The cover image relates to the Research Article https://doi.org/10.1111/ddi.70070 “Direct Integration of Population Genetics and Dynamic Species Distribution Modelling Improves Predictions of Post-Glacial History of Piper nigrum” Photo credit: Sandeep Sen
Morera-Pujol, V., Catry, P., Magalhães, M. et al. 2025. “Migratory Connectivity and Non-Breeding Habitat Segregation Across Biogeographical Scales in Closely Related Seabird Taxa.” Diversity and Distributions 31: e70013. https://doi.org/10.1111/ddi.70013.
The affiliation information for author Isabel Afán was incorrect in the published article. The correct affiliation information should be: Institut de Ciències del Mar, CSIC, Barcelona, Spain.
The data availability statement contained erroneous links in the published article. The correct statement should read as follows: ‘The novel code developed for this manuscript can be found at https://github.com/VirginiaMorera/Migratory-connectivity and the tracking data necessary to perform the analyses can be downloaded at https://doi.org/10.5061/dryad.g79cnp5z7. The data on colony locations and breeding populations is available in the Supporting Information of Morera-Pujol et al., 2023. Methods to detect spatial biases in tracking studies caused by differential representativeness of individuals, populations and time. Diversity and Distributions, 29, 19–38. https://doi.org/10.1111/ddi.13642’.
We apologize for this error.
Subjective study area delineation in conservation planning often overlooks species occurrences integrality, truncating the ecological niches. Incorporating occurrences from expanded areas into species distribution prediction within the study area provides an innovative approach to mitigate negative impacts, but the conservation effectiveness of this approach requires further clarification.
We selected the Southeast Himalaya Biodiversity Priority Conservation Area and the Himalayas biogeographic region as the target and expanded areas, respectively.
We set three scenarios by extracting species occurrences from the target area, expanded area, and both areas (scenarios 1, 2, and 3, respectively). Using MaxEnt for predicting the potential distributions of species (SPDs) and Zonation for identifying priority conservation areas (PCAs) across the three scenarios, we evaluated the SPD prediction accuracy, conservation effectiveness, and ecological representativeness.
Incorporating data from the expanded area in scenarios 2 and 3 improved the prediction accuracy and covered a wider SPD range than scenario 1. High-richness areas and PCAs in scenarios 2 and 3 were identified in the Kangrigebu South Wing Mountains, Salween and Lancangjiang Incisive Mountains, and southern Brahmaputra Great Turn and Upper Salween Incisive Mountains. These PCAs improved the coverage of the SPD areas (77.74%–82.20%) and priority forest and wetland ecosystems (11.86%–12.84%). In contrast, the PCAs in scenario 1 had a relatively larger distribution in the Himalayas Central Mountains, covering a higher proportion of their own SPD areas (83.75%) and priority steppe ecosystem (31.55%). Overall, scenarios 2 and 3 demonstrated greater conservation effectiveness and ecological representativeness, with minimal differences between them, and both outperformed scenario 1.
Our study proposed an innovative approach that expanded the study area to biogeographic regions and supplemented species occurrences from these expanded areas, thereby improving the prediction accuracy of SPDs and conservation effectiveness, while providing an easily implementable and generalizable framework in data deficient areas.
Climate change has a strong impact on species ranges and the genetic structure of populations, yet conclusions are often subject to large uncertainties when both are analysed independently. Here, we develop a novel framework to directly integrate population genetics and dynamic species distribution modelling to reduce such uncertainties when reconstructing the post-glacial history of black pepper.
Western Ghats, India.
Genetic data of 243 individuals from 14 populations of wild Piper nigrum were derived from six chloroplast and five nuclear DNA simple sequence repeats (SSRs). Dynamic species distribution models (DSDMs) were applied since the Last Glacial Maximum (LGM, 21,000 years BP) based on paleo-climatic suitability at a high resolution (1 km, 100 years) and evaluated for a wide range of estimated migration rates and climate niches of the species. Population genetics and DSDMs were finally combined in a genetically informed DSDM, in which the estimated model parameters were optimised by maximising the correlation between the genetic diversity of the populations and their simulated colonisation history since the LGM.
We observed higher gene diversity, haplotype richness, and allelic richness at lower latitudes, and two major phylogeographic groups belonging to the southern and central Western Ghats. Demographic inference from chloroplast SSRs estimated the split of these groups around the LGM. DSDMs showed a high uncertainty in parameter estimates, which were clearly reduced for the genetically informed DSDM. With this model, the correlation between genetic diversity and colonisation time was stronger than the correlation with latitude, and the simulation showed a northward expansion from low-latitude refugia and a recent fragmentation of the species range.
Our integrative approach reduces uncertainty in DSDMs and facilitates the interpretation of the population genetic structure. This added value is not given when population genetics and species distribution modelling are applied independently and merely compared.
Rapid shifts in marine species distributions driven by ocean warming require more effective monitoring across entire ranges to detect emerging ecological change. Traditionally, visual surveys have been used to track these distributional shifts, but they often overlook small-bodied, rare or cryptic species, potentially underestimating range changes. Environmental DNA (eDNA) bypasses these limitations, yet its effectiveness in detecting species near their range limits remains understudied.
Eastern Australia.
We combined eDNA metabarcoding and visual surveys to assess reef fish communities across nine sites spanning a 2000-km latitudinal gradient within a global warming hotspot encapsulating tropical, subtropical and temperate reefs. Variation in detectability across methods and biogeographic ranges was also assessed at the level of functional traits (trophic guild, thermal guild and water column position).
eDNA and visual surveys revealed different fish species compositions, potentially underestimating the extent of fish biogeographic ranges. eDNA detected 44 more unique tropical species than visual surveys across their range, and was more effective at detecting tropical carnivores, omnivores, invertivores, planktivores, detritivores and all water column positions. In contrast, visual surveys were more effective at detecting temperate carnivores, invertivores and benthic species. For tropical fishes at their cold range edge in temperate ecosystems, eDNA identified 12 unique species, including herbivores and cryptic species not previously recorded by long-term visual surveys. Contrastingly, eDNA detected 20 fewer temperate species than visual surveys across their biogeographic range and was less effective (five unique species) than visual surveys (nine unique species) at detecting temperate species at their warm trailing range in subtropical ecosystems.
Combining eDNA and visual surveys improves the detection of reef fishes near the limits of their known distributions. This approach helps reveal overlooked species, particularly those that are cryptic, rare or low in abundance, and supports more accurate assessments of species distributions across biogeographic gradients.
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