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Makowski, D.

Publications and source records attributed to Makowski, D..

11 recordsLinked to original sources

Mean yield gap explains differences in yield stability between organic and conventional systems

Over recent decades, numerous studies have compared agricultural productivity across different management systems and environments, with increasing attention to the stability of crop yields. Yield stability is a key component of agroecosystem resilience under global change, yet it remains unclear whether some cropping systems are more stable than others. The debate over organic farming is particularly heated, as some evidence indicates that organic systems are less stable, while other evidence suggests the opposite. Here, we develop a conceptual and statistical framework for comparing crop yield stability across agricultural systems that explicitly accounts for a parametric function relating inter-annual yield standard deviation to mean yield value. Using a new global dataset of long-term field experiments spanning multiple crop species and environments, we show that the fitted functions relating yield standard deviation and mean yield value obtained for organic and conventional cropping systems share several important similarities. For both systems, the yield coefficient of variation (CV) significantly decreases with mean yield, and most of the difference in yield stability between conventional and organic systems is explained by differences in mean productivity. As a consequence, the CV of the two systems becomes similar as the difference in average efficiency narrows. Our framework reconciles apparently conflicting results in the literature and provides a more robust basis for comparing stability across cropping systems.

ecology↗

Reduced nutritional quality of plants due to climate change

The effect of climate change on the nutritional quality of plants is poorly understood even though it may have major implications for the food chain and ecosystems. Here we use a dataset covering > 1450 plant species to identify the factors driving plants nutritional properties and develop global projections. We reveal that plant type, CO2, and solar radiation are major drivers controlling nutritional properties. Projections for 2050 show a decline in nutritional quality (-8%, on average at the global scale), measured as the protein to fiber ratio, a strong decrease in minerals (-18%), and a small decrease in digestibility (-3%). Plants in arid and tropical areas will experience the largest decline in quality, which will decline minimally in temperate areas and improve in cold, and polar regions. Quality trends will be opposite in grasses. These results have important implications for livestock management and wildlife conservation.

plant biology↗

High potential contribution of intercropping to soybean and maize self-sufficiency in Europe

This study examines whether maize-soybean intercropping could improve the European Unions soybean self-sufficiency while minimizing trade-offs with maize and other crops production. Assuming a four-year return, intercropping on 6.3, 13.1, and 20.1 Mha could produce 9.1 (28.8), 18.2 (63.7), and 27.2 (99.0) Mt of soybean (maize), achieving 25% (34%), 50% (75%), and 75% (116%) self-sufficiency. Reaching similar co-productions with sole crops require an additional 11.1, 24.7, and 36.5 Mha, implying 20-21% land savings with intercrops. Full soybean self-sufficiency could require more than 25 Mha of intercrops (25% of European cropland) annually. These estimates held under a large range of nitrogen inputs and temporal overlaps between crop species, provided 1 hectare of intercropping produced more soybean than 0.5 hectare of sole soybean. Geographic variation in sole crop yields should therefore be considered when assessing intercrops land-use efficiency. Our results highlight intercropping as a strategy to simultaneously improve European soybean production, satisfy maize needs, and save lands.

plant biology↗

Global review of meta-analyses reveals key data gaps in agricultural impact studies on biodiversity in croplands

AimAgriculture depends heavily on biodiversity, yet unsustainable management practices continue to affect a wide range of organisms and ecosystems at unprecedented levels worldwide. Addressing the global challenge of biodiversity loss requires access to consolidated knowledge across management practices, spatial levels, and taxonomic groups. LocationGlobal Time period1994 to 2022 Major taxa studiedAnimals, microorganisms, plants. MethodsWe conducted a comprehensive literature review synthesising data from all meta-analyses about the impacts of agricultural management practices on biodiversity in croplands, covering field, farm, and landscape levels. From 200 retained meta-analyses, we extracted 1,885 mean effect sizes (from 69,850 comparisons between a control and treatment) assessing the impact of management practices on biodiversity, alongside characterising over 9,000 primary papers. ResultsSeven high-income countries, notably the USA, China, and Brazil dominate agricultural impact studies with fertiliser use, phytosanitary interventions and crop diversification receiving widespread attention. The focus on individual practices overshadows research at the farm and landscape level. Taxonomically, Animalia, especially arthropods, are heavily studied while taxa such as annelids and plants receive comparatively less attention. Effect sizes are predominantly calculated from averaged abundance data. Significant gaps persist in terms of studies on the effects of agricultural interventions on specific taxonomic groups (e.g. annelids, mammals) and studies analysing functional traits. Main conclusionsOur study highlights the importance of analysing the effects of combined practices to accurately reflect real-world farming contexts. While abundance metrics are common, reflecting several biodiversity facets and adopting a more balanced research approach across taxa are crucial for understanding biodiversity responses to agricultural changes and informing conservation strategies. Given the unbalanced evidence on impacts of agricultural practices on biodiversity, caution is required when utilising meta-analytical findings for informing public policies or integrating them into global assessment models like life-cycle assessments or global flux models.

ecology↗

Revealing the spatial characteristics of rice heat exposure in Japan through panicle temperature analysis

Elevated temperatures during the flowing stage contribute to heat-induced spikelet sterility in rice, posing a major threat to production considering climate change projections. Developing effective strategies for stable rice production through breeding and crop management is critical; however, our understanding of regional, seasonal, and long-term trends in rice heat exposure remains limited. Previous studies on spikelet sterility revealed that panicle temperature, estimated using a micrometeorological model and common meteorological factors, serves as a reliable indicator of rice heat exposure. In this study, we employed this model to identify the differences between panicle and air temperatures (DPAT) and their causes over the past 45 years in Japan. A gridded daily meteorological dataset covering Japan was interpolated at an hourly time step and used as input data of the micrometeorology model for estimating panicle temperatures during flowering. Statistical analysis of the resulting data revealed an increasing trend in the frequency of rice panicle heat exposure over time across many locations in Japan. During heat-receptive periods, panicle temperature generally exceeded air temperature, indicating the inadequacy of relying solely on air temperature to gauge rice heat stress. DPAT values showed substantial inter-regional variations in both mean values (from -0.5 to 3.0) and seasonality. Through machine learning and statistical methods, the relationship between DPAT and meteorological factors was characterized, delineating the effects of the meteorological factors on regional and seasonal DPAT variations. Focusing on major high-risk regions, we show that mitigation strategies should be adapted to consider regional characteristics and avoid high DPAT conditions during rice heading periods.

plant biology↗

Effectiveness of heat tolerance rice cultivars in preserving grain appearance quality under high temperatures - A meta-analysis

BackgroundClimate change, particularly rising temperatures, negatively affects rice grain quality, increasing chalky grain percentage (CG) and hampering rice grade and price. Heat-tolerant cultivars have been bred and released since the 2000s, but the effectiveness of heat tolerance in reducing the occurrence of CG has yet to be quantified. ObjectivesThis study aimed to measure the effectiveness of breeding for better heat tolerance in reducing the negative impact of high temperatures on rice quality. MethodsThrough a systematic literature search, we developed a dataset including 1297 field observations covering 48 cultivars from five different heat tolerant ranks (HTRs) at 44 sites across Japan. A linear mixed-effect model (LME) and a random forest model (RF) were fitted to the data to analyze the effect of HTR and climatic factors such as the cumulative mean air temperature above 26 {degrees}C (TaHD), mean solar radiation, and mean relative humidity for 20 days after heading on CG. ResultsThe LME model explained 63 % of the variation with a 14% RMSE. The RF partial dependence plot revealed that the logit-transformed CG response to climate factors was linear, supporting the assumption of LME. The statistical analysis showed that CG increased as a function of TaHD (P < 0.001), with significant differences among HTRs (P < 0.001). The strongest effect of TaHD was obtained for the lowest HTR and was found to decrease with increasing HTR. CG also increased with higher relative humidity (P < 0.001) and solar radiation (P < 0.01). Based on our modeling, we estimated that as TaHD increased from 20 to 80 {degrees}Cd (equivalent to a mean temperature increase from 27 {degrees}C to 30 {degrees}C), CG increased by 66 % points (difference in CG) for cultivars with the lowest HTR, 45 % points for cultivars with an intermediate HTR, and 19 % points for cultivars with the highest HTR. Raising HTR by just one step (from intermediate to moderately tolerant) is projected to increase the proportion of first-grade rice at a grain-filling temperature of 27 {degrees}C, but tolerance levels need to be improved further in case of stronger warming. ConclusionsThe effect of high temperatures on CG was highly dependent on the cultivars HTR. Improvements in HTR effectively reduce the negative impacts of high temperatures on rice grain quality. SignificanceHeat-tolerant cultivars are projected to suppress the prevalence of CG more than threefold compared with heat-sensitive cultivars when grain-filling temperature increases from 27 to 30 {degrees}C.

plant biology↗

A global dataset for the projected impacts of climate change on four major crops

Reliable estimates of the impacts of climate change on crop production are critical for assessing the sustainability of food systems. Global, regional, and site-specific crop simulation studies have been conducted for nearly four decades, representing valuable sources of information for climate change impact assessments. However, the wealth of data produced by these studies has not been made publicly available. Here, we develop a global dataset by consolidating previously published meta-analyses and data collected through a new literature search covering recent crop simulations. The new global dataset builds on 8314 simulations from 203 studies published between 1984 and 2020. It contains projected yields of four major crops (maize, rice, soybean, and wheat) in 91 countries under major emission scenarios for the 21st century, with and without adaptation measures, along with geographical coordinates, current temperatures, local and global warming levels. This dataset provides a basis for a comprehensive understanding of the impacts of climate change on crop production and will facilitate the rapidly developing data-driven machine learning applications.

plant biology↗

Data-driven yield projections suggest large opportunities to improve Europe's soybean self-sufficiency under climate change

Currently, demand for soybean in Europe is mostly fulfilled by imports. However, soybean-growing areas across Europe have been rapidly increasing in response to a rising demand for locally-produced, non-GM soybean in recent years. This raises questions about the suitability of European agro-climatic conditions for soybean production. We used data-driven relationships between climate and soybean yield derived from machine-learning techniques to make yield projections under current and future climate with moderate (RCP 4.5) to intense (RCP 8.5) warming, up to the 2050s and 2090s time horizons. Results suggest that a self-sufficiency level of 50% (100%) would be achievable in Europe under historical and future climate if 4-5% (9-12%) of the current European cropland is dedicated to soybean production. The associated increase in soybean area in Europe would bring environmental benefits, with a potential decrease of nitrogen fertilizer use in Europe by 5-8% (13-18%) and a possible reduction of deforestation in biodiversity hotspots in South America. However, it would also lead to an important reduction in the production of other cultivated species in Europe (e.g. cereals) and a potential increase in the use of irrigation water.

plant biology↗

Benefits of crop diversification for biodiversity and ecosystem services

Ecological theory suggests that biodiversity has a positive and stabilizing effect on the delivery of ecosystem services. Yet, the impacts of increasing the diversity of cultivated crop species or varieties in agroecosystems are still under scrutiny. The empirical evidence available is scattered in scope, agronomic and geographical contexts and impacts on ecosystem services may depend on the type of diversification strategy used. To robustly assess the effects of crop diversification in agroecosystems, we compiled the results of 95 meta-analyses integrating 5,156 experiments conducted over 84 experimental years and representing more than 54,500 paired observations on 120 crop species in 85 countries. Overall, our synthesis of experimental data from across the globe shows that crop diversification enhances not only crop production (median effect +14%), but also the associated biodiversity (+24%, i.e. the biodiversity of non-cultivated plants and animals), and several supporting and regulating ecosystem services including water quality (+51%), pest and disease control (+63%) and soil quality (+11%). However, there was substantial variability in the results for each individual ecosystem service between different diversification strategies like agroforestry, intercropping, cover-crops, crop rotation or variety mixtures. Agroforestry is particularly effective in delivering multiple ecosystem services, i.e. water use and quality, pest and diseases regulation, associated biodiversity, long-term soil productivity and quality. Variety mixtures, instead, provide the lowest benefits, while the other strategies show intermediate results. Our results highlight that while increasing the diversity of cultivated crop species or varieties in agroecosystems represents a very promising strategy for more sustainable land management, contributing to enhanced yields, enhanced biodiversity and ecosystem services, some crop diversification strategies are more effective than others in supporting key ecosystem services.

ecology↗

Standardizing carabid pitfall catches for trapping effort; a meta-analysis

O_LICarabid beetles (Coleoptera: Carabidae) provide important ecological services and are frequently used as a bio-indicator in monitoring environmental quality. The abundance and diversity of carabids is usually determined using pitfall trapping, but trap catches are difficult to compare between studies due to variation in trapping effort. The standardization of the catch for trapping effort has not been previously addressed in a global analysis of studies in the literature. C_LIO_LIThe aims of this study are (i) to define a method for estimating the effect of trapping effort on the size of the pitfall catch, and (ii) to explore factors related to study designs, sampling method, study origin, and level of data aggregation to determine how these factors affect the catch per unit effort in pitfall trapping. C_LIO_LIWe conducted a meta-analysis on the activity-density and diversity of carabids across studies, based on published data from Europe and North-America to analyse whether standardization of catch measurements might be possible. Data were extracted from 104 publications, spanning a period of 42 years. C_LIO_LIThe total catch was proportional to the number of trap days, and ranged from 0.19-9.53 beetles/(trap day) across studies (95% range), with a mean of 1.33 beetles/(trap day). The number of species was allometrically related to the trapping effort defined as the product of the number of traps, their perimeter and the time of exposure in the field, and characterized by a power exponent of 0.25. Species richness ranged across studies from 2.30-13.18 species/(m day)0.25 (95% range) with a mean of 7.15 species/(m day)0.25. The size of the catch and the number of species were higher in crops with narrow as compared to wide rows. There was no significant change in abundance or diversity of carabids in arable land over the 42 years covered. We also found that increasing trapping effort may not yield more accurate results. C_LIO_LIThe results show that it is possible to standardize activity-density-based catches and species diversity for trapping effort across studies using a power transformation, allowing meta-analysis of such data, e.g. to elucidate factors affecting abundance and diversity of the focal taxa. C_LI

ecology↗

A global map of root biomass across the world's forests

Abstract (150 words limits)Root plays a key role in plant growth and functioning. Here we combine 10307 field measurements of forest root biomass worldwide with global observations of forest structure, climatic conditions, topography, land management and soil characteristics to derive a spatially-explicit global high-resolution (~ 1km) root biomass dataset, including fine and coarse roots. In total, 142 {+/-} 32 Pg of live dry matter biomass is stored below-ground, that is a global average root:shoot biomass ratio of 0.25 {+/-} 0.10. Our estimations of total root biomass in tropical, temperate and boreal forests are 44-226% smaller than earlier studies1-3. The smaller estimation is attributable to the updated forest area, spatially explicit above-ground biomass density used to predict the patterns of root biomass, new root measurements and upscaling methodology. We show specifically that the root shoot allometry is one underlying driver that leads to methodological overestimation of root biomass in previous estimations.

ecology↗