Biology subjects

Ishihama, F.

Publications and source records attributed to Ishihama, F..

3 recordsLinked to original sources

bioRxiv2023

Scalable phylogenetic Gaussian process models improve the detectability of environmental signals on extinction risks for many Red List species

1. Conservation biologists have a daunting task of understanding the causes of species decline associated with anthropogenic factors and predicting the extinction risk of a growing number of endangered species. By stabilising estimates with information on closely related species, phylogenetic information among species can bridge gaps in information on species with small sample sizes when modelling large numbers of endangered species. However, modelling many species with the Gaussian process (GP), which underlies the evolutionary process of phylogenetic random effects, remains a challenge owing to the computational burden in estimating the large variance-covariance matrix. 2. Here, we applied a phylogenetic generalised mixed model with random slopes and random intercepts to 1,010 endangered vascular plant taxa in Japan following phylogenetic GPs implemented by nearest neighbour GP (NNGP) approximation. NNGP enables flexibility in changing the proximity on the phylogenetic tree of species from which information is borrowed to stabilise parameter estimates with a realistic computational burden. We evaluated the effectiveness of phylogenetic models by comparing the predictive performance and descriptive power of phylogenetic and non-phylogenetic models and identified the anthropogenic factors contributing to the decline of each of the studied endangered species. 3. We found that the model with phylogenetic information had better prediction performance than the model without phylogenetic information. The results showed that across all explanatory variables, the phylogenetic model could detect interspecific differences in response to environmental factors in a number of species more clearly. Combined with the phylogenetic signal results, we could also detect a phylogenetic bias in the species that could benefit from the positive effects of protected areas but reduce the extinction risk of 95% of all studied taxa. 4. In conclusion, our model, considering phylogenetic information with NNGP, allows the elucidation of factors causing the decline of many endangered species. In future analyses, the estimation of extinction probability linked to environmental change using such modelling might be applied to future climate-land use scenarios, advancing the comprehensive assessment of biodiversity degradation and threats to species at multiple scales.

ecology↗

bioRxiv2022

Higher-order dissimilarity in biodiversity: Identifying dissimilarities of spatial or temporal dissimilarity structures

O_LIElucidating biodiversity patterns and their background processes is critical in biodiversity science. Dissimilarity, which is calculated based on multivariate biological quantities, is a major component of biodiversity. As spatial and temporal biodiversity information availability increases, the scope of dissimilarity studies has been expanded to cover various levels and types of spatio-temporal biodiversity facets (e.g., gene, community, and ecosystem function), and diverse pairwise dissimilarity indices have been developed. However, further development of the dissimilarity concept is required in comparative studies on spatio-temporal structures of biodiversity compositional patterns, such as those exploring commonalities of biogeographical boundaries among taxa, compared to the conventional ones to consider higher dimensions of dissimilarity: dissimilarity of dissimilarity structures. C_LIO_LIThis study proposes a novel and general concept, high-order dissimilarity (HOD), for quantitatively evaluating the dissimilarities of spatial or temporal dissimilarity structures among different datasets, proposes specific implementations of HOD as operational indices, and illustrates the potential resolution of scientific and practical questions through HOD. C_LIO_LIWe further demonstrate the advantages of the HOD concept by applying it to actual patterns, such as long-term and/or large-spatial hypothetical monitoring datasets. C_LIO_LIOur conceptual framework on HOD extends the existing framework of biodiversity science and is versatile, with many potential applications in acquiring more valuable information from ever-increasing biodiversity data. C_LI

ecology↗

bioRxiv2021

SecSel, a new software tool for conservation prioritization that is applicable to ordinal-scale data for multiple biodiversity features

SecSel, a protected-area prioritization tool, has been developed to help design areas that efficiently protect multiple features, including conservation of biodiversity and use of ecosystem services. The prioritization by SecSel is based on evaluation of the local units of each feature. The evaluation metrics should be quantitative but need not be ratio scale. The minimum requirement of the input data is that they are ordinal. The conservation target is the number of local units with high values of each feature to be protected in the area. SecSel can handle conflicts among features, including conflicts between conservation and utilization of land or specific ecosystem functions. Before the selection procedure, one of a conflicting pair of features in a site is discarded. That decision is based on the dispensability of the local unit to fulfilling the conservation target of each feature. SecSel also considers the cost of including each site in the protected area and the compactness of the area in terms of total boundary length or the distance to the nearest site. To demonstrate the functionality of Secsel, we used it to design land use in an alpine region of northern Japan where conservation of alpine vegetation and its recreational use are important considerations.

ecology↗