{"id":99282,"date":"2026-05-28T04:00:11","date_gmt":"2026-05-28T08:00:11","guid":{"rendered":"https:\/\/news.utoledo.edu\/?p=99282"},"modified":"2026-06-02T11:19:44","modified_gmt":"2026-06-02T15:19:44","slug":"utoledo-scientists-develop-new-method-to-estimate-hidden-species","status":"publish","type":"post","link":"https:\/\/news.utoledo.edu\/index.php\/05_28_2026\/utoledo-scientists-develop-new-method-to-estimate-hidden-species","title":{"rendered":"UToledo Scientists Develop New Method to Estimate Hidden Species"},"content":{"rendered":"

When researchers survey wildlife in a lake, forest or other habitat, they rarely capture every species present \u2014 some are simply too rare or elusive to detect. <\/span><\/p>\n

A new study published in the May issue of Ecological Informatics addresses this longstanding challenge by offering a more powerful statistical method to estimate not just the species scientists can<\/em> see, but also the ones they’re likely missing.<\/span><\/p>\n

\"Nature

A research team from UToledo, the U.S. Geological Survey Great Lakes Science Center and Wittenberg University<\/span> built on a mathematical framework developed in the 1940s to model how species and their populations are distributed in nature, which will help track how ecosystems respond to environmental pressures such as pollution, climate change or habitat loss.<\/span><\/p><\/div>\n

The study proposing the new data model,<\/span><\/strong> titled \u201c<\/span>A Bayesian hierarchical modeling approach for species diversity in ecology<\/span><\/a>,\u201d noted that \u201cestimating the \u2018true\u2019 species richness, which includes identifying the number of missing species, has intrigued ecologists for decades.\u201d<\/span><\/strong><\/span><\/p>\n

The research team from The University of Toledo, the U.S. Geological Survey Great Lakes Science Center and Wittenberg University<\/span> built on a mathematical framework originally developed in the 1940s to model how species and their populations are distributed in nature. <\/span><\/p>\n

By combining this framework with modern computational techniques, the researchers created a tool that can estimate the “true” number of species in an ecosystem \u2014 including those that went uncounted \u2014 while also revealing how evenly or unevenly individuals are spread across different species.<\/span><\/p>\n

The method was tested against simulated data and three real-world historical datasets and proved both accurate and computationally efficient. Researchers also demonstrated how the approach can pool data from multiple related studies \u2014 such as the annual Great Lakes fishery survey \u2014 to reveal broader trends across time and geography.<\/span><\/p>\n

\u201cBeyond counting species, this tool gives scientists a richer picture of ecosystem health by measuring two key qualities at once: how abundant species are overall, and how evenly they share that abundance,\u201d said the study\u2019s lead author, Dr. Song S.<\/span>\u00a0<\/span>Qian, from UToledo\u2019s <\/span>Department of Environmental Sciences<\/span>.<\/span><\/span><\/p>\n

The tool will be useful for tracking how ecosystems respond to environmental pressures such as pollution, climate change or habitat loss.<\/span><\/p>\n

The research team was comprised of <\/span><\/strong>Song<\/span><\/span>, Dr. <\/span><\/span>Mark R.<\/span><\/span>\u00a0<\/span><\/span>DuFour, a UToledo graduate who now works at <\/span><\/span>the U.S. Geological Survey\u2019s Great Lakes Science Center-Lake Erie Biological Station in Huron,<\/span>\u00a0Dr. <\/span>Sabrina<\/span><\/span>\u00a0<\/span><\/span>Jaffe of <\/span><\/span>Wittenberg University<\/span>,<\/span><\/span>\u00a0Dr. <\/span>Corbin<\/span><\/span>\u00a0<\/span><\/span>Hilling,<\/span><\/span> another UToledo graduate who works at the U.S. Geological Survey\u2019s Great Lakes Science Center-Lake Erie Biological Station in Huron<\/span> and Dr. William D.<\/span><\/span>\u00a0<\/span><\/span>Hintz<\/span><\/span> from The University of Toledo Department of Environmental Sciences & Lake Erie Center.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"\"Nature<\/a>

The new model for collecting species data within ecosystems is published in the May issue of Ecological Informatics.<\/p>\n","protected":false},"author":930,"featured_media":99283,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[50,39,1,3,7],"tags":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/posts\/99282"}],"collection":[{"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/users\/930"}],"replies":[{"embeddable":true,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/comments?post=99282"}],"version-history":[{"count":3,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/posts\/99282\/revisions"}],"predecessor-version":[{"id":99286,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/posts\/99282\/revisions\/99286"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/media\/99283"}],"wp:attachment":[{"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/media?parent=99282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/categories?post=99282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/news.utoledo.edu\/index.php\/wp-json\/wp\/v2\/tags?post=99282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}