Adapting to change: Exploring the consequences of climate-induced host plant shifts in two specialist Lepidoptera species.

Asynchronous migration of insect herbivores and their host plants towards higher elevations following climate warming is expected to generate novel plant-insect interactions. While the disassociation of specialised interactions can challenge species' persistence, consequences for specialised low-elevation insect herbivores encountering novel high-elevation plants under climate change remain largely unknown. To explore the ability of two low-elevation Lepidoptera species, and , to undergo shifts from low- to high-elevation host plants, we combined a translocation experiment performed at two elevations in the Swiss Alps with experiments conducted under controlled conditions.

Multispecies deep learning using citizen science data produces more informative plant community models.

In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. Here, we map fine-grained spatiotemporal distributions for thousands of species, using deep neural networks (DNNs) and ubiquitous citizen science data. Based on 6.

The genome and population genomics of allopolyploid Coffea arabica reveal the diversification history of modern coffee cultivars.

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C.