Biology subjects

Righetti, D.

Publications and source records attributed to Righetti, D..

3 recordsLinked to original sources

bioRxiv2023

Mapping global marine biodiversity under sparse data conditions

Sparse and spatiotemporally highly uneven sampling efforts pose major challenges to obtaining accurate species and biodiversity distributions. Here, we demonstrate how limited surveys can be integrated with global models to uncover hotspots and distributions of marine biodiversity. We test the skill of recent and advanced species distribution model setups to predict the global biodiversity of >560 phytoplankton species from 183,000 samples. Recent setups attain quasi-null skill, while models optimized for sparse data explain up to 91% of directly observed species richness variations. Using a refined spatial cross-validation approach to address data sparsity at multiple temporal resolutions we find that background choices are the most critical step. Predictor variables selected from broad sets of drivers and tuned for each species individually improve the models ability in identifying richness hotspots and latitude gradients. Optimal setups identify tropical hotspots, while common ones lead to polar hotspots disjunct from general marine diversity. Our results show that unless great care is taken to validate models, conservation areas in the ocean may be misplaced. Yet a game-changing advance in mapping diversity can be achieved by addressing data-sparse conditions that prevail for >80% of extant marine species. Authorship statementAll authors designed the research and contributed to the writing. D.R. designed the multiscale validation and predictor selection methods, developed the figures with input by M.V. and N.E.Z., performed research, and wrote the first draft.

ecology↗

bioRxiv2022

Strategies for sampling pseudo-absences for species distribution models in complex mountainous terrain

O_LIPredictions from species distribution models (SDMs) that rely on presence-only data are strongly influenced by how pseudo-absences are derived. However, which strategies to generate pseudo-absences give rise to faithful SDMs in complex mountainous terrain, and whether species-specific or generic strategies perform better remain open questions. C_LIO_LIHere, across 500 plant species, we investigated comprehensively how predictions of SDMs at a 93 m spatial resolution are influenced by pseudo-absence strategies, using the complex topography of the Swiss mountains as a model system. We used five generic (random, equal-stratified, proportional-stratified, target, density) and three species-specific (target specific, density specific and geographic specific) approaches to derive pseudo-absence data. We conducted performance tests for each of our eight strategies in combination with (a) spatial bias, generated within our occurrence dataset on sites with highest sampling density, to investigate how this common bias problem influences the performance of pseudo-absence sampling strategies, and (b) a new approach to reduce model extrapolation in environmental space by including background data from all environmental conditions of the study area. SDMs were evaluated against an independent and well-sampled dataset of true presences and absences. C_LIO_LIThe random, the density (generic), and the geographic specific (species-specific) strategies consistently performed best, even in cases of strong spatial sampling bias in the occurrence data. Including a background of environmentally stratified pseudo-absences improved predictions of species distributions towards environmental extremes, and significantly reduced spatial extrapolations of model predictions in environmental space. C_LIO_LIOur results indicate that both generic and species-specific pseudo-absence strategies allow estimating robust SDMs and we provide clear recommendations which strategies to choose in complex terrain and when presence data are prone to high sampling bias. In datasets with strong sampling bias, most pseudo-absence strategies produce extrapolation problems and we additionally recommend environmentally stratified pseudo-absences in these cases. Overall, in species rich datasets the use of complex and computationally demanding, species-specific pseudo-absence strategies may not always be justified compared to simpler generic approaches. C_LI

ecology↗

bioRxiv2021

A highly endemic area of Echinococcus multilocula is identified through a comparative re-assessment of prevalence in red fox (Vulpes vulpes), Alto Adige (Italy: 2019-2020)

BackgroundSurveillance of E. multilocularis at the edge of its range is hindered by fragmented distributional patterns and low prevalence and burden in definitive hosts. Thus, tests with adequate levels of sensitivity are especially important for discriminating between infected and non-infected areas. AimWe reassessed the prevalence of E. multilocularis at the southern border of its distribution in Alto Adige (Italy), to improve surveillance in wildlife and provide more accurate estimates of exposure risk. MethodsWe compared results from the diagnostic test currently implemented for surveillance (based on Coproscopy+Multiplex PCR - CMPCR), against a real-time quantitative PCR (qPCR) for 235 fox faeces collected in 2019-2020. The performances of the two tests were estimated using a scraping technique (SFCT) as the gold standard applied to the small intestines of a subsample (n=123) of the same hosts. True prevalence was calculated and sample size required by each faecal test for the detection of the parasite was then estimated. ResultsTrue prevalence of E. multilocularis in foxes (14.3%) was definitely higher than reported in the last decade (never >5% from 2012 to 2018). The qPCR also had a higher sensitivity (83%) compared to CMPCR (21%). Agreement with the gold standard was far higher for qPCR (0.816) than CMPCR (0.298) as well, determining a smaller sample size required to detect the disease. ConclusionsAlto Adige should be considered a highly endemic area. Surveillance at the edges of E. multilocularis distribution should adopt qPCR diagnostics on definitive hosts on a small geographic scale. AUTHOR SUMMARYEchinococcus multilocularis is an intestinal flatworm, whose adult stage in Europe is harboured mainly by the red fox (Vulpes vulpes), which spreads parasites eggs by faeces. This parasite is the agent of a severe and potentially lethal zoonosis, the alveolar echinococcosis, affecting humans after accidental ingestion of parasites eggs. In the Italian Alpine area, which represents the southernmost border of E. multilocularis European range, surveillance is hindered by a fragmented distributional pattern, where presence in foxes has been consistently reported only in few isolated foci in Alto Adige (Bolzano province - Italy) of low prevalence. In order to improve the efficiency of monitoring efforts, we tested the performances of two diagnostic protocols on fox faeces (sedimentation, filtration, counting technique followed by standard PCR, and whole stool real-time PCR) against a benchmark technique on fox intestines (scraping, filtration, counting technique - considered as the gold standard). This allowed not only to determine qPCR as a far more sensitive and sample-efficient diagnostic tool for E. multilocularis detection in marginally affected areas, but also to re-assess its prevalence in Alto Adige, which should be considered a highly endemic area. Consequent actions in the field and modifications in the surveillance strategy should be therefore considered.

molecular biology↗