Small but visible: Predicting rare bryophyte distribution and richness patterns using remote sensing-based ensembles of small models.
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ABSTRACT:
SUBMITTER: Cerrejon C
PROVIDER: S-EPMC8735603 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A large amount of data for inconspicuous taxa is stored in natural history collections; however, this information is often neglected for biodiversity patterns studies. Here, we evaluate the performance of direct interpolation of museum collections data, equivalent to the traditional approach used in bryophyte conservation planning, and stacked species distribution models (S-SDMs) to produce reliable reconstructions of species richness patterns, given that differences between these methods have been insufficiently evaluated for inconspicuous taxa. Our objective was to contrast if species distribution models produce better inferences of diversity richness than simply selecting areas with the higher species numbers. As model species, we selected Iberian species of the genus Grimmia (Bryophyta), and we used four well-collected areas to compare and validate the following models: 1) four Maxent richness models, each generated without the data from one of the four areas, and a reference model created using all of the data and 2) four richness models obtained through direct spatial interpolation, each generated without the data from one area, and a reference model created with all of the data. The correlations between the partial and reference Maxent models were higher in all cases (0.45 to 0.99), whereas the correlations between the spatial interpolation models were negative and weak (-0.3 to -0.06). Our results demonstrate for the first time that S-SDMs offer a useful tool for identifying detailed richness patterns for inconspicuous taxa such as bryophytes and improving incomplete distributions by assessing the potential richness of under-surveyed areas, filling major gaps in the available data. In addition, the proposed strategy would enhance the value of the vast number of specimens housed in biological collections.
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Project description:In stark contrast to the wealth of detail about C. elegans developmental biology and molecular genetics, biologists lack basic data for understanding the abundance and distribution of Caenorhabditis species in natural areas that are unperturbed by human influence.Here we report the analysis of dense sampling from a small, remote site in the Amazonian rain forest of the Nouragues Natural Reserve in French Guiana.Sampling of rotting fruits and flowers revealed proliferating populations of Caenorhabditis, with up to three different species co-occurring within a single substrate sample, indicating remarkable overlap of local microhabitats. We isolated six species, representing the highest local species richness for Caenorhabditis encountered to date, including both tropically cosmopolitan and geographically restricted species not previously isolated elsewhere. We also documented the structure of within-species molecular diversity at multiple spatial scales, focusing on 57 C. briggsae isolates from French Guiana. Two distinct genetic subgroups co-occur even within a single fruit. However, the structure of C. briggsae population genetic diversity in French Guiana does not result from strong local patterning but instead presents a microcosm of global patterns of differentiation. We further integrate our observations with new data from nearly 50 additional recently collected C. briggsae isolates from both tropical and temperate regions of the world to re-evaluate local and global patterns of intraspecific diversity, providing the most comprehensive analysis to date for C. briggsae population structure across multiple spatial scales.The abundance and species richness of Caenorhabditis nematodes is high in a Neotropical rainforest habitat that is subject to minimal human interference. Microhabitat preferences overlap for different local species, although global distributions include both cosmopolitan and geographically restricted groups. Local samples for the cosmopolitan C. briggsae mirror its pan-tropical patterns of intraspecific polymorphism. It remains an important challenge to decipher what drives Caenorhabditis distributions and diversity within and between species.
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Project description:Biodiversity is rapidly changing due to changes in the climate and human related activities; thus, the accurate predictions of species composition and diversity are critical to developing conservation actions and management strategies. In this paper, using satellite remote sensing products as covariates, we constructed stacked species distribution models (S-SDMs) under a Bayesian framework to build next-generation biodiversity models. Model performance of these models was assessed using oak assemblages distributed across the continental United States obtained from the National Ecological Observatory Network (NEON). This study represents an attempt to evaluate the integrated predictions of biodiversity models-including assemblage diversity and composition-obtained by stacking next-generation SDMs. We found that applying constraints to assemblage predictions, such as using the probability ranking rule, does not improve biodiversity prediction models. Furthermore, we found that independent of the stacking procedure (bS-SDM versus pS-SDM versus cS-SDM), these kinds of next-generation biodiversity models do not accurately recover the observed species composition at the plot level or ecological-community scales (NEON plots are 400 m2). However, these models do return reasonable predictions at macroecological scales, i.e., moderately to highly correct assignments of species identities at the scale of NEON sites (mean area ~ 27 km2). Our results provide insights for advancing the accuracy of prediction of assemblage diversity and composition at different spatial scales globally. An important task for future studies is to evaluate the reliability of combining S-SDMs with direct detection of species using image spectroscopy to build a new generation of biodiversity models that accurately predict and monitor ecological assemblages through time and space.
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Project description:An investigation of terrestrial bryophyte species diversity and community structure along an altitudinal gradient from 2,001 to 4,221 m a.s.l. in Gongga Mountain in Sichuan, China was carried out in June 2010. Factors which might affect bryophyte species composition and diversity, including climate, elevation, slope, depth of litter, vegetation type, soil pH and soil Eh, were examined to understand the altitudinal feature of bryophyte distribution. A total of 14 representative elevations were chosen along an altitudinal gradient, with study sites at each elevation chosen according to habitat type (forests, grasslands) and accessibility. At each elevation, three 100 m × 2 m transects that are 50 m apart were set along the contour line, and three 50 cm × 50 cm quadrats were set along each transect at an interval of 30 m. Species diversity, cover, biomass, and thickness of terrestrial bryophytes were examined. A total of 165 species, including 42 liverworts and 123 mosses, are recorded in Gongga mountain. Ground bryophyte species richness does not show any clear elevation trend. The terrestrial bryophyte cover increases with elevation. The terrestrial bryophyte biomass and thickness display a clear humped relationship with the elevation, with the maximum around 3,758 m. At this altitude, biomass is 700.3 g m(-2) and the maximum thickness is 8 cm. Bryophyte distribution is primarily associated with the depth of litter, the air temperature and the precipitation. Further studies are necessary to include other epiphytes types and vascular vegetation in a larger altitudinal range.
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Project description:Species richness on oceanic islands has been related to a series of ecological factors including island size and isolation (i.e. the Equilibrium Model of Island Biogeography, EMIB), habitat diversity, climate (i.e., temperature and precipitation) and more recently island ontogeny (i.e. the General Dynamic Model of oceanic island biogeography, GDM). Here we evaluate the relationship of these factors with the diversity of bryophytes in the Macaronesian region (Azores, Madeira, Canary Islands and Cape Verde). The predictive power of EMIB, habitat diversity, climate and the GDM on total bryophyte richness, as well as moss and liverwort richness (the two dominant bryophyte groups), was evaluated through ordinary least squares regressions. After choosing the best subset of variables using inference statistics, we used partial regression analyses to identify the independent and shared effects of each model. The variables included within each model were similar for mosses and liverworts, with orographic mist layer being one of the most important predictors of richness. Models combining climate with either the GDM or habitat diversity explained most of richness variation (up to 91%). There was a high portion of shared variance between all pairwise combinations of factors in mosses, while in liverworts around half of the variability in species richness was accounted for exclusively by climate. Our results suggest that the effects of climate and habitat are strong and prevalent in this region, while geographical factors have limited influence on Macaronesian bryophyte diversity. Although climate is of great importance for liverwort richness, in mosses its effect is similar to or, at least, indiscernible from the effect of habitat diversity and, strikingly, the effect of island ontogeny. These results indicate that for highly vagile taxa on oceanic islands, the dispersal process may be less important for successful colonization than the availability of suitable ecological conditions during the establishment phase.
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