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Biology subjects

Clough, Y.

Publications and source records attributed to Clough, Y..

3 recordsLinked to original sources

Climate-driven specialisation in plant-pollinator networks peaks outside the tropics

Pollination is a key ecological process sustaining biodiversity and food security, yet global patterns of plant-pollinator specialisation have remained unresolved. Using the largest global dataset of quantitative networks (>3,400 networks, >110,000 interactions), we show that the latitudinal specialisation gradient (LSG) exists, but it is non-linear, hemispherically asymmetric, and strongly taxon-dependent. Network-level and pollinator specialisation were lowest in the tropics and peaked at northern mid-latitudes, whereas plants tended to become more specialised toward higher latitudes. Climate consistently outperformed latitude, species richness, and environmental productivity as a predictor of these patterns. Specialisation declined with increasing temperature, rose with moderate rainfall before declining at the wettest sites, and increased with temperature seasonality, but plants and pollinators responded differently to these drivers. Functional groups diverged strongly: ectothermic insects were most specialised in cooler, seasonal climates, while birds showed weaker links to latitude but reduced specialisation in wetter regions. These findings demonstrate that climate, rather than latitude or species richness, structures global variation in specialisation. Because warmer and less seasonal climates promote generalisation, climate change is likely to disrupt the most specialised pollination systems, unevenly across taxa and regions, with important consequences for biodiversity and ecosystem stability.

ecology↗

Airborne environmental DNA metabarcoding for the monitoring of terrestrial insects - a proof of concept

Biodiversity is in decline due to human land use, exploitation, and climate change. To be able to counteract this alarming trend it is paramount to closely monitor biodiversity at global scales. Because this is practically impossible with traditional methods, the last decade has seen a strong push for solutions. In aquatic ecosystems the monitoring of species from environmental DNA (eDNA) has emerged as one of the most powerful tools at our disposal but in terrestrial ecosystems the power of eDNA for monitoring has so far been hampered by the local scale of the samples. In this study we report the first attempt to detect insects from airborne eDNA. We compare our results to two traditional insect monitoring projects (1) using light trapping for moth monitoring and (2) transect counts for the monitoring of butterflies and wild bees. While we failed to detect many of the same species monitored with the traditional methods, airborne eDNA metabarcoding revealed DNA from from six classes of Arthropods, and twelve order of Insects - including representatives from all of the four largest orders: Diptera (flies), Lepidoptera (butterflies and moths), Coleoptera (beetles) and Hymenoptera (bees, wasps and ants). We also recovered DNA from nine species of vertebrates, including frogs, birds and mammals as well as from 12 other phyla. We suggest that airborne eDNA has the potential to become a powerful tool for terrestrial biodiversity monitoring, with many impactful applications including the monitoring of pests, invasive or endangered species or disease vectors.

ecology↗

Reducing ecological complexity using the archetype approach - an application to natural pest control

Natural control of crop pests has the potential to complement or replace intensive agricultural practices, but its mainstream application requires reliable predictions in diverse socioecological settings. In lack of a widely accepted model of natural pest control, we review existing modelling approaches and critically examine their potential to provide understanding and predictions across agricultural landscapes. Models that explicitly represent the underlying mechanisms are better positioned to represent the diversity and context sensitivity of natural pest control than correlative models. Such mechanistic models have used diverse techniques to represent crop-pest-enemy combinations at various spatiotemporal scales. However, certain regions of the world and socioeconomic aspects of natural pest control are underrepresented, while modelling approaches are restricted by a fundamental trade-off between generality and realism. We propose that modelling natural pest control across agroecosystems requires a framework of context-specific generalizations, based on empirical evidence and theoretical expectations. Reviewed models of natural pest control indicate potential attributes of such a general predictive framework.

ecology↗