Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.03.24.713891

Grazing and mowing enhance aquatic macroinvertebrate diversity of small artificial ponds in eutrophic landscape

Abstract

Artificial pond construction is widely used in wetland restoration, yet biodiversity outcomes depend strongly on design and subsequent management. We tested how different regimes (grazing, mowing, and no management) influence habitat structure, water conditions, and aquatic macroinvertebrate diversity in newly excavated experimental ponds within an eutrophic wetland in South Moravia (Czechia). Across four focal groups (Mollusca, Odonata, Coleoptera, Heteroptera), we observed rapid colonisation of the newly built ponds. Species richness and densities rose during early development, dropped after drying events, and then partially recovered, indicating repeated "resetting" of communities under fluctuating hydrology. Periodic drying also prevented fish stock establishment. Management significantly affected species composition and both grazed and mowed ponds displayed higher densities (abundances) than controls, but differed only slightly in terms of species richness. The grazed ponds were characterised by high sunlight exposure, reduced reed dominance, and trampling-generated high littoral heterogeneity. These ponds showed highest numbers of taxa adapted to shallow and warm waterbodies, muddy substrate, semiaquatic microhabitats, or newly emerged and disturbed habitats. The mowed ponds promoted dense submergent vegetation, supporting Odonata representation and other taxa requiring aquatic vegetation. The control ponds remained highly shaded by high-grown reed, organic-matter rich, hosting a set of taxa tolerant of low-light, low-oxygen conditions. At the wetland scale, multiple small ponds increased overall diversity through high between-pond heterogeneity. Our results highlight that pond construction alone is insufficient for wetland restoration: follow-up long-term management regimes, especially extensive grazing, can rapidly generate structural heterogeneity and sustain diverse aquatic invertebrate assemblages in eutrophic wetlands.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Petruzelova, J., Petruzela, J., Cerna, A., Kotasova Adamkova, M.. 2026-03-26. Grazing and mowing enhance aquatic macroinvertebrate diversity of small artificial ponds in eutrophic landscape. https://doi.org/10.64898/2026.03.24.713891

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Operationalising the context in regenerative agriculture: decision-making and farm variability

Soil degradation is a widespread challenge that requires a broad response at the individual farm level. To ensure effectivity, the practices should be tailored to the farm context: land manager objectives and farm specific challenges. These have however been difficult to quantify. Here we demonstrate that a workable farm context can be created based on a value survey, open satellite and soil data, and published models for vegetation gross primary productivity and soil erosion. Based on the findings, despite individual differences, farmers value profitability and operational efficiency, but also biodiversity and soil health. At least the regenerative farmers surveyed also value working for the greater good more than maintaining tradition or power. In spite of wide differences in farm production orientation, we also found that each farm also had a broad variation in individual fields GPP. Most fields have a stable GPP level, which is either high or low, and that there is a 2-3-fold difference between the weakest and best producing fields indicating the potential for improving GPP by improving the growing conditions on currently weak fields. In addition, soil loss was found to be highly concentrated in critical source areas, where 10% of the field area contributed to 50% of the soil loss. Overall, open data can be linked to modelling workflows to rapidly produce a decision-making context for farmers. This facilitates benchmarking and co-learning as well as enables land managers and advisors to identify the farm context for planning effective responses to soil degradation.

ecology↗

Fly, land, listen: Autonomous intermittent locomotion enables scalable low-noise drone ecoacoustic surveys

Ecoacoustic monitoring is enabling scientists and land managers to monitor and manage biodiversity more effectively and cost-efficiently in the face of human pressures and rapidly changing climates. Currently, most ecoacoustic surveys use manually deployed static sensors to record data, limiting the scale and reach of surveying efforts. Here we present a proof-of-concept autonomous drone platform that can use intermittent locomotion to conduct ecoacoustic surveys using an onboard sensor. Our custom prototype is able to fly, navigate, and avoid obstacles autonomously, land at a pre-determined location, record audio from an onboard microphone whilst static, before taking off and moving to the next sampling site. Autonomous navigation and operation enable greater sampling flexibility, reach, and scalability. Furthermore, by recording audio only whilst landed, noise from the drone's rotors does not mask signals or disturb animals, simplifying signal processing and downstream ecological analyses. We conducted trials in a scrubland habitat at the Knepp Estate in West Sussex, where our prototype demonstrated successful autonomous navigation and obstacle avoidance. Furthermore, we found that avian biodiversity data collected from the drone platform was comparable to that from traditional static acoustic sensor deployments, and that vocalisation patterns were not significantly impacted by the noise of the drone arriving or leaving a site. While scaled deployments of our technology would require further technical and regulatory challenges to be solved, our first demonstration of autonomous intermittent robotics-assisted ecoacoustic surveys lays the foundations for more cost-effective and far-reaching biodiversity surveys, with transformative potential for conservation, agricultural management, biosecurity, and more.

ecology↗

Do higher-order moments improve inference of population dynamics?

Fitting mathematical models of population dynamics to microbial time-series data allows us to estimate the ecological processes and interactions taking place in the microbiome. Repeated experiments of microbial systems yield replicates which slightly differ from each other. Some of this variability arises due to the fact that births and deaths occur at random. Most prior work focuses on fitting a deterministic mathematical model to the average across replicates. We use a stochastic model to fit the variability to the observed variability across replicates. Using a simulation-driven approach, we study the conditions under which our approach allows us to infer a larger fraction of ecological parameters correctly. We observe a substantial improvement in parameter inference. Lastly, our Bayesian approach not only allows us to incorporate prior information about the system, but also provides a distribution of parameters which conveys some idea of the uncertainty of the estimates.

ecology↗