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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.
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.
Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter λ describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψww describing the typical ‘well-watered’ leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset [root mean square error (RMSE) < 0.5 MPa)]. We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.
Mehr als 7 Prozent der Treibhausgase, die in Deutschland freigesetzt werden, stammen aus der Landwirtschaft: Von wiederkäuenden Rindern etwa, aus stickstoffhaltigen Düngemitteln. Hinzu kommen Emissionen aus trockengelegten Mooren oder aus verrottendem Humus umgepflügter Wiesen. Rund 58 Milliarden Euro fließen jährlich vom EU-Budget in die europäische Landwirtschaft. Dies gibt Bund und Ländern viele Möglichkeiten, etwas für den Klimaschutz zu tun.
Der Wald der Zukunft ... : ...braucht andere Bäume. Welche, versuchen Forscher herauszufinden
(2020)
Die Luft ist heiß und trocken, der sandige Boden hält kein Wasser: Es gibt nicht viele Wälder in Deutschland, denen es schlechter geht als dem Frankfurter Stadtwald. Für Wolfgang Brüggemann und Vera Holland ist er damit der perfekte Ort, um klimawandelresistente Bäume zu finden. Denn: Wer es hier schafft, der schafft es überall.
In recent years, reports of elephants causing damage in rural villages by destroying houses and foraging on stored food have been increasing, but little is known about the determinants and magnitude of this damage. In this study, we have examined the extent of property damage by elephants (Loxodonta africana and Elephas maximus), in one African and two Asian study areas over a six‐year period. A total of 1,172 damaged constructions were observed on site, involving detailed damage assessment by trained enumerators and standardized interviews with witnesses. Depending on the study area, between 67.1 and 86.4% of damage events were attributed to single, individual elephants or pairs of males. The majority of properties were damaged in search for food (62.5–76.7% respectively). Property damage caused higher mean losses than crop damage on farmland in all study areas. Results suggest that property damage by elephants has been largely underestimated and needs to form a focus in future human–elephant conflict research. We suggest a need to reduce the attractiveness of villages by storing food in locked and safe places, away from sleeping areas and to foster the development of elephant safe stores, appropriate to the particular cultural background of the target area.
Traditional beekeeping has been playing important socio-economic roles in Ethiopia for millennia. The country is situated in northeast Africa, where ranges of major evolutionary lineages of Apis mellifera adjoin. However, studies on the classification and distribution of subspecies and lineages of honey bees in the country are partly inconsistent, either proposing multiple subspecies and lineages or a unique A. m. simensis. This study was conducted with the aim of elucidating Ethiopian honey bees in reference to African subspecies and major global lineages using wing geometric morphometrics and COI-COII mitochondrial DNA analyses. For this purpose, 660 worker bees were collected from 66 colonies representing highland, midland, and lowland zones in different locations. Both methods indicated that the samples from this study form a distinct cluster together with A. m. simensis reference. In addition, forewing venation patterns showed that most of the Ethiopian samples are separate from all reference subspecies, except A. m. simensis. Analysis of COI-COII sequences revealed five DraI haplotypes (Y2, Y1, A1, and O5’), of which one was new denoted as Y3. Moreover, centroid size strongly associated with elevation. In conclusion, the results supported that Ethiopian honey bees are distinct both at lineage and subspecies levels; however, there is an indication of lineage O in the north.