2) emissions from soil-char mixtures in combination with solid digestate or mineral nitrogen(N) fertiliser were measured in dynamic chambers for 10 d. Compared to the original material(maize straw), pyrolysis and HTC chars showed significantly lower CO2 emissions and slower decay dynamics; and compared to the soil control, HTC char increased soil respiration to a significant extent, while pyrolysis char did not. The addition of mineral N resulted in a delayed respiration dynamics for HTC char, while the addition of digestate resulted in an increase in the respired CO2 for pyrolysis char and a decrease for HTC char. For the first time, a peculiar two-stage decay kinetics was observed for HTC char,indicating a highly inhomogeneous substrate consisting at least of two C pools.
基金the Sino-German research project MAGIM (Matter fluxes in Grasslands of Inner Mongolia as influenced by stocking rate) funded by DFG (German Research Foundation, Research Unit 536)
文摘To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was con- ducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear imple- mentation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale.
文摘Verticillium dahliae induced wilt disease in strawberry can cause severe yield losses and thus lead to inevitable negative economic impacts. Inoculation of plants with non-pathogenic strains of Verticillium was conducted as a biologic control agent (BCA) according to the concept that preoccupation of the ecologic niche rendered strawberry plants immune to infection with soil-borne pathogenic Verticillium. This concept was tested for economic viability in a field trial under commercial conditions. Results were reported for 2 years of field trials under practice conditions in two locations in Brandenburg, Germany. Inoculation was shown to have a positive effect of 20% of plants, while 30% of plants remain unaffected and of equally high vitality. However, 50%-0% of plants were impacted negatively, showing severe wilt symptoms up to total loss. The characteristic progression of wilt symptoms suggested an infestation caused by Phytophtora sp. and other pathogens. Further results showed that the main factor of the side effects was caused by different qualities of plant material in interaction to the inoculation with the BCA and only to a minor extent depended on pre-infestation of soils. We conclude that specific conditions, such as certified plant material or soil analysis for other pathogens besides Verticillium, avoided these side-effects relevant for commercial farming.
基金the Eurasia Program of the Norwegian Centre for Cooperation in Education(CPEA-LT-2016/10095)the German Academic Exchange Service(DAAD)the President's International Fellowship Initiative of the Chinese Academy of Sciences(2018VBA002S).
文摘Endophytic bacteria of halophytic plants play essential roles in salt stress tolerance.Therefore,an understanding of the true nature of plant-microbe interactions under extreme conditions is essential.The current study aimed to identify cultivable endophytic bacteria associated with the roots and shoots of Seidlitzia rosmarinus Ehrenb.ex Boiss.grown in the salt-affected soil in Uzbekistan and to evaluate their plant beneficial traits related to plant growth stimulation and stress tolerance.Bacteria were isolated from the roots and the shoots of S.rosmarinus using culture-dependent techniques and identified by the 16S rRNA gene.RFLP(Restriction Fragment Length Polymorphism)analysis was conducted to eliminate similar isolates.Results showed that the isolates from the roots of S.rosmarinus belonged to the genera Rothia,Kocuria,Pseudomonas,Staphylococcus,Paenibacillus and Brevibacterium.The bacterial isolates from the shoots of S.rosmarinus belonged to the genera Staphylococcus,Rothia,Stenotrophomonas,Brevibacterium,Halomonas,Planococcus,Planomicrobium and Pseudomonas,which differed from those of the roots.Notably,Staphylococcus,Rothia and Brevibacterium were detected in both roots and shoots,indicating possible migration of some species from roots to shoots.The root-associated bacteria showed higher levels of IAA(indole-3-acetic acid)synthesis compared with those isolated from the shoots,as well as the higher production of ACC(1-aminocyclopropane-1-carboxylate)deaminase.Our findings suggest that halophytic plants are valuable sources for the selection of microbes with a potential to improve plant fitness under saline soils.
基金partially funded by Agrilac Resiliente and by Mitig ate+:Research for Low-Emission Food Systemsfunded by the project 18_Ⅲ_106_COL_A_Sustainable productive strategies
文摘As the COVID-19 pandemic unfolded,questions arose as to whether the pandemic would amplify or pacify tropical deforestation.Early reports warned of increased deforestation rates;however,these studies were limited to a few months in 2020 or to selected regions.To better understand how the pandemic infl uenced tropical deforestation globally,this study used historical deforestation data(2004–2019)from the Terra-i pantropical land cover change monitoring system to project expected deforestation trends for 2020,which were used to determine whether observed deforestation deviated from expected trajectories after the fi rst COVID-19 cases were reported.Time series analyses were conducted at the regional level for the Americas,Africa and Asia and at the country level for Brazil,Colombia,Peru,the Democratic Republic of Congo and Indonesia.Our results suggest that the pandemic did not alter the course of deforestation trends in some countries(e.g.,Brazil,Indonesia),while it did in others(e.g.,Peru).We posit the importance of monitoring the long-term eff ects of the pandemic on deforestation trends as countries prioritize economic recovery in the aftermath of the pandemic.
文摘Changes in major climatic elements such as temperature, precipitation and wind distribution have triggered weather-related and geophysical disasters. In recent years, the globe has experienced an increased number of floods and landslide events which are said to be the most common among other natural disasters. This study examines the influence of climatic elements on the geo-hydrological disaster which occurred in Hanang district-Tanzania on 3rd December 2023. The study used the primary data collected from 182 respondents. Also, the trend analysis (1981-2023) was conducted using average rainfall from 7 meteorological stations in the study area. Annual and seasonal rainfall as well as a number of rainy days were analyzed. The calculated rainfall data were then used to compute the dimensions of the standardized precipitation anomalies (SPA) which is designated as SPA = (P − P*)/σp. Besides, the temperature was analysed to investigate its trend and trend anomaly. Also, the wind rose statistics for the annual, March to May (MAM) and October to December (OND) for the climatology period of 1991-2020 were analysed so as to examine its contribution to rainfall distribution in Hanang district. The examination of annual rainfall data indicates an upward trend in precipitation levels, accompanied by notable variability in rainfall patterns, including seasonal anomalies and deviations from historical averages. The combination of elevated rainfall, anomalies in rainfall patterns, and potentially unfavourable terrain characteristics may have contributed to devastated geo-hydrological disaster risk. However, future research is recommended that could focus on integrating rainfall and temperature data with comprehensive geo-hydrological susceptibility assessments, considering factors such as terrain stability, land cover and land use practices.
基金supported by iDiv,funded by the German Research Foundation(DFG-FZT 118,202548816).
文摘Interspecific plant-soil feedback(PSF)-the influence of soil conditioned by one plant species on another-is key to ecosystem processes but remains challenging to predict due to complex factors like species origin and phylogenetic relatedness.These aspects are underexplored,limiting our understanding of the mechanisms driving PSFs and their broader implications for ecosystem functioning and species coexistence.To shed light on the role of plant species origin and phylogenetic distance in interspecific PSFs,we conducted a greenhouse experiment with 10 native responding species and soils conditioned by 10 native and 10 exotic species resulting in 20 species pairs.These pairs represented a range of phylogenetic distances between both species,spanning up to 270 million years of evolutionary history since their last common ancestor.Conditioning by both native and exotic species reduced biomass production,with stronger inhibition observed for native-conditioned soils.Native-conditioned soils also exhibited lower phosphorus levels,higher basal and specific respiration,and greater cation exchange capacity,base saturation,and magnesium content compared to exotic-conditioned soils.Contrary to expectations,phylogenetic distance did not influence PSFs,regardless of conditioning species origin.Our findings suggest that co-evolution drives native plants to foster microbial communities with low carbon-use efficiency,highlighting soil biota’s critical role in PSFs.This advances our understanding of interactions between plant species origin and microbial communities and underlines the importance of microbial management for promoting native species and controlling invasives.The lack of phylogenetic distance effects aligns with prior studies,indicating evolutionary relatedness alone does not reliably predict PSF outcomes.
基金the financial support of the Earth and Environmental Sciences PhD-PON program(Research&Innovation,2014-2020,Education and research for recovery-REACT-EU,DOT1322534-4)of University of Pavia,Department of Earth and Environmental Sciencesthe financial support of the RTDA-PON program(Research&Innovation 2014-2020,Education and research for recovery-REACT-EU,C6-G-32370-3),University of Milano-Bicocca,Department of Earth and Environmental Sciencessupported by the Belmont ABRESO project(https://www.belmontforum.org).
文摘In this paper we introduce HOTSED,a novel,innovative GIS-based model designed for assessing potential hotspots of sediment dynamics at watershed scale.HOTSED integrates geomorphic spatial information with both structural and functional properties of connectivity.HOTSED provides a single and intuitive output that depicts the location of sediment source hotspots.Moreover,it enables the identification of“relative hazard”classes for sediment production and related effects.The general methodological framework is based on the initial elaboration of an Inventory Map(IM)of sediment-related landforms and processes,along with the implementation of a corresponding database.Subsequently,we used data stored in the IM to estimate the geomorphic Potential of Sediment Sources(PSS)through a relative scoring system.Furthermore,we computed Structural Sediment Connectivity(STC)and the Potential for Sediment Transport(PST)by combining terrain and hydrological parameters,vegetation roughness,and rainfall erosivity.Afterwards,PSS,STC,and PST components are integrated through a raster-based calculation method yielding the HOTSED model.We tested the HOTSED procedure in the upper Val d’Arda-Mignano watershed,which is a representative geomorphologically highly active Mediterranean area of the Northern Apennines(Italy).Through photointerpretation,terrain analysis,and fieldwork,we mapped sedimentrelated geomorphic features for a total of 4640 ha including:badlands and gullies(0.26%),rill-interrill erosion(15.03%),fluvial erosion(0.03%),landslides(70.06%),litho-structural erosional systems(0.87%),slope deposits(12.56%),and alluvial deposits(1.19%).HOTSED revealed hotspots with a very high hazard potential located near main channels or upstream of the reservoir.These areas are often linked with active landslides highly connected to the drainage system and frequently associated with other processes like bank erosion or surficial soil erosion.The model also highlighted linear hotspots corresponding to drainages flowing alongside or intersecting complex geomorphic systems such as landslides.Furthermore,HOTSED identified areas where sediments are stored in depositional landforms,exhibiting a low hazard potential,considering both low geomorphic potential and sediment connectivity.Our conceptual model is generally applicable but proves to be particularly effective in areas characterized by complex and polygenetic geomorphic systems,such as the Northern Apennines.HOTSED offers a valuable tool for watershed authorities to support sustainable watershed and reservoir management.
基金National Key Project for basic research(973)(2009CB421106)Key Program of Knowledge Innovation of CAS(KZCX2-EW-306)China-EU Corporation Program of Ministry of Science and Technology(MOST)of China(0813)
文摘Microplastics are increasingly recognized as a factor of global change. By altering soil inherentproperties and processes, ripple-on effects on plants and their symbionts can be expected.Additionally, interactions with other factors of global change, such as drought, can influence theeffect of microplastics. We designed a greenhouse study to examine effects of polyester microfibers,arbuscular mycorrhizal (AM) fungi and drought on plant, microbial and soil responses. We found thatpolyester microfibers increased the aboveground biomass of Allium cepa under well-watered anddrought conditions, but under drought conditions the AM fungal-only treatment reached the highestbiomass. Colonization with AM fungi increased under microfiber contamination, however, plantbiomass did not increase when both AM fungi and fibers were present. The mean weight diameter ofsoil aggregates increased with AM fungal inoculation overall but decreased when the system wascontaminated with microfibers or drought stressed. Our study adds additional support to themounting evidence that microplastic fibers in soil can affect the plant–soil system by promoting plantgrowth, and favoring key root symbionts, AM fungi. Although soil aggregation is usually positivelyinfluenced by plant roots and AM fungi, and microplastic promotes both, our results show that plasticstill had a negative effect on soil aggregates. Even though there are concerns that microplastic mightinteract with other factors of global change, our study revealed no such effect for drought.
文摘Tire particles(TPs)are a major source of microplastic on land,and considering their chemical composition,they represent a potential hazard for the terrestrial environment.We studied the effectsof TPs at environmentally relevant concentrations alongawide concentrationgradient(0–160 mg g^(-1))and tested the effects on plant growth,soil pH and the key ecosystem process of litter decomposition and soil respiration.The addition of TPs negatively affected shoot and root growth already at low concentrations.Tea litter decomposition slightly increased with lower additions of TPs but decreased later on.Soil pH increased until a TP concentration of 80 mg g^(-1) and leveled off afterwards.Soil respiration clearly increased with increasing concentration of added TPs.Plant growth was likely reduced with starting contamination and stopped when contamination reached a certain level in the soil.The presence of TPs altered a number of biogeochemical soil parameters that can have further effects on plant performance.Considering the quantities of yearly produced TPs,their persistence,and toxic potential,we assume that these particles will eventually have a significant impact on terrestrial ecosystems.
基金supported by ZALF Integrated Priority Project(IPP2022)“Co-designing smart,resilient,sustainable agricultural landscapes with cross-scale diversification”,Bundesministerium für Bildung und Forschung(BMBF)Land-Innovation-Lausitz project“Landschaftsinnovationen in der Lausitz für eine klimaangepasste Bioökonomie und naturnahen Bioökonomie-Tourismus”(03WIR3017A)BMBF project“Multi-modale Datenintegration,domänenspezifische Methoden und KI zur Stärkung der Datenkompetenz in der Agrarforschung”(16DKWN089)Brandenburgische Technische Universität Cottbus-Senftenberg GRS cluster project“Integrated analysis of Multifunctional Fruit production landscapes to promote ecosystem services and sustainable land-use under climate change”(GRS2018/19).
文摘Artificial intelligence and machine learning have been increasingly applied for prediction in agricultural science.However,many models are typically black boxes,meaning we cannot explain what the models learned from the data and the reasons behind predictions.To address this issue,I introduce an emerging subdomain of artificial intelligence,explainable artificial intelligence(XAI),and associated toolkits,interpretable machine learning.This study demonstrates the usefulness of several methods by applying them to an openly available dataset.The dataset includes the no-tillage effect on crop yield relative to conventional tillage and soil,climate,and management variables.Data analysis discovered that no-tillage management can increase maize crop yield where yield in conventional tillage is<5000 kg/ha and the maximum temperature is higher than 32°.These methods are useful to answer(i)which variables are important for prediction in regression/classification,(ii)which variable interactions are important for prediction,(iii)how important variables and their interactions are associated with the response variable,(iv)what are the reasons underlying a predicted value for a certain instance,and(v)whether different machine learning algorithms offer the same answer to these questions.I argue that the goodness of model fit is overly evaluated with model performance measures in the current practice,while these questions are unanswered.XAI and interpretable machine learning can enhance trust and explainability in AI.
基金This study was supported by the Leibniz Centre of Agricultural Landscape Research(ZALF e.V.)by the BMBF in the framework of the BIBS project(01LC1501B).
文摘Aims Plant-plant interactions,being positive or negative,are rec-ognized to be key factors in structuring plant communities.However,it is thought that root competition may be less impor-tant than shoot competition due to greater size symmetry below-ground.Because direct experimental tests on the importance of root competition are scarce,we aim at elucidating whether root competition may have direct or indirect effects on commu-nity structure.Indirect effects may occur by altering the overall size asymmetry of competition through root-shoot competitive interactions.Methods We used a phytometer approach to examine the effects of root,shoot and total competition intensity and importance on evenness of experimental plant communities.Thereby two different phytom-eter species,Festuca brevipila and Dianthus carthusianorum,were grown in small communities of six grassland species over three levels of light and water availability,interacting with neighbouring shoots,roots,both or not at all.Important Findings We found variation in community evenness to be best explained if root and shoot(but not total)competition were considered.However,the effects were species specific:in Dianthus communities increasing root competition increased plant community evenness,while in Festuca communities shoot competition was the driving force of this evenness response.Competition intensities were influenced by environmental conditions in Dianthus,but not in Festuca phytometer plants.While we found no evidence for root-shoot interactions for neither phytom-eter species root competition in Dianthus communities led to increased allocation to shoots,thereby increasing the potential ability to perform in size-asymmetric competition for light.Our experiment demonstrates the potential role of root competition in structuring plant communities.
文摘Background:Soil structure is a key indicator of the functioning of soil processes in grasslands,which is influenced by site conditions and management.Methods:In this study,we investigated soil structure and its relationship with root growth in 31 Leptosols under different grassland management intensities using X-ray microcomputed tomography.A close relationship between land use intensity,soil structure,and root growth was observed.Results:Our results show that land use type affects root development and soil structure.Pastures had more developed roots and more structured soils than meadows and mown pastures.However,all pastures were unfertilized,while meadows and mown pastures had both fertilized and unfertilized plots.Although no significant differences were found in the unfertilized plots,sample size was limited.In particular,fertilization negatively affected root growth and soil structure,resulting in significant differences between fertilized and unfertilized grasslands.Mowing frequency also had an effect on soil physics,but to a much lesser extent than fertilization.Conclusions:Increased land use intensity,characterized by increased fertilization and more frequent mowing,reduces root growth and adversely affects soil structure.Therefore,X-ray microcomputed tomography is a suitable method to investigate the relationship between soil structure and roots in the soil.
基金supported by the Brandenburg University of Technology Cottbus-Senftenberg(BTU),Graduate Research School(GRS)cluster project“Integrated analysis of Multifunctional Fruit production landscape to promote ecosystem services and sustainable land-use under climate change”(grant number BTUGRS2018_19)the Croppie funded by Deutsche Gesellschaft fur Internationale Zusammenarbeit(GIZ)(grant number 81275837).
文摘Deep learning and computer vision,using remote sensing and drones,are 2 promising nondestructive methods for plant monitoring and phenotyping.However,their applications are infeasible for many crop systems under tree canopies,such as coffee crops,making it challenging to perform plant monitoring and phenotyping at a large spatial scale at a low cost.This study aims to develop a geographic-scale monitoring method for coffee cherry counting,supported by an artificial intelligence(AI)-powered citizen science approach.The approach uses basic smartphones to take a few pictures of coffee trees;2,968 trees were investigated with 8,904 pictures in Junin and Piura(Peru),Cauca,and Quindio(Colombia)in 2022,with the help of nearly 1,000 smallholder coffee farmers.Then,we trained and validated YOLO(You Only Look Once)v8 for detecting cherries in the dataset in Peru.An average number of cherries per picture was multiplied by the number of branches to estimate the total number of cherries per tree.The model's performance in Peru showed an R^(2)of 0.59.When the model was tested in Colombia,where different varieties are grown in different biogeoclimatic conditions,the model showed an R^(2)of 0.71.The overall performance in both countries reached an R^(2)of 0.72.The results suggest that the method can be applied to much broader scales and is transferable to other varieties,countries,and regions.To our knowledge,this is the first AI-powered method for counting coffee cherries and has the potential for a geographic-scale,multiyear,photo-based phenotypic monitoring for coffee crops in low-income countries worldwide.
基金This work was made possible through funding from the Digital Agriculture Knowledge and Information System(DAKIS)Project(ID:FKZ 031B0729A)financed by the German Federal Ministry of Education and Research(BMBF).Sincere thanks to Amir Armaghan for his amazing sketches on the DAKIS GUI,enabling us to approach the work from the user's perspective.We acknowledge the valuable contributions of Stefan Zachaeus,Sebastian Möller and Nils Niemann on the design of the DAKIS back end.We thank the many other members of the DAKIS crew that one way or another contribute expertise and input to the development of the DAKIS.
文摘Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems.We present the Digital Agricultural Knowledge and Information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture.To develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools.The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability levels.To overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources.The approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and settings.Ultimately,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands.
基金the Africa Economic Research Consortium(AERC),German Academic Exchange Service(DAAD)and Haramaya University for funding the study and production of this paper.
文摘Adoption rates of soil and water conservation measures remain below the expected levels in Ethiopia despite the considerable investments in reducing land degradation and improving soil fertility.This constitutes one of the key research agendas in the country.This paper underscores the need for investigating the factors hindering or facilitating the adoption of soil and water conservation measures.The study results presented in this paper are based on cross-section data collected from 408 households in eastern Ethiopia,including field observations of 790 plots selected using a multi-stage sampling procedure.A multivariate probit model was employed to analyse the determinants of adoption of three soil and water conservation measures (stone bund,soil bund,and bench terracing) at the plot level.The study findings reveal that household,socioeconomic,and institution characteristics were the key factors that influenced the adoption of soil bund,stone bund,and bench terracing conservation measures.Furthermore,there was a significant correlation among the three soil and water conservation measures,indicating that the adoption of these measures is interrelated.In particular,the results show that there was a positive correlation between stone bunds and soil bunds.However,the correlations between bench terracing and stone bunds as well as bench terracing and soil bunds were negative (implying substitutability).These results imply that the Government and other relevant organizations that are responsible for reducing land degradation in order to increase agricultural production should support the establishment and strengthening of local institutions to facilitate the adoption of soil and water conservation measures.
基金in part through funding by the PEATWISE project(https://www.eragas.eu/en/eragas/research-projects/peatwise.htm)under the FACCE ERA-GAS Research Programme(under the European Union’s Horizon 2020 Research&Innovation Programme,grant agreement no.696356)the support of the Wet Net BB project(Management and Biomass Utilization of Wet Fens:Network of Model and Demonstration Projects in Peatland Regions of Brandenburg),funded by the Federal Ministry of Food and Agriculture through the Climate and Transformation Fund
文摘Agriculture and forestry on drained peatlands contribute substantial amounts of anthropogenic greenhouse gas emissions.The transformation of peatland management toward“wet”land use takes on an increasingly critical role in achieving zero net carbon emissions by 2050.Yet,the translation of European Union climate target ambitions into peatland relevancy on emission reduction remains unclear.The study presents an analysis of the current status and future pathways of peatland transformation in European countries.Our data are collected by a survey with 60 experts in 8 countries and a workshop with 16 experts in 3 countries.The analysis shows expected trends for drained peatlands,indicating a shift from drainage-based cropland to grassland or wetland use.Although these trends support emission reduction,nations with lucrative peatland areas are likely to resist shifting to less profitable land uses.Three categories of management practices were identified based on water level.Among them,grassland paludiculture and grassland with elevated water tables are appreciated by experts.The transition pathways for Finland,Germany,and the Netherlands reflect the consensus that peatland emissions have to be reduced drastically.However,differences in soil types,geoclimatic zones,and diverse management approaches among countries pose a challenge when assessing and implementing the potential of mitigation.Experts highlighted the desirability and feasibility of spatial coordination to align the interests of land managers.Similar hurdles appear for the transition pathways,especially missing economic incentives.The transition demands wider public support,financial action,and reconciling differing stakeholder interests along transparent and stringent pathways.
