Thünen Institute

Refined conversion factors for soil fungal biomarkers are proposed. High interspecific variability is present in all fungal biomarkers. A modeling approach supports the validity of biomarker estimates in diverse soils. ITS1 copies vary strongly, but are fungal-specific with least phylogenetic bias. A combination of fungal biomarkers will reveal soil fungal physiology and activity. The abundances of fungi and bacteria in soil are used as simple predictors for carbon dynamics, and represent widely available microbial traits. Soil biomarkers serve as quantitative estimates of these microbial groups, though not quantifying microbial biomass per se. The accurate conversion to microbial carbon pools, and an understanding of its comparability among soils is therefore needed. We refined conversion factors for classical fungal biomarkers, and evaluated the application of quantitative PCR (qPCR, rDNA copies) as a biomarker for soil fungi. Based on biomarker contents in pure fungal cultures of 30 isolates tested here, combined with comparable published datasets, we propose average conversion factors of 95.3 g fungal C g−1 ergosterol, 32.0 mg fungal C µmol−1 PLFA 18:2ω6,9 and 0.264 pg fungal C ITS1 DNA copy−1. As expected, interspecific variability was most pronounced in rDNA copies, though qPCR results showed the least phylogenetic bias. A modeling approach based on exemplary agricultural soils further supported the hypothesis that high diversity in soil buffers against biomarker variability, whereas also phylogenetic biases impact the accuracy of comparisons in biomarker estimates. Our analyses suggest that qPCR results cover the fungal community in soil best, though with a variability only partly offset in highly diverse soils. PLFA 18:2ω6,9 and ergosterol represent accurate biomarkers to quantify Ascomycota and Basidiomycota. To conclude, the ecological interpretation and coverage of biomarker data prior to their application in global models is important, where the combination of different biomarkers may be most insightful.

Agricultural expansion and intensification are major drivers of global biodiversity loss, endangering natural habitats and ecosystem functions, such as pollination. In this study, we analyze the spatiotemporal dynamics of avocado frontier expansion and intensification from 2011 to 2019 and assess their effects on landscape connectivity, focusing on Michoacán, Mexico, the world’s leading avocado exporter. Using high-resolution satellite imagery combined with deep learning based on convolutional neural networks, we delineated avocado orchards and other land use/cover classes, mapped individual avocado tree crowns and irrigation ponds, and identified hotspots of expanding and intensifying avocado production. We used a circuit theory approach to evaluate the effects of avocado expansion and intensification on the connectivity of natural and semi-natural habitats. Our results reveal a rapid increase in avocado orchards, which expanded by 4175 ha—a growth from 27.9% to 37% in area—over the eight-year period. There was also a decline in rainfed agriculture by 3252 ha, and oak-pine forests by 1343 ha. We observed not only the expansion of the avocado frontier into forests but also an intensification of avocado production via increases in high-density plantations, irrigation ponds, and orchards prone to intensive pruning. Moreover, lower-intensity land-use classes, such as rainfed crops, were rapidly converted to avocado orchards. This expansion and intensification have led to increasing isolation of forest fragments. Although we identified routes that could facilitate the movement of species, the dense avocado monocultures continue to threaten the connectivity of natural and semi-natural habitats, causing notable losses of old-growth oak-pine forests and disrupting crucial ecological corridors. Our research underscores the adverse effects of avocado production on land use and landscape connectivity, emphasizing the need for sustainable management practices to ensure the long-term viability of avocado production systems and overall ecosystem functioning.

Field monitoring plays a crucial role in understanding insect dynamics within ecosystems. It facilitates pest distribution assessment, control measure evaluation, and prediction of pest outbreaks. Additionally, it provides important information on bioindicators with which the state of biodiversity and ecological integrity in specific habitats and ecosystems can be accurately assessed. However, traditional monitoring systems face various difficulties, leading to a limited temporal and spatial resolution of the obtained information. Despite recent advancements in automatic insect monitoring traps, also called e‐traps, most of these systems focus exclusively on studying agricultural pests, rendering them unsuitable for monitoring diverse insect populations. To address this issue, we introduce the Field Automatic Insect Recognition (FAIR)‐Device, a novel nonlethal field tool that relies on semi‐automatic image capture and species identification using artificial intelligence via the iNaturalist platform. Our objective was to develop an automatic, cost‐effective, and nonspecific monitoring solution capable of providing high‐resolution data for assessing insect diversity. During a 26‐day proof‐of‐concept evaluation, the FAIR‐Device recorded 24.8 GB of video, identifying 431 individuals from 9 orders, 50 families, and 69 genera. While improvements are possible, our device demonstrated its potential as a cost‐effective, nonlethal tool for monitoring insect biodiversity. Looking ahead, we envision new monitoring systems such as e‐traps as valuable tools for real‐time insect monitoring, offering unprecedented insights for ecological research and agricultural practices.

Earthworms are a key faunal group in agricultural soils, but little is known on how farming systems affect their communities across wide climatic gradients and how farming system choice might mediate earthworms' exposure to climate conditions. Here, we studied arable soil earthworm communities on wheat fields across a European climatic gradient, covering nine pedo‐climatic zones, from Mediterranean to Boreal (S to N) and from Lusitanian to Pannonian (W to E). In each zone, 20–25 wheat fields under conventional or organic farming were sampled. Community metrics (total abundance, fresh mass, and species richness and composition) were combined with data on climate conditions, soil properties, and field management and analyzed with mixed models. There were no statistically discernible differences between organic and conventional farming for any of the community metrics. The effects of refined arable management factors were also not detected, except for an elevated proportion of subsurface‐feeding earthworms when crop residues were incorporated. Soil properties were not significantly associated with earthworm community variations, which in the case of soil texture was likely due to low variation in the data. Pedo‐climatic zone was an overridingly important factor in explaining the variation in community metrics. The Boreal zone had the highest mean total abundance (179 individuals m⁻²) and fresh mass (86 g m⁻²) of earthworms while the southernmost Mediterranean zones had the lowest metrics (<1 individual m⁻² and <1 g m⁻²). Within each field, species richness was low across the zones, with the highest values being recorded at the Nemoral and North Atlantic zones (mean of 2–3 species per field) and declining from there toward north and south. No litter‐dwelling species were found in the southernmost, Mediterranean zones. These regional trends were discernibly related to climate, with the community metrics declining with the increasing mean annual temperature. The current continent‐wide warming of Europe and related increase of severe and rapid onsetting droughts will likely deteriorate the living conditions of earthworms, particularly in southern Europe. The lack of interaction between the pedo‐climatic zone and the farming system in our data for any of the earthworm community metrics may indicate limited opportunities for alleviating the negative effects of a warming climate in cereal field soils of Europe.

We present detailed annual land cover maps for the Baltic Sea region, spanning more than two decades (2000–2022). The maps provide information on eighteen land cover (LC) classes, including eight general LC types, eight major crop types and grassland, and two peat bog-related classes. Our maps represent the first homogenized annual dataset for the region and address gaps in current land use and land cover products, such as a lack of detail on crop sequences and peat bog exploitation. To create the maps, we used annual multi-temporal remote sensing data combined with a data encoding structure and deep learning classification. We obtained the training data from publicly available open datasets. The maps were validated using independent field survey data from the Land Use/Cover Area Frame Survey (LUCAS) and expert annotations from high-resolution imagery. The quantitative and qualitative results of the maps provide a reliable data source for monitoring agricultural transformations, peat bog exploitation, and restoration activities in the Baltic Sea region and its surrounding countries.

Fish age is an important biological variable required as part of routine stock assessment and analysis of fish population dynamics. Age estimates are traditionally obtained by human experts from the count of ring-like patterns along calcified structures such as otoliths. To automate the process and minimize human bias, modern methods have been designed utilizing the advances in the field of artificial intelligence (AI). While many AI-based methods have been shown to attain satisfactory accuracy, there are concerns regarding the lack of explainability of some early implementations. Consequently, new explainable AI-based approaches based on U-Net and Mask R-CNN have been recently published having direct compatibility with traditional ring counting procedures. Here we further extend this endeavor by creating an interactive website housing these explainable AI methods allowing age readers to be directly involved in the AI training and development. An important aspect of the platform presented in this article is that it allows the additional use of different advanced concepts of Machine Learning (ML) such as transfer learning, ensemble learning and continual learning, which are all shown to be effective in this study.

To produce biogenic phenolic-rich liquids, which could be of great interest to the adhesive, wood preservation and coating industry, beech wood slow pyrolysis liquid (SPL) was extracted with supercritical CO2 (scCO2). To this end, a scCO2 extraction plant was extended with a separation unit with three separators. A stepwise depressurisation of the scCO2 in the separators enabled various fractions of the extracted SPL, with differing compositions, to be collected. During depressurisation, the density of the scCO2 (724 kg/m³–2 kg/m³) and, thus, the solubilities of the extracted substances in scCO2 were reduced in three separators. At a density of 261 kg/m³ in the second separator, extracts with a content of up to 41.1 wt.% GC-detectable monomeric phenolic substances were produced. At lower scCO2 densities in the subsequent separator, the proportion of better scCO2-soluble substances, such as acids, ketones and furans, increased in the extracts.

During fish larvae development functional, morphological, and physiological adaptations are key in larval survival strategies and can determine mortality bottlenecks. For many fish groups such as needlefish, which play crucial roles in marine food webs, studies on early life stages are almost lacking. Herein, the development, with focus on the postcranial skeleton, of the garfish Belone belone (Linnaeus, 1761) is described and a staging system is introduced. Ten larval and juvenile life stages are proposed in three main phases: yolk sac, larval, and juvenile development. During the yolk sac phase the garfish deplete their yolk reservoirs and finish the development of their unpaired fins. During the larval period the lower jaw elongates and the needlenose stage is reached. In the juvenile phase, the upper jaw elongates until both jaws are almost equally long. Since B. belone larvae develop much of their postcranial skeleton in the late embryonic and yolk sac phases they might not experience a severe bottleneck in this early stage such as many other marine fish species. Therefore, young garfish could be more resilient to environmental changes.

In monoculture-dominated landscapes, recovering biodiversity is a priority, but effective restoration strategies have yet to be identified. In this study, we experimentally tested passive and active restoration strategies to recover taxonomic, phylogenetic, and functional diversity of woody plants within 52 tree islands established in an oil palm landscape. Large tree islands and higher initial planted diversity catalyzed diversity recovery, particularly functional diversity at the landscape level. At the local scale, results demonstrated that greater initial planting diversity begets greater diversity of native recruits, overcoming limitations of natural recruitment in highly modified landscapes. Establishing large and diverse tree islands is crucial for safeguarding rare, endemic, and forest-associated species in oil palm landscapes.

Abandoned and even active limestone quarries (excavation sites) can represent important secondary habitats for many species, including wild bees, associated with dry grasslands, which are threatened biodiversity hotspots in Europe. However, is not well understood how interactions between local habitat and landscape characteristics influence the value of limestone quarries for wild bees and how this could guide conservation schemes. We studied how wild bee communities in limestone quarries are affected by landscape variables (connectivity to neighbouring dry grasslands, landscape diversity), local quarry characteristics (area, age, woody vegetation cover, flowering plant species) and their interactions. We surveyed bee communities during 208 transects in 19 quarries in southern Lower Saxony, Germany. In total, we recorded 114 bee species (2360 individuals), including 35 endangered species. High flowering plant species richness positively affected bee abundance and richness. Large quarry area was important for determining the presence of endangered bee species. High levels of woody vegetation cover had a negative effect on bee abundance and richness. Bee abundance and richness can increase with quarry age, but only at sites with moderate woody vegetation cover. We found potentially positive interactions between quarry age and landscape diversity and/or habitat connectivity to neighbouring dry grasslands. In particular, high habitat connectivity ensured stable richness of endangered species in old quarries. Synthesis and applications. Observed negative effects of high woody vegetation cover on bee communities highlight the importance of local management to reduce shrub encroachment and reset successional processes in limestone quarries. Local management is particularly important in old quarries of great ecological value, where the adverse impact of high woody vegetation cover on wild bees appears to be most severe. Large and old quarries with high connectivity to neighbouring dry grasslands are especially valuable for endangered bee species. Therefore, landscape‐scale restoration and conservation of dry grasslands is the most promising approach to promote endangered bee species through enhanced habitat connectivity.

Fisheries science aims to understand and manage marine natural resources. It relies onresource-intensive sampling and data analysis. Within this context, the emergence of machinelearning (ML) systems holds significant promise for understanding disparate components ofthese marine ecosystems and gaining a greater understanding of their dynamics. The goal ofthis paper is to present a review of ML applications in fisheries science. It highlights boththeir advantages over conventional approaches and their drawbacks, particularly in terms ofoperationality and possible robustness issues. This review is organized from small to largescales. It begins with genomics and subsequently expands to individuals (catch items),aggregations of different species in situ , on-board processing, stock/populations assessmentand dynamics, spatial mapping, fishing-related organizational units, and finally ecosystemdynamics. Each field has its own set of challenges, such as pre-processing steps, the quantityand quality of training data, the necessity of appropriate model validation, and knowingwhere ML algorithms are more limited, and we discuss some of these discipline-specificchallenges. The scope of discussion of applied methods ranges from conventional statisticalmethods to data-specific approaches that use a higher level of semantics. The paper concludeswith the potential implications of ML applications on management decisions and a summaryof the benefits and challenges of using these techniques in fisheries.

Agriculture is confronted with several challenges such as climate change, the loss of biodiversity and stagnating productivity. The massive increasing amount of data and new digital technologies promise to overcome them, but they necessitate careful data integration and data management to make them usable. The FAIRagro consortium is part of the National Research Data Infrastructure (NFDI) in Germany and will develop FAIR compliant infrastructure services for the agrosystems science community, which will be integrated in the existing research data infrastructure service landscape. Here we present the initial steps of designing and implementing the FAIRagro middleware infrastructure to connect existing data infrastructures. The middleware will feature services for the seamless data integration across diverse infrastructures. Data and metadata are streamlined for research in agrosystems science by downstream processing in the central FAIRagro Search and Inventory Portal and the data integration and analysis workflow system “SciWIn”.

The West Atlantic trumpetfish Aulostomus maculatus is a species of little commercial importance, but it is frequently used as a study organism in behavioural ecology, and it has been traded in the aquarium industry to some extent. The adult life stage is well described, however its early life history is nearly unknown. This paper provides the first description of post-flexion larvae of A. maculatus, including detailed illustrations, photographs, morphological data, and collection site data of specimens collected during a multipurpose research survey conducted within the Sargasso Sea Subtropical Convergence Zone. The collection site also implies a geographic range expansion, off the continental shelf, of the pelagic larvae stage. This paper hence advances the scientific knowledge about the early life stages, distribution and ecology of this species.

Anthropogenic ammonia (NH3) emissions, of which about 95 % are from agriculture, have led to environmental pollution, resulting in tremendous damage to human health and ecosystems. Thus, the NEC Directive 2016/2284/EU sets national reduction targets for NH3 emissions in individual EU countries. To implement the NEC Directive for NH3 emission targets, Germany amended the Fertilizer Application Ordinance in 2017 and 2020 (DüV_amended) and set the air pollution control regulation, Technical Instructions on Air Quality Control (TA_Luft). This study aimed to evaluate the impact of the DüV_amended on NH3 mitigation from applying livestock manure, digestates, synthetic nitrogen (N) fertilizers, and TA_Luft on housing and storage. This study showed that Germany reached the first national NH3 reduction target in 2020, as set by the NEC directive. The German DüV_amended, a significant policy change, has profoundly impacted NH3 emission mitigation from agriculture after 2017 by implementing measures aimed directly at NH3 reduction, reducing N surpluses, and improving N use efficiency. The reduction in NH3 emissions from synthetic N fertilizers between 2016 and 2022 contributed about 51 % to the decrease from the agricultural sector over the same period. Among the synthetic fertilizers, NH3 reduction from urea between 2016 and 2022 accounted for around 83 % of the total reduction from synthetic N, indicating that the NH3 emissions from urea fertilizer by reducing urea application and mandating urea to be incorporated immediately or to be stabilized with urease inhibitors played a crucial role in the sharp decrease in NH3 emissions over the last years in Germany. Achieving a high yield by lowering the synthetic N rate in this study strongly suggests that optimal reduction in N rate does not necessarily result in yield losses but rather in a pivotal relationship between the agronomic and environmental performance and indicates that the DüV_amended was an effective measure that can reduce the NH3 emissions. Over 80 % of Germany's annual agricultural NH3 emissions in 2021 and 2022 originated from livestock and digestates from energy crops. Mandatory close to the soil band application of slurry and digestates on cultivated cropland since 2020 reduced NH3 emissions. In addition, banning of broadcast application of slurry to grassland and manure incorporation within one hour on uncultivated soils will become mandatory in 2025 to comply with NEC 2030´s target of 29 % NH3 reduction relative to 2005. The recent German air pollution control regulation (TA_Luft) enforces abatement measures such as air purifiers in large poultry and pig housings and covered storage of slurry and digestate storages of large farms. The results of the German NH3 abatement strategy for synthetic N fertilizers may help reduce NH3 emissions worldwide, especially for countries consuming high amounts of urea fertilizers.

Fishes inhabiting the mesopelagic zone of the world's oceans are estimated to account for the majority of the world's fish biomass. They have recently attracted new attention because they are part of the biological carbon pump and have been reconsidered as a contribution to food security. Hence, there is an urgent need to understand how environmental conditions and species interactions shape their assemblages, and how they contribute to the functioning of marine ecosystems. Trait‐based approaches are valuable for addressing these types of questions. However, the biology and ecology of mesopelagic fishes are understudied compared to fishes in shallow and epipelagic waters. Here, we synthesise existing knowledge of traits of mesopelagic fishes and relate them to their role in survival, feeding and growth and reproduction, the key functions that contribute to fitness. Vertical migrations, specialised vision and the use of bioluminescence are among the most striking adaptations to the conditions in the mesopelagic realm. Many traits are interrelated as a result of trade‐offs, which may help to understand selection pressures. While morphological traits are straightforward to observe, major knowledge gaps exist for traits that require frequent sampling, assessment under experimental conditions or age determination. The unique adaptations of mesopelagic fishes need to be included in management strategies as well as fundamental research of the habitat.

Global deforestation and forest degradation threaten the sustainability of natural and human systems. Forest landscape restoration , through active approaches such as plantations, woodlots, boundary planting, and agroforestry, and passive approaches like exclosures, presents an opportunity to mitigate adverse effects, enhance ecosystem service recovery, and associated benefits for livelihoods. Here, using different spatial scales, we compare the contribution of both approaches to the recovery of plant diversity in southern Ethiopia. Using forest inventory data (891 plots) from multi-aged stands, we estimated and compared alpha (α), beta (β), and gamma (γ) diversity in regeneration and tree layers between the approaches. We observed increasing α-diversity in the order grazing lands-active-passive-forest sites. β-Diversity revealed similarity between passively restored sites and natural forests. γ-Diversity was higher in active restoration for the regeneration layer, but passive restoration had higher γ-diversity in the tree layer. For both approaches, γ-diversity was consistently highest in intermediate-aged stands (10-20 years). Results highlight the potential of active restoration strategies to facilitate vegetation recovery in human-dominated landscapes, especially when management allows natural regeneration, while stand age variation may be associated with disturbance intensities for both approaches. Our results support a paradigm shift toward implementation of a mixture of these approaches in the landscapes to meet increasing human demands while restoring important ecosystem services like biodiversity. We recommend enhancing species diversity on restored sites to improve performance and ecosystem service recovery. On actively restored sites, we recommend protecting regenerated species; on passively restored sites, enrichment planting, increased protection, and sustainable utilization.

The water potential in drying soils, comprising both matric potential and osmotic potential components, can be measured using the dew point method (DPM). By combining DPM data with retention curve data acquired from techniques such as the suction plate method or the simplified evaporation method (SEM), it becomes possible to determine the soil water retention curve across the entire moisture spectrum. However, as the latter methods only determine the matric potential, the osmotic potential component in DPM data must either be negligible or known so that osmotic and matric potential components can be separated. This study aims to critically analyse common approaches for calculating the osmotic potential. To achieve this, we measured the water retention properties of a silt loam, a sandy loam and a sand across the entire moisture range by combining SEM and DPM. By using almost salt‐free soil material, we characterized reference water retention curves with negligible osmotic potential components. The impact of salt on water potential was analysed by conditioning soils with MgCl 2 solutions of different concentrations, drying them, and measuring the water potential at different water contents using the DPM. The resulting water potentials were compared to the reference potentials and differences were interpreted as the osmotic potential component. The DPM‐measured water potentials in drying soils can be significantly affected by osmotic potential, especially at higher matric potentials (low suctions). Two models accounting for ideal and one model accounting for non‐ideal electrolyte behaviour were used to compare osmotic potential predictions with measurements. At low to medium salt concentrations, all models performed fairly well. At high concentrations, only the model accounting for non‐ideal behaviour predicted the osmotic potential satisfactorily, whereas at very high concentrations, all models underestimated the impact of osmotic potential on water potential. This suggests that the surface properties of the soil matrix, such as the specific surface area and surface charges, may lead to a decrease in osmotic potential beyond what is expected in pure solutions.

Phylogeographic studies on widespread rainforest species from West and Central Africa often reveal genetic discontinuities. These discontinuities can originate from past barriers to gene flow resulting from long-lasting population fragmentation during glacial periods, according to the forest refuge hypothesis. This study 69 nuclear SNPs, 13 plastid SNPs, and 24 mitochondrial SNPs to characterized the distribution of genetic diversity in 377 individuals of the widespread tropical tree Khaya ivorensis, in western and central African evergreen forests. Two very well-differentiated nuclear genetic clusters (FST = 0.28) are located respectively in West and Central Africa. The gradual transition of allele frequencies between the clusters across a broad geographic area going from Cameroon to Nigeria accords with the recognition of a single species, although we show an incipient divergence that could eventually lead to the separation of two taxa. The two clusters have similar genetic diversity at nuclear SNPs. However, the cytoplasmic data revealed high haplotypic diversity and numerous endemic haplotypes in Central Africa, and only one widespread haplotype in West Africa, suggesting an ancient colonization of West Africa from Central Africa. The genetic diversity inside and outside putative forest refugia (Anhuf et al., Palaeogeogr Palaeoclimatol Palaeoecol 239:510–527, 2006) does not differ significantly in either genetic cluster. Hence, we cannot confirm that forest refugia played a particular role in the pattern of distribution of genetic diversity in K. ivorensis. Owing to the high haplotypic diversity of their populations, Central Africa, especially Gabon, constitutes a priority area for the conservation of the genetic diversity of K. ivorensis.

The banana value chain produces over 4 tonnes of waste biomass for every tonne of bananas harvested, including leaves, pseudostems, peels, rejected fruits, rhizomes, and empty fruit bunches. With rising fossil fuel costs and environmental concerns, these wastes present opportunities for alternative biofuel production through thermochemical processing and densification. This review examines the properties of various banana plant wastes, their pretreatments, and suitability for processes like pyrolysis, torrefaction, and hydrothermal carbonization, as well as briquetting. Banana plant wastes vary in physico-chemical properties depending on the biomass type. Their high volatile matter content (70.5–89.1%db) makes them better suited for bio-oil and gas production rather than biochar. Pretreatment methods such as water-washing, alkaline treatment, drying, pressing, chopping, grinding, and milling may be needed before thermochemical conversion of the wastes. Among conversion routes, pyrolysis is the most studied, followed by hydrothermal carbonization and dry torrefaction. The hydraulic press is the most commonly used technology for briquetting banana plant wastes. Depending on factors such as binder-to-biomass ratio, dwell time, and compaction pressure, this method can produce briquettes with compressive strength ranging from 1.33 to 38.39 MPa, which exceeds the minimum acceptable level of 0.38 MPa. However, these briquettes can have ash content as high as > 20%db, which can reduce their calorific value, increase the risk of ash slagging and fouling in combustion systems, as well as lead to increased emission of particulate matter during combustion. While thermochemical conversion and briquetting of banana plant wastes may incur significant costs, these could be offset by the low cost of the raw materials, improved fuel properties, and better handling, transportation, and storage. Research efforts should focus on ascertaining the emission potential of thermochemical conversion and briquetting of banana plant wastes, which could encourage wider acceptance of these technologies, especially considering growing awareness about the need for environmental protection. Graphical abstract