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Making agriculture sustainable is a global challenge. In the European Union (EU), the Common Agricultural Policy (CAP) is failing with respect to biodiversity, climate, soil, land degradation as well as socio‐economic challenges.
The European Commission's proposal for a CAP post‐2020 provides a scope for enhanced sustainability. However, it also allows Member States to choose low‐ambition implementation pathways. It therefore remains essential to address citizens' demands for sustainable agriculture and rectify systemic weaknesses in the CAP, using the full breadth of available scientific evidence and knowledge.
Concerned about current attempts to dilute the environmental ambition of the future CAP, and the lack of concrete proposals for improving the CAP in the draft of the European Green Deal, we call on the European Parliament, Council and Commission to adopt 10 urgent action points for delivering sustainable food production, biodiversity conservation and climate mitigation.
Knowledge is available to help moving towards evidence‐based, sustainable European agriculture that can benefit people, nature and their joint futures.
The statements made in this article have the broad support of the scientific community, as expressed by above 3,600 signatories to the preprint version of this manuscript. The list can be found here (https://doi.org/10.5281/zenodo.3685632).
A free Plain Language Summary can be found within the Supporting Information of this article.
Grüne Maden schonen Umwelt : studentisches Projekt Green Grubs stellt proteinreiches Tierfutter her
(2019)
As a cognitively-mediated response, autonomous adaptation at farm-gate levels constitutes reactionary actions by farmers against climate impacts. These actions are shaped by interacting factors such as household characteristics, livelihood scope and resources. It is driven by the goal of adapting cultivated farmlands to climate and for sustaining crop yields. Thus, interest in balancing adaptation goals with protection of vegetation conditions is less of a priority. Lack of research interest in understanding the gap between objectives of reactionary adaptation and protection of surface conditions (vegetation canopies) is a gap in research. In many studies, farm-gate level adaptation is described as a set of zero-feedback actions in response to climate impacts. This perception conceals the stress and impact-engendering attribute of reactionary adaptation. Inspired towards addressing this conceptual gap; this study investigates impact of farmers’ reactionary adaptation on vegetation cover in Keffi, Nasarawa, Nigeria. A twenty-year time-series NDVI and rainfall datasets are linearly regressed to examine the extent of NDVI-rainfall sensitivity. A weak linear relationship between NDVI and rainfall in Keffi for the period, 1999-2018 is observed. At a regression slope of 0.001, R squared, R2=0.129 (implying that only about 13% of the variability in NDVI in Keffi are explained by rainfall amount) and a bivariate regression coefficient, r=0.359; statistical evidence shows that rainfall amount are not significant predictors of NDVI in Keffi. In investigating the possible interference of non-rainfall factors on vegetation productivity (NDVI) in Keffi; a residual trend (RESTREND) analysis was carried out. Regression of residuals from NDVI-Rainfall linear regression produced a R=0.192 with a negative and downwards slope. The downward character of the RESTREND slope is suggestive of non-rainfall factors contained in the residuals. In validating the RESTREND analysis, a comparative analysis between observed and predicted NDVI derived from a reference NDVI value of 0.46 was carried out. The NDVI value of 0.46, is empirically assumed to be average NDVI value expected at a minimum rainfall amount of 850mm/year reported in tropical Savanna ecosystems. Using this empirical relationship, NDVI values were predicted for Keffi. Even at higher rainfall amounts≈1340mm/year, amounts were unable to produce corresponding higher NDVI values; rather a more plausible correlation between reference-derived predicted NDVI values and rainfall was obtained. A further analysis with predicted NDVI values, based on 1999 NDVI value in Keffi returned higher NDVI units than observed NDVI values. This strengthens the attribution of the possible interference of rainfall-NDVI sensitivity by non-rainfall factors like human activities on vegetation productivity. Surface soil analysis to exclude potential impacts of soil nutrients and moisture deficiency on vegetation productivity, showed that soil had insignificant effect on vegetation dynamics. Further inferential analysis, using the inter-annual NDVI and the reclassified bi-decadal NDVI maps showed that spatial vegetation distribution in Keffi were driven by farmers inter-annual rotational cultivation footprints than rainfall variability. With a three-class categorization, “gain, loss and significant loss”, the spatial distribution of vegetation in Keffi between (1999-2008) and (2009-2018) was assessed. Temporal condition (stressed and healthy) across the three classes supports the attribution of farmers’ reactionary adaptation and cultivation practices on the dynamic spatial vegetation distribution. Between 1999 -2018, an increase in areas with significant vegetation loss (42%), so with a decrease of -25% in areas with healthy vegetation was observed. The character of vegetation cover across the two decadal time slices, reflects landuse intensity and unsustainable farming practices. Preferences for modification of cultivation practices and changes in seed by farmers exerts positive feedbacks on vegetation cover. Higher statistical measures, 38.4% (yearly cropping) and 44% (shifting cultivation with less fallow periods) were observed in the chi-square analysis. These measures were higher than 2.0% relating to shifting cultivation with more fallow periods. While 11.6% farmers noted cultural practices as reasons for preferred cultivation methods, 48.4% farmers attributed climate as reason behind cultivation modification. This was higher than 24.4% who linked issues of tenure rights to cultivation practices. With preferences for yield- breaching strategies, the non-receding cultivation and shorter fallow practices in Keffi triggers feedback on vegetation dynamics. Evidence from this study shows that the NDVI-rainfall functional sensitivity in Keffi is plausibly dampened by effects of reactionary farm-gate level adaptation practices.
Within the world’s oceans, regionally distinct ecological niches develop due to differences in water temperature, nutrients, food availability, predation and light intensity. This results in differences in the vertical dispersion of planktonic foraminifera on the global scale. Understanding the controls on these modern-day distributions is important when using these organisms for paleoceanographic reconstructions. As such, this study constrains modern depth habitats for the northern equatorial Indian Ocean, for 14 planktonic foraminiferal species (G. ruber, G. elongatus, G. pyramidalis, G. rubescens, T. sacculifer, G. siphonifera, G. glutinata, N. dutertrei, G. bulloides, G. ungulata, P. obliquiloculata, G. menardii, G. hexagonus, G. scitula) using stable isotopic signatures (δ18O and δ13C) and Mg/Ca ratios. We evaluate two aspects of inferred depth habitats: (1) the significance of the apparent calcification depth (ACD) calculation method/equations and (2) regional species-specific ACD controls. Through a comparison with five global, (sub)tropical studies we found the choice of applied equation and δ18Osw significant and an important consideration when comparing with the published literature. The ACDs of the surface mixed layer and thermocline species show a tight clustering between 73–109 m water depth coinciding with the deep chlorophyll maximum (DCM). Furthermore, the ACDs for the sub-thermocline species are positioned relative to secondary peaks in the local primary production. We surmise that food source plays a key role in the relative living depths for the majority of the investigated planktonic foraminifera within this oligotrophic environment of the Maldives and elsewhere in the tropical oceans.
Good quality data on precipitation are a prerequisite for applications like short-term weather forecasts, medium-term humanitarian assistance, and long-term climate modelling. In Sub-Saharan Africa, however, the meteorological station networks are frequently insufficient, as in the Cuvelai-Basin in Namibia and Angola. This paper analyses six rainfall products (ARC2.0, CHIRPS2.0, CRU-TS3.23, GPCCv7, PERSIANN-CDR, and TAMSAT) with respect to their performance in a crop model (APSIM) to obtain nutritional scores of a household’s requirements for dietary energy and further macronutrients. All products were calibrated to an observed time series using Quantile Mapping. The crop model output was compared against official yield data. The results show that the products (i) reproduce well the Basin’s spatial patterns, and (ii) temporally agree to station records (r = 0.84). However, differences exist in absolute annual rainfall (range: 154 mm), rainfall intensities, dry spell duration, rainy day counts, and the rainy season onset. Though calibration aligns key characteristics, the remaining differences lead to varying crop model results. While the model well reproduces official yield data using the observed rainfall time series (r = 0.52), the products’ results are heterogeneous (e.g., CHIRPS: r = 0.18). Overall, 97% of a household’s dietary energy demand is met. The study emphasizes the importance of considering the differences among multiple rainfall products when ground measurements are scarce.
In October 2015, the Cluster of Excellence 'Image Knowledge Gestaltung. An Interdisciplinary Laboratory' at Humboldt Universität zu Berlin staged a symposium entitled Science meets Comics. Academics from various disciplines converged along with artists from all over the world in order to discuss the future of global nutrition – and the medium of the comic strip as a communication tool for the complex issues in this field. The open two-day symposium was followed by a closed, three-day workshop wherein the artists and cluster members took up the issues raised at the symposium and worked on possible directions for the future.
Human-induced environmental change represents one of the major challenges of current and future generations. To evaluate the anthropogenic impacts on the biosphere, the concept of Planetary Boundaries was developed, indicating that in case of four out of nine environmental indicators a transgression of corresponding boundaries has already taken place: Biodiversity loss, climate change, land-system change, and biogeochemical flows. Further, paleoclimate research has shown that the earth´s environment has been relatively stable for the last 12,000 years. Researchers assume that this, in geological terms, very short period – called Holocene – is now already again replaced by a new geological era: the Anthropocene, due to the tremendous impacts humans had on earth.
Our daily food consumption is slowly but surely turning into the largest environmental threat. The agricultural sector consumes 70% of the water used by humankind. The production of meat consumes enormous amounts of water compared to plants. Innovations in the area of food production are lately summarized as AgTech, agricultural technology. This encompasses all sorts of areas, ranging from drone-controlled tractors to printed hamburgers. Specifically the challenge of making use of the limited areas available in cities and maximizing crop yields has seen a recent boom in novel approaches – and quite a bit of investor finance.
The Global Irrigation Model (GIM) is used within the framework of the global hydrological model WaterGAP to calculate monthly irrigation crop water use. Results on a 0.5 degrees grid include, consumption (ICU) and, via division by irrigation efficiencies, water withdrawal (IWU). The model distinguishes up to two cropping periods of rice and non-rice crops, each grown for 150 days, using a grid of area equipped for irrigation (AEI). Historical development of AEI and fraction of area actually irrigated (AAI) was previously considered via scaling of cell-specific results with country-specific factors for each year. In this study, GIM was adapted to use the new Historical Irrigation Data set (HID) with cell-specific AEI for 14 time slices between 1900 and 2005. AEI grids were temporally interpolated, and using the optional grid of AAI/AEI, results for years 1901-2014 were generated (runs "HID-ACT"). Thus, new installation or abandonment of irrigation infrastructure in new grid cells can be represented in a spatially explicit manner. For evaluated years 1910, 1960, 1995, and 2005, ICU from HID-ACT was superior to country-specific scaled results (run "HID-ACTHIST") in representing historical development of the spatial pattern. Compared to US state-level reference data, spatial patterns were better, while country totals were not always better. For calculating the cropping periods, 30-years climate means are needed, the choice of which is relevant. Four chosen periods before 1981-2010 all resulted in considerable, pertaining changes of ICU spatial pattern, and various percent changes in country totals. This might be because of already present climate change.
The paper broaches the issue of unfair trading practices (UTPs) at the expense of, economically spoken, weaker actors among the food supply chain in context of the EU. For illustrating the concept of UTPs and delivering a theoretical basis for scrutinizing the term of fairness in respective trading practices the paper suggests the three variables 1) bargaining power, 2) market power/anti competitive practices and 3) unequal gain distribution. Subsequently the article presents selected national food-specific legislative based reactions towards UTPs evolved in context of the three variables. Ultimately the paper presents a qualitatively generated hypothesis which presumes that legislative food-specific measurements focussing on protecting suppliers lead to a beneficial monetary share for farmers, by means of influencing the producer price to a monetarily advantageous extent. The hypothesis was generated unprejudiced in the run-up to the paper. The research design which led to the hypothesis mentioned will be presented.