Relationships among multiple aspects of agriculture's environmental impact and productivity: a meta-analysis to guide sustainable agriculture

An overview of approaches for assessing the environmental sustainability of diets - a scoping review for Nordic Nutrition Recommendations 2023

Assessing the environmental impacts of food, food systems and diets is highly complex due to the multitude of processes involved, the uncertainty in assessment models, the variability in production systems and the large range of products available. No single assessment method alone can provide a complete evidence base. The increasing number of Life Cycle Assessment and food system analyses, and more recently the integration of planetary boundaries offer insights from which we can draw some robust high-level conclusions, whilst recognising there is a need for more detailed analysis to capture the inherent nuances of more location and context-specific situations. Despite the complexity of assessing the environmental sustainability of food, diets and food systems, there are a number of key considerations that could be used to guide this process, and in doing so, they help to increase utility of the outcomes and limit unintended adverse consequences. We identified five key considerations that can be applied (consider the thresholds, consider the system, consider the variables, consider the context and consider the spillover) to ensure assessments are comprehensive.

A machine learning approach to map the potential agroecological complexity in an indigenous community of Colombia

Agroecological systems are potential solutions to the environmental challenges of intensive agriculture. Indigenous communities, such as the Kamëntšá Biyá and Kamëntšá Inga from the Sibundoy Valley (SV) in Colombia, have their own ancient agroecological systems called chagras. However, they are threatened by population growth and expansion of intensive agriculture. Establishing new chagras or enhancing existing ones faces impediments such as the necessity for continuous monitoring and mapping of agroecological potential. However, this method is often costly and time consuming. To address this limitation, we created a digital map of the Biodiversity Management Coefficient (BMC) (as a proxy of agroecological potential) using Machine Learning. We utilized 15 environmental predictors and in-situ BMC data from 800 chagras to train an XGBoost model capable of predicting a multiclass BMC structure with 70% accuracy. This model was deployed across the study area to map the extent and spatial distribution of BMC classes, providing detailed information on potential areas for new agroecological chagras as well as areas unsuitable for this purpose. This map captured footprints of past and present disturbance events in the SV, revealing its usefulness for agroecological planning. We highlight the most significant predictors and their optimal values that trigger higher BMC status.

Analysis of the beneficial effects of prior soybean cultivation to the field on corn yield and soil nitrogen content

Corn-soybean rotation is a cropping pattern to optimize crop structure and improve resource use efficiency, and nitrogen (N) fertilizer application is an indispensable tool to increase corn yields. However, the effects of N fertilizer application levels on corn yield and soil N storage under corn-soybean rotation have not been systematically studied. The experimental located in the central part of the Songnen Plain, a split-zone experimental design was used with two planting patterns of continuous corn (CC) and corn-soybean rotations (RC) in the main zone and three N application rates of 0, 180, and 360 kg hm-2 of urea in the secondary zone. The research has shown that RC treatments can enhance plant growth and increase corn yield by 4.76% to 79.92% compared to CC treatments. The amount of N fertilizer applied has a negative correlation with yield increase range, and N application above 180 kg hm-2 has a significantly lower effect on corn yield increase. Therefore, a reduction in N fertilizer application may be appropriate. RC increased soil N storage by improving soil N-transforming enzyme activity, improving soil N content and the proportion of soil organic N fractions. Additionally, it can improve plant N use efficiency by 1.4%-5.6%. Soybeans grown in corn-soybean rotations systems have the potential to replace more than 180 kg hm-2 of urea application. Corn-soybean rotation with low N inputs is an efficient and sustainable agricultural strategy.

Improving crop salt tolerance through soil legacy effects

Soil salinization poses a critical problem, adversely affecting plant development and sustainable agriculture. Plants can produce soil legacy effects through interactions with the soil environments. Salt tolerance of plants in saline soils is not only determined by their own stress tolerance but is also closely related to soil legacy effects. Creating positive soil legacy effects for crops, thereby alleviating crop salt stress, presents a new perspective for improving soil conditions and increasing productivity in saline farmlands. Firstly, the formation and role of soil legacy effects in natural ecosystems are summarized. Then, the processes by which plants and soil microbial assistance respond to salt stress are outlined, as well as the potential soil legacy effects they may produce. Using this as a foundation, proposed the application of salt tolerance mechanisms related to soil legacy effects in natural ecosystems to saline farmlands production. One aspect involves leveraging the soil legacy effects created by plants to cope with salt stress, including the direct use of halophytes and salt-tolerant crops and the design of cropping patterns with the specific crop functional groups. Another aspect focuses on the utilization of soil legacy effects created synergistically by soil microorganisms. This includes the inoculation of specific strains, functional microbiota, entire soil which legacy with beneficial microorganisms and tolerant substances, as well as the application of novel technologies such as direct use of rhizosphere secretions or microbial transmission mechanisms. These approaches capitalize on the characteristics of beneficial microorganisms to help crops against salinity. Consequently, we concluded that by the screening suitable salt-tolerant crops, the development rational cropping patterns, and the inoculation of safe functional soils, positive soil legacy effects could be created to enhance crop salt tolerance. It could also improve the practical significance of soil legacy effects in the application of saline farmlands.

Knowledge domain and research progress in the field of crop rotation from 2000 to 2020: a scientometric review

As one of the most fundamental and prevalent agronomic practices, crop rotation is of great significance for the optimization of regional planting structure and sustainable agricultural development. Therefore, crop rotation has attracted continuous attention from both researchers and producers worldwide. In recent years, many review articles have been published in the field of crop rotation. However, since most reviews usually focus on specialized directions and topics, only few systematic quantitative reviews and comprehensive analysis can fully determine the state of research. To address this knowledge gap, we present a scientometric review to determine the current research status of crop rotation by using CiteSpace software. The main findings were as follows: (1) From 2000 to 2020, five knowledge domains were identified as representing the intellectual base of crop rotation: (a) synergism and comparison of conservation agriculture measures or other management measures; (b) soil microecology, pest control, weed control, and plant disease control; (c) soil carbon sequestration and greenhouse gases (GHGs) emissions; (d) organic crop rotation and double cropping patterns; and (e) soil properties and crop productivity. (2) Six notable research fronts were identified: (a) plant-soil microbial interactions under crop rotation; (b) integrated effect with minimum soil disturbance and crop retention; (c) carbon sequestration and GHG emission reduction; (d) impact on weed control; (e) heterogeneity of rotation effects under different weather and soil conditions; and (f) comparison between long-term and short-term rotation. Overall, this study provides a comprehensive overview of crop rotation and proposes some future development trends for the researchers.

Biodiversity-based cropping systems: A long-term perspective is necessary

Biodiversity-based cropping systems are an interesting option to address the many challenges that agriculture faces. However, benefits of these systems should not obscure the fact that creating biodiversity-based cropping systems represents a major change for farmers. To address this challenge, we argue that designing biodiversity-based cropping systems requires transforming ecological concepts into technical opportunities. Indeed, integrating ecological concepts such as plant-soil feedback and plant functional traits more strongly into cropping system design offers promising opportunities for the provision of ecosystem services, such as pest and disease control, crop production (including crop yield stability), climate regulation and regulation of soil quality. Accordingly, we demonstrate that designing biodiversity-based cropping systems requires considering not only the short term but also the long term. This would ensure that the expected ecosystem services have enough time to build up and provide their full effects, that the cropping systems are resilient and that they avoid the limitations of short-term assessments, which do not sufficiently consider multi-year effects. Considering long-term consequences of system change - induced by biodiversity - is essential to identify potential trade-offs between ecosystem services, as well as agricultural obstacles to and mechanisms of change. Including farmers and other food-chain actors in cropping system design would help find acceptable compromises that consider not only the provision of ecosystem services, but also other dimensions related to economic viability, workload or the technical feasibility of crops, which are identified as major obstacles to crop diversification. This strategy represents an exciting research front for the development of agroecological cropping systems.

Plant biodiversity promotes sustainable agriculture directly and via belowground effects

While the positive relationship between plant biodiversity and ecosystem functioning (BEF) is well established, the extent to which this is mediated via belowground microbial processes is poorly understood. Growing evidence suggests that plant community structure influences soil microbial diversity, which in turn promotes functions desired for sustainable agriculture. Here, we outline the 'plant-directed' and soil microbe-mediated mechanisms expected to promote positive BEF. We identify how this knowledge can be utilized in plant diversification schemes to maximize ecosystem functioning in agroecosystems, which are typically species poor and sensitive to biotic and abiotic stressors. In the face of resource overexploitation and global change, bridging the gaps between biodiversity science and agricultural practices is crucial to meet food security in the Anthropocene.

Differences in responses of ammonia volatilization and greenhouse gas emissions to straw return and paddy-upland rotations

Paddy-upland rotation and/or straw return could improve soil structure and soil nutrient availability. Different previous crops (wheat and/or oilseed rape) and straw return methods (straw mulching and/or returning) might increase soil organic carbon (C) and total nitrogen (N) content, and further affected the ammonia (NH₃) volatilization, nitrous oxide (N₂O), and methane (CH₄) emissions. A comparison study was carried out in a located field experiment started from 2014 in Central China, aiming to exam seasonal and annual NH₃, N₂O, and CH₄ emissions under the wheat-rice (WR) and oilseed rape-rice (OR) rotations. Three treatments were chosen, i.e., (i) no chemical N fertilizer application (PK), (ii) chemical nitrogen-phosphorus-potassium combination (NPK), and (iii) chemical NPK with straw returning (NPK+St). We found that after 3 years of cultivation, treatment with straw return increased soil total N content and organic C by 15.57% and 17.11% on average as compared with the NPK treatment, respectively. Straw return did not generate additional NH₃ and N₂O losses during the rice season after improving soil fertility. However, CH₄ emissions increased by 45.35% on average after straw return in summer. In winter, straw return increased NH₃, N₂O, and CH₄ emissions by 70.12-85.23%, 16.93-22.97%, and 7.18-9.17%, respectively. The stimulation of NH₃ volatilization mainly occurred in the topdressing stage. Compared with WR rotation, OR rotation had no significant effect on NH₃ and CH₄ emissions, and the change of N₂O emission might be related to the increase of soil C and N pools. The retention of residues in the process of straw decomposition may be the main factor leading to the difference of gas emission between the paddy-upland rotation and straw return.

Fertilizer and pesticide reduction in cherry tomato production to achieve multiple environmental benefits in Guangxi, China

Cherry tomatoes, as a highly profitable vegetable, consume a substantial amount of fertilizer and pesticide compared with other staple crops, which leads to remarkably negative environmental impacts. The optimization of these agricultural inputs to mitigate these environmental burdens and improve cherry tomato yield has drawn little attention. This study used life cycle assessment (LCA) combined with a field investigation to analyze the environmental benefits under optimized fertilizer and pesticide inputs (i.e., reduction of 24.7% nitrogen, 35.6% phosphorus pentoxide, 18.8% potassium oxide, 17.1% organic fertilizer, and 30.9% pesticides) compared to traditional farmer inputs. Results showed that: (1) compared to traditional farmer management, optimized inputs reduced the energy depletion by 24.7%, water depletion by 6.4%, global warming by 28.8%, acidification by 23.7%, aquatic eutrophication by 34.2%, human toxicity by 34.8%, aquatic eco-toxicity by 34.8%, and soil eco-toxicity by 26.7%, respectively; (2) among them, aquatic eco-toxicity and aquatic eutrophication were the major environmental impacts in cherry tomato production and were mainly attributed to chlorothalonil and phosphate fertilizer use, respectively; and (3) optimized inputs decreased the total environmental index and environmental damage cost by 33.8% and 28.1%, respectively, without compromising the yield. These findings provide insight into optimizing fertilizer and pesticide usage to alleviate multiple environmental impacts while maintaining cherry tomato yield and improving economic benefits. Further studies should focus mainly on less harmful pesticide utilization and phosphate use efficiency improvement, which may achieve vegetable production system sustainability in China and also provide a reference value for vegetable production systems in the Global South.

Understanding the effectiveness of policy instruments to encourage adoption of farming practices to improve water quality for the Great Barrier Reef

Governments in Australia and internationally are experimenting with policy instruments to facilitate the adoption of farming practices with reduced environmental impacts. The Great Barrier Reef (Australia) is one such case, where sustained efforts over 20 years have yielded insufficient progress towards targets to reduce the impacts of agriculture on water quality in downstream marine ecosystems. We present a critical review of policy instruments as implemented in Great Barrier Reef catchments. We catalogue the evolving mix of policy instruments employed in reef programs, and examine evidence of the effectiveness of agricultural extension, financial incentives, and direct regulation of farming practices. There is little robust evidence to assess instrument effectiveness, in part due to the evolving mix of the instruments employed, weak program evaluation and heterogeneity of agricultural enterprises. We identify the need to improve the understanding of instrument fit to landholders and enterprises. We recommend a modelling approach to clarify pathways to impact and guide improved policy evaluation.

The Nexus between Environmental Impact and Agricultural Sector Linkages: A Case Study of Pakistan

Agriculture has a substantial environmental impact. However, little research has been conducted on the relationship between agriculture’s environmental impacts and linkages, particularly for the key agriculture-based Pakistani economy. Additionally, the literature on environmental linkages rarely estimates multiple types of linkages in a single study. This study fills these critical research gaps. The study estimates the land, water, nitrogen, and CO2 impacts and linkages of Pakistan’s agriculture sector using an input–output model and the hypothetical extraction method. The results indicated that agriculture directly accounted for approximately 27%, 93%, 92%, and 1% of Pakistan’s total sectoral land, water, nitrogen, and CO2 impacts (LWNC), respectively. While the sector indirectly contributed almost 2%, 0.3%, 0.4%, and 0.4% of Pakistan’s total LWNC. The bulk of direct LWNC impacts were caused by agricultural purchases from downstream sectoral importers. The majority of the indirect LWNC impacts were induced by agriculture’s re-imports. The agricultural purchases from the downstream sector of “Food and Beverages” induced the greatest environmental impact. To ensure sustainable agriculture, particularly in Pakistan, the agriculture sector’s direct and indirect environmental impacts should be reduced not only through better management practices and technology, but also by focusing on intermediate sectoral sources of direct and indirect environmental impacts.

Pesticides in surface waters of tropical river basins draining areas with rice-vegetable rotations in Hainan, China: Occurrence, relation to environmental factors, and risk assessment

Pesticides are heavily applied in rice-vegetable rotations in tropical China, yet publicly available information on the contamination and risk of currently used pesticides (CUPs) and legacy pesticides (LPs) in surface waters of river basins draining these areas is very limited. Therefore, in two tropical river basins (Nandu River and Wanquan River basins) dominated by rice-vegetable rotations in Hainan, China, pesticides were analyzed in 256 surface water samples in wet and dry seasons. Forty-one pesticides were detected, and total concentrations ranged from not detectable to 24.2 μg/L. Carbendazim and imidacloprid were the two most prevalent CUPs, detected in 59.8% and 17.7%, respectively, of surface water samples at concentrations above 0.1 μg/L. Chlorpyrifos was the main LP, detected in 9.0% of samples at a concentration above 0.05 μg/L. The fungicides difenoconazole and emamectin benzoate, the herbicide butachlor, and the insecticide acetamiprid occurred in ≥12.5% samples at concentrations above 0.1 μg/L. Surface waters typically (85.2%) contained 5 to 15 residues, with an average of nine. Seasonally, the concentrations of the 41 pesticides were in the order January > July > November > September. Spatially, the composition of the main CUPs (not LPs) was significantly different depending on position in the drainage, which also changed with seasons. Crop and pest types and wet and dry seasons were the key factors controlling the spatiotemporal distribution of CUPs and LPs in surface waters. On the basis of evaluations of the exposures to individual pesticides and the dominant combinations with ≥8 pesticides, multiple pesticides were likely a significant risk to aquatic organisms, although noncarcinogenic and carcinogenic risks to humans were low. This study provides valuable data to better understand pesticide occurrence and ecological risks in river basins draining areas with rice-vegetable rotation systems in tropical China.

Distinguishing anthropogenic and natural contributions to coproduction of national crop yields globally

Crop production is a crucial ecosystem service that requires a combination of natural and anthropogenic contributions to high and stable yields, which is a coproduction process. We analysed this coproduction based on nationally aggregated data for 15 major crops for 67 countries and the European Union with data for four time steps (2000, 2006, 2010, 2014). We found strong increases in fertilizer use, net capital stock and manure use intensity for lower-middle-income countries and stagnation or decrease of these for high-income countries. We used a multiple linear regression model predicting yield to distinguish the effect of anthropogenic contributions (crop-specific fertilizer use intensity, net capital stock intensity, manure use intensity) and natural contributions (crop-specific agricultural suitability, including soil characteristics, topography and climate). We found that in particular fertilizer use intensity, manure use intensity and agricultural suitability explained variation in yields to a considerable degree (R² = 0.62).

Sown Wildflowers Enhance Habitats of Pollinators and Beneficial Arthropods in a Tomato Field Margin

We evaluated the capacity of selected plants, sown along a processing tomato field margin in central Greece and natural vegetation, to attract beneficial and Hymenoptera pollinating insects and questioned whether they can distract pollinators from crop flowers. Measurements of flower cover and attracted pollinators and beneficial arthropods were recorded from early-May to mid-July, during the cultivation period of the crop. Flower cover was higher in the sown mixtures compared to natural vegetation and was positively correlated with the number of attracted pollinators. The sown Glebionis coronaria, Coriandrum sativum, Anethum graveolens, and Fagopyrum esculentum attracted mainly wild bees, which were the most abundant pollinating insects. In the natural vegetation, Rapistrum rugosum attracted mainly honeybees, while Asteraceae, Convolvulaceae, and Apiaceae species attracted wild bees. Beneficial arthropod abundance and diversity were higher in the sown mixture. Tomato flowers were visited by a small number of wild bees. Their number was not affected by the distance from the field margin, indicating no distraction effect from the sown or natural vegetation flowering plants. Our results suggest that selected flowering plants can improve the field margin habitats for pollinating insects and beneficial arthropods, but more work is needed to elucidate the effect on crop pollination.

An Actor-Oriented Multi-Criteria Assessment Framework to Support a Transition towards Sustainable Agricultural Systems Based on Crop Diversification

Crop diversification represents a key lever to support the development of sustainable agri-food systems. Knowledge on trade-offs and carry over effects from different crop diversification strategies is essential to inform agricultural stakeholders of potential costs and benefits. This knowledge is limited by existing data and performance measures predominantly focused on single crops, rather than complete rotations. Moreover, sustainability performance indicators are often used for assessment purposes, rather than supporting stakeholder learning and actions. A new set of 32 indicators was developed to address these needs, and used to evaluate the environmental, economic and social sustainability of the diversified agricultural systems highlighted in the case studies, which are often characterized by data availability constraints. This approach was tested in France, Germany and Italy to determine a critical ex-post diagnosis of the existing systems, and for the assessment of ex-ante innovative scenarios. The results will be used to support these case studies in the identification and design of more sustainable agricultural systems. Although the framework is based on feasible and proxy indicators, the assessment outcomes have allowed local actors to reflect on the effects generated by the implemented crop diversification strategies. Key issues include trade-offs occurring between optimizing economic and environmental performance.

Selection of Winter Season Crop Pattern for Environmental-Friendly Agricultural Practices in India

Owing to the sudden changes in climatic conditions, monsoon failure, and scarce availability of resources because of population hike, yielding a minimum profit has become a challenge for Indian farmers. This is a severe problem for India, as a major part of the Nation’s Gross Domestic Product (GDP) depends on agriculture. To change this dreadful situation, Indian farmers must employ sustainable agricultural practices in farming, as it will help them to meet their agricultural needs and economic stability. Here, we have built a framework for selecting the ideal crop pattern for Winter Cropping Season (Rabi Season), as crop pattern plays a vital role in the effective function of sustainable agricultural practices. We have used the rough AHP-TOPSIS (Analytical Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution) method for finding the best crop pattern for the Rabi season, by considering all the influential criteria in terms of agriculture sustainability. Our study demonstrates an overall idea to the farmers and stakeholders about attaining maximum crop productivity with optimum use of available resources, without compromising the economic, social, and ecological aspects of agriculture.

Landscape context affects the sustainability of organic farming systems

Organic agriculture promotes sustainability compared to conventional agriculture. However, the multifunctional sustainability benefits of organic farms might be mediated by landscape context. Assessing how landscape context affects sustainability may aid in targeting organic production to landscapes that promote high biodiversity, crop yields, and profitability. We addressed this using a meta-analysis spanning 60 crop types on six continents that assessed whether landscape context affected biodiversity, yield, and profitability of organic vs. conventional agroecosystems. We considered landscape metrics reflecting landscape composition (percent cropland), compositional heterogeneity (number and diversity of cover types), and configurational heterogeneity (spatial arrangement of cover types) across our study systems. Organic sites had greater biodiversity (34%) and profits (50%) than conventional sites, despite lower yields (18%). Biodiversity gains increased as average crop field size in the landscape increased, suggesting organic farms provide a "refuge" in intensive landscapes. In contrast, as crop field size increased, yield gaps between organic and conventional farms increased and profitability benefits of organic farming decreased. Profitability of organic systems, which we were only able to measure for studies conducted in the United States, varied across landscapes in conjunction with production costs and price premiums, suggesting socioeconomic factors mediated profitability. Our results show biodiversity benefits of organic farming respond differently to landscape context compared to yield and profitability benefits, suggesting these sustainability metrics are decoupled. More broadly, our results show that the ecological, but not the economic, sustainability benefits of organic agriculture are most pronounced in more intensive agricultural landscapes.

Effect of straw amount on feed intake and weight gain in growing pigs housed in pens with partly slatted floor

The provision of straw to pigs kept in conventional pens with concrete floor improves animal welfare, but the effects of straw on pigs' performance are unclear. In two steps, we investigated the relationship between amount of straw provided to pigs and measures of performance in a set-up maintaining constant space allowance and controlled room temperature. From approximately 30- to 85-kg BW, pigs were housed in groups of 18 in pens (5.48 m × 2.48 m) with concrete floor (1/3 solid, 1/3 drained and 1/3 slatted). The pens were cleaned manually twice a week, and the designated amount of fresh uncut wheat straw was provided daily onto the solid part of the floor. In the first step, 48 pens were assigned to 10-, 500- or 1000-g straw per pig per day, while in the second step, 90 pens were assigned to 10-, 80-, 150-, 220-, 290-, 360-, 430- or 500-g straw per pig per day. Pigs were weighed at the start of the experimental period at approximately 30 kg and again at approximately 85-kg BW. The average daily gain increased 8.1 g (SEM 17) for every extra 100-g straw added daily (P < 0.001) resulting in 40 g higher average daily gain with 500 compared to 10-g straw per pig per day. The feed conversion ratio was not affected by the amount of straw provided, as the feed intake tended to be higher with increasing amounts of straw. Thus, between 10 and 500 g, the more straw provided, the higher the daily weight gain. As the nutritional value of straw is considered minimal, this result is likely due to improved gut health from the increasing amounts of straw ingested and increased feed intake due to increased stimulation of exploratory behaviour with increasing amounts of straw available, or a combination of these. The observed tendency for a higher feed intake supports this suggestion, but studies are needed to establish the impact of these two contributing factors.

The GA-BPNN-Based Evaluation of Cultivated Land Quality in the PSR Framework Using Gaofen-1 Satellite Data

Rapid and efficient assessment of cultivated land quality (CLQ) using remote sensing technology is of great significance for protecting cultivated land. However, it is difficult to obtain accurate CLQ estimates using the current satellite-driven approaches in the pressure-state-response (PSR) framework, owing to the limitations of linear models and CLQ spectral indices. In order to improve the estimation accuracy of CLQ, this study used four evaluation models (the traditional linear model; partial least squares regression, PLSR; back propagation neural network, BPNN; and BPNN with genetic algorithm optimization, GA-BPNN) to evaluate CLQ for determining the accurate evaluation model. In addition, the optimal satellite-derived indicator in the land state index was selected among five vegetation indices (the normalized vegetation index, NDVI; enhanced vegetation index, EVI; modified soil-adjusted vegetation index, MSAVI; perpendicular vegetation index, PVI; and soil-adjusted vegetation index, SAVI) to improve the prediction accuracy of CLQ. This study was conducted in Conghua District of Guangzhou, Guangdong Province, China, based on Gaofen-1 (GF-1) data. The prediction accuracies from the traditional linear model, PLSR, BPNN, and GA-BPNN were compared using observations. The results demonstrated that (1) compared with other models (the traditional linear model: R² = 0.14 and RMSE = 91.53; PLSR: R² = 0.33 and RMSE = 74.58; BPNN: R² = 0.50 and RMSE = 61.75), the GA-BPNN model based on EVI in the land state index provided the most accurate estimates of CLQ, with the R² of 0.59 and root mean square error (RMSE) of 56.87, indicating a nonlinear relationship between CLQ and the prediction indicator; and (2) the GA-BPNN-based evaluation approach of CLQ in the PSR framework was driven to map CLQ of the study area using the GF-1 data, leading to an RMSE of 61.44 at the regional scale, implying that the GA-BPNN-based evaluation approach has the potential to map CLQ over large areas. This study provides an important reference for the high-accuracy prediction of CLQ based on remote sensing technology.

The Optimal Image Date Selection for Evaluating Cultivated Land Quality Based on Gaofen-1 Images

This study proposes a method for determining the optimal image date to improve the evaluation of cultivated land quality (CLQ). Five vegetation indices: leaf area index (LAI), difference vegetation index (DVI), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI) are first retrieved using the PROSAIL model and Gaofen-1 (GF-1) images. The indices are then introduced into four regression models at different growth stages for assessing CLQ. The optimal image date of CLQ evaluation is finally determined according to the root mean square error (RMSE). This method is tested and validated in a rice growth area of Southern China based on 115 sample plots and five GF-1 images acquired at the tillering, jointing, booting, heading to flowering, and milk ripe and maturity stage of rice in 2015, respectively. The results show that the RMSEs between the measured and estimated CLQ from four vegetation index-based regression models at the heading to flowering stage are smaller than those at the other growth stages, indicating that the image date corresponding with the heading to flowering stage is optimal for CLQ evaluation. Compared with other vegetation index-based models, the LAI-based logarithm model provides the most accurate estimates of CLQ. The optimal model is also driven using the GF-1 image at the heading to flowering stage to map CLQ of the study area, leading to a relative RMSE of 14.09% at the regional scale. This further implies that the heading to flowering stage is the optimal image time for evaluating CLQ. This study is the first effort to provide an applicable method of selecting the optimal image date to improve the estimation of CLQ and thus advanced the literature in this field.

Conventional land-use intensification reduces species richness and increases production: A global meta-analysis

Most current research on land-use intensification addresses its potential to either threaten biodiversity or to boost agricultural production. However, little is known about the simultaneous effects of intensification on biodiversity and yield. To determine the responses of species richness and yield to conventional intensification, we conducted a global meta-analysis synthesizing 115 studies which collected data for both variables at the same locations. We extracted 449 cases that cover a variety of areas used for agricultural (crops, fodder) and silvicultural (wood) production. We found that, across all production systems and species groups, conventional intensification is successful in increasing yield (grand mean + 20.3%), but it also results in a loss of species richness (-8.9%). However, analysis of sub-groups revealed inconsistent results. For example, small intensification steps within low intensity systems did not affect yield or species richness. Within high-intensity systems species losses were non-significant but yield gains were substantial (+15.2%). Conventional intensification within medium intensity systems revealed the highest yield increase (+84.9%) and showed the largest loss in species richness (-22.9%). Production systems differed in their magnitude of richness response, with insignificant changes in silvicultural systems and substantial losses in crop systems (-21.2%). In addition, this meta-analysis identifies a lack of studies that collect robust biodiversity (i.e. beyond species richness) and yield data at the same sites and that provide quantitative information on land-use intensity. Our findings suggest that, in many cases, conventional land-use intensification drives a trade-off between species richness and production. However, species richness losses were often not significantly different from zero, suggesting even conventional intensification can result in yield increases without coming at the expense of biodiversity loss. These results should guide future research to close existing research gaps and to understand the circumstances required to achieve such win-win or win-no-harm situations in conventional agriculture.

Reducing food’s environmental impacts through producers and consumers

Food’s environmental impacts are created by millions of diverse producers. To identify solutions that are effective under this heterogeneity, we consolidated data covering five environmental indicators; 38,700 farms; and 1600 processors, packaging types, and retailers. Impact can vary 50-fold among producers of the same product, creating substantial mitigation opportunities. However, mitigation is complicated by trade-offs, multiple ways for producers to achieve low impacts, and interactions throughout the supply chain. Producers have limits on how far they can reduce impacts. Most strikingly, impacts of the lowest-impact animal products typically exceed those of vegetable substitutes, providing new evidence for the importance of dietary change. Cumulatively, our findings support an approach where producers monitor their own impacts, flexibly meet environmental targets by choosing from multiple practices, and communicate their impacts to consumers.