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Land-use type temporarily affects active pond community structure but not gene expression patterns
(2022)
Changes in land use and agricultural intensification threaten biodiversity and ecosystem functioning of small water bodies. We studied 67 kettle holes (KH) in an agricultural landscape in northeastern Germany using landscape-scale metatranscriptomics to understand the responses of active bacterial, archaeal and eukaryotic communities to land-use type. These KH are proxies of the millions of small standing water bodies of glacial origin spread across the northern hemisphere. Like other landscapes in Europe, the study area has been used for intensive agriculture since the 1950s. In contrast to a parallel environmental DNA study that suggests the homogenization of biodiversity across KH, conceivably resulting from long-lasting intensive agriculture, land-use type affected the structure of the active KH communities during spring crop fertilization, but not a month later. This effect was more pronounced for eukaryotes than for bacteria. In contrast, gene expression patterns did not differ between months or across land-use types, suggesting a high degree of functional redundancy across the KH communities. Variability in gene expression was best explained by active bacterial and eukaryotic community structures, suggesting that these changes in functioning are primarily driven by interactions between organisms. Our results indicate that influences of the surrounding landscape result in temporary changes in the activity of different community members. Thus, even in KH where biodiversity has been homogenized, communities continue to respond to land management. This potential needs to be considered when developing sustainable management options for restoration purposes and for successful mitigation of further biodiversity loss in agricultural landscapes.
Controlling bioenergy-induced land-use-change emissions is key to exploiting bioenergy for climate change mitigation. However, the effect of different land-use and energy sector policies on specific bioenergy emissions has not been studied so far. Using the global integrated assessment model REMIND-MAgPIE, we derive a biofuel emission factor (EF) for different policy frameworks. We find that a uniform price on emissions from both sectors keeps biofuel emissions at 12 kg CO2 GJ−1. However, without land-use regulation, the EF increases substantially (64 kg CO2 GJ−1 over 80 years, 92 kg CO2 GJ−1 over 30 years). We also find that comprehensive coverage (>90%) of carbon-rich land areas worldwide is key to containing land-use emissions. Pricing emissions indirectly on the level of bioenergy consumption reduces total emissions by cutting bioenergy demand but fails to reduce the average EF. In the absence of comprehensive and timely land-use regulation, bioenergy thus may contribute less to climate change mitigation than assumed previously.
Under current land-use regulation, carbon dioxide emissions from biofuel production exceed those from fossil diesel combustion. Therefore, international agreements need to ensure the effective and globally comprehensive protection of natural land before modern bioenergy can effectively contribute to achieving carbon neutrality.
The cultivation of energy crops leads to direct and indirect land use changes that impair the biodiversity of the agricultural landscape. In our study, we analyse the effects of mitigation measures on the European brown hare (Lepus europaeus), which is directly affected by ongoing land use change and has experienced widespread decline throughout Europe since the 1960s. Therefore, we developed a spatially explicit and individual-based ecological model to study the effects of different landscape configurations and compositions on hare population development. As an input, we used two 4 x 4 km large model landscapes, which were generated by a landscape generator based on real field sizes and crop proportions and differed in average field size and crop composition. The crops grown annually are evaluated in terms of forage suitability, breeding suitability and crop richness for the hare. In six mitigation scenarios, we investigated the effects of a 10 % increase in the following measures: (1) mixed silphie, (2) miscanthus, (3) grass-clover ley, (4) alfalfa, (5) set-aside, and (6) general crop richness. All mitigation measures had significant effects on hare population development. Compared to the base scenario, the relative change in hare abundance ranged from a factor of 0.56 in the grass-clover ley scenario to-0.16 in the miscanthus scenario. The mitigation measures of mixed silphie, grass-clover ley and increased crop richness led to distinct increases in hare abundance in both landscapes ( > 0.3). The results show that both landscape configuration and composition have a significant effect on hare population development, which responds particularly strongly to compositional changes. The increase in crop diversity, e.g., through the cultivation of alternative energy crops such as mixed silphie and grass-clover ley, proves to be beneficial for the brown hare.
We analyze to what extent climate conditions affect the prevalence of sharecropping as a form of traditional land tenure. We investigate how sharecropping tenure is related to climate risk and how it interacts with fertilizer use and livestock ownership that both influence production risk. We first develop a stylized theoretical model to illustrate the role of climate for land tenure and production. Our empirical analysis is based on more than 9000 households with considerable heterogeneity in climate conditions across several African countries. We find that farmers in areas with low precipitation are more likely to be sharecroppers. We further find evidence for risk management interaction effects as sharecropping farmers are less likely to own livestock and more likely to use fertilizer. In economies where formal kinds of insurance are unavailable, sharecropping thus functions as a form of insurance and reduces the need for potentially costly risk management strategies.
Remote sensing plays an increasingly key role in the determination of soil organic carbon (SOC) stored in agriculturally managed topsoils at the regional and field scales. Contemporary Unmanned Aerial Systems (UAS) carrying low-cost and lightweight multispectral sensors provide high spatial resolution imagery (<10 cm). These capabilities allow integrate of UAS-derived soil data and maps into digitalized workflows for sustainable agriculture. However, the common situation of scarce soil data at field scale might be an obstacle for accurate digital soil mapping. In our case study we tested a fixed-wing UAS equipped with visible and near infrared (VIS-NIR) sensors to estimate topsoil SOC distribution at two fields under the constraint of limited sampling points, which were selected by pedological knowledge. They represent all releva nt soil types along an erosion-deposition gradient; hence, the full feature space in terms of topsoils' SOC status. We included the Topographic Position Index (TPI) as a co-variate for SOC prediction. Our study was performed in a soil landscape of hummocky ground moraines, which represent a significant of global arable land. Herein, small scale soil variability is mainly driven by tillage erosion which, in turn, is strongly dependent on topography. Relationships between SOC, TPI and spectral information were tested by Multiple Linear Regression (MLR) using: (i) single field data (local approach) and (ii) data from both fields (pooled approach). The highest prediction performance determined by a leave-one-out-cross-validation (LOOCV) was obtained for the models using the reflectance at 570 nm in conjunction with the TPI as explanatory variables for the local approach (coefficient of determination (R-2) = 0.91; root mean square error (RMSE) = 0.11% and R-2 = 0.48; RMSE = 0.33, respectively). The local MLR models developed with both reflectance and TPI using values from all points showed high correlations and low prediction errors for SOC content (R-2 = 0.88, RMSE = 0.07%; R-2 = 0.79, RMSE = 0.06%, respectively). The comparison with an enlarged dataset consisting of all points from both fields (pooled approach) showed no improvement of the prediction accuracy but yielded decreased prediction errors. Lastly, the local MLR models were applied to the data of the respective other field to evaluate the cross-field prediction ability. The spatial SOC pattern generally remains unaffected on both fields; differences, however, occur concerning the predicted SOC level. Our results indicate a high potential of the combination of UAS-based remote sensing and environmental covariates, such as terrain attributes, for the prediction of topsoil SOC content at the field scale. The temporal flexibility of UAS offer the opportunity to optimize flight conditions including weather and soil surface status (plant cover or residuals, moisture and roughness) which, otherwise, might obscure the relationship between spectral data and SOC content. Pedologically targeted selection of soil samples for model development appears to be the key for an efficient and effective prediction even with a small dataset.
Biodiversity and abundance of wildlife has dramatically declined in agricultural landscapes. Sown, short-lived wildflower (WF) strips along the margins of crop fields are a widespread and often subsidised in agri-environmental schemes, intended to enhance biodiversity, provide refuges for wild plant and arthropod populations and to provide ecosystem services to crops. Meanwhile, WF elements are also criticised, since their functionality decreases with plant succession, the removal of aged WF strip poses an ecological trap for the attracted arthropod populations and only common and mobile species benefit. Further, insects in WF strips are impacted by pesticides from agricultural fields due to shared boundaries with crop fields and by edge effects. The performance of the measure could be improved by combining several WF strips of different successional stages, each harbouring a unique community of plants and arthropods, into persistent, composite WF block, where successional stages exist in parallel. Monitoring data on many taxa in the literature shows, that a third of species are temporarily present in an ageing WF stip, thus offering composite WF blocks should increase cumulative species richness by 28%-39% compared to annual richness in WF strips. Persistence of composite WF blocks would offer reliable refuge for animal and plant populations, also supporting their predators and herbivores. Further, WF blocks have less boundaries to crops compared to WF strips of the same area, and are less impacted by edge effects and pesticides. Policy implications. Here I suggest a change of conservation practice changing from successional WF strips to composite WF blocks. By regular removal and replacement of aged WF strips either within the block (rotational) or at its margins (rolling), the habitat heterogeneity in composite WF block could be perpetuated. Rolling composite WF blocks change locations over years, and the original location can be reconverted to arable land while a nearby WF block is still available to wildlife. A change in agricultural schemes would be necessary, since in some European countries clustered WF strips are explicitly not subsidised.
While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.
Agricultural land-use practices have intensified over the last decades, leading to population declines of various farmland species, including the European hare (Lepus europaeus). In many European countries, arable fields dominate agricultural landscapes. Compared to pastures, arable land is highly variable, resulting in a large spatial variation of food and cover for wildlife over the course of the year, which potentially affects habitat selection by hares. Here, we investigated within-home-range habitat selection by hares in arable areas in Denmark and Germany to identify habitat requirements for their conservation. We hypothesized that hare habitat selection would depend on local habitat structure, that is, vegetation height, but also on agricultural field size, vegetation type, and proximity to field edges. Active hares generally selected for short vegetation (1-25 cm) and avoided higher vegetation and bare ground, especially when fields were comparatively larger. Vegetation >50 cm potentially restricts hares from entering parts of their home range and does not provide good forage, the latter also being the case on bare ground. The vegetation type was important for habitat selection by inactive hares, with fabaceae, fallow, and maize being selected for, potentially providing both cover and forage. Our results indicate that patches of shorter vegetation could improve the forage quality and habitat accessibility for hares, especially in areas with large monocultures. Thus, policymakers should aim to increase areas with short vegetation throughout the year. Further, permanent set-asides, like fallow and wildflower areas, would provide year-round cover for inactive hares. Finally, the reduction in field sizes would increase the density of field margins, and farming different crop types within small areas could improve the habitat for hares and other farmland species.
Agricultural land‐use practices have intensified over the last decades, leading to population declines of various farmland species, including the European hare (Lepus europaeus). In many European countries, arable fields dominate agricultural landscapes. Compared to pastures, arable land is highly variable, resulting in a large spatial variation of food and cover for wildlife over the course of the year, which potentially affects habitat selection by hares. Here, we investigated within‐home‐range habitat selection by hares in arable areas in Denmark and Germany to identify habitat requirements for their conservation. We hypothesized that hare habitat selection would depend on local habitat structure, that is, vegetation height, but also on agricultural field size, vegetation type, and proximity to field edges. Active hares generally selected for short vegetation (1–25 cm) and avoided higher vegetation and bare ground, especially when fields were comparatively larger. Vegetation >50 cm potentially restricts hares from entering parts of their home range and does not provide good forage, the latter also being the case on bare ground. The vegetation type was important for habitat selection by inactive hares, with fabaceae, fallow, and maize being selected for, potentially providing both cover and forage. Our results indicate that patches of shorter vegetation could improve the forage quality and habitat accessibility for hares, especially in areas with large monocultures. Thus, policymakers should aim to increase areas with short vegetation throughout the year. Further, permanent set‐asides, like fallow and wildflower areas, would provide year‐round cover for inactive hares. Finally, the reduction in field sizes would increase the density of field margins, and farming different crop types within small areas could improve the habitat for hares and other farmland species.