{"id":33065,"date":"2021-04-29T14:45:30","date_gmt":"2021-04-29T12:45:30","guid":{"rendered":"https:\/\/tourduvalat.org\/?p=33065"},"modified":"2022-10-07T16:10:36","modified_gmt":"2022-10-07T14:10:36","slug":"new-article-imputation-of-incomplete-large%e2%80%90scale-monitoring-count-data-via-penalized-estimation","status":"publish","type":"post","link":"https:\/\/tourduvalat.org\/en\/publications-en\/new-article-imputation-of-incomplete-large%e2%80%90scale-monitoring-count-data-via-penalized-estimation\/","title":{"rendered":"New article – Imputation of incomplete large\u2010scale monitoring count data via penalized estimation"},"content":{"rendered":"

This article has been published in the\u00a0Methods in Ecology and Evolution <\/strong>journal. Using a method based on penalized Poisson models, the article highlighted the long\u2010term trends of 16 waterbird species for the first time at the entire North African scale.<\/h4>\n

You can access to it on the Tour du Valat web documentary portal<\/a>.<\/p>\n

 <\/p>\n

\"\"Abstract : <\/strong><\/p>\n

    \n
  1. In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and conservation status. These large\u2010scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large\u2010scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies.<\/li>\n
  2. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large\u2010scale framework. The method allows parameterization of (a) space and time factors, (b) the main effects of predictor covariates, as well as (c) space\u2013time interactions. It also benefits from robust statistical and computational capability in large\u2010scale settings.<\/li>\n
  3. The method was tested extensively on both simulated and real\u2010life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long\u2010term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series.<\/li>\n
  4. This new approach opens promising perspectives to increase the accuracy of species\u2010abundance trend estimations. We made it freely available in the r package \u2018lori\u2019 (https:\/\/CRAN.R\u2010project.org\/package=lori<\/a>) and recommend its use for large\u2010scale count data, particularly in citizen science monitoring programmes.<\/li>\n<\/ol>\n

    Bibliographical reference:\u00a0<\/strong>Dakki M, Robin G, Suet M, et al. Imputation of incomplete large-scale monitoring count data via penalized estimation. Methods Ecol Evol. 2021;00:1\u20139. https:\/\/doi.org\/10.1111\/2041-210X.13594<\/a>
    \n<\/strong><\/p>\n

     <\/p>\n","protected":false},"excerpt":{"rendered":"

    This article has been published in the\u00a0Methods in Ecology and Evolution journal. Using a method based on penalized Poisson models, the article highlighted the long\u2010term trends of 16 waterbird species for the first time at the entire North African scale. You can access to it on the Tour du Valat web documentary portal.   Abstract […]<\/p>\n","protected":false},"author":332,"featured_media":33095,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[101],"tags":[28,779,778,777,776],"class_list":["post-33065","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications-en","tag-biodiversity","tag-ecosystems","tag-mediterranean","tag-waterbirds","tag-wetlands","country-mediterranean"],"acf":[],"_links":{"self":[{"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/posts\/33065","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/users\/332"}],"replies":[{"embeddable":true,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/comments?post=33065"}],"version-history":[{"count":15,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/posts\/33065\/revisions"}],"predecessor-version":[{"id":37462,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/posts\/33065\/revisions\/37462"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/media\/33095"}],"wp:attachment":[{"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/media?parent=33065"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/categories?post=33065"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tourduvalat.org\/en\/wp-json\/wp\/v2\/tags?post=33065"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}