<b>Use of secondary diversity data to improve diversity estimates at multiple geographic scales</b>

Studying the patterns and properties of biological diversity at multiple geographic scales is essential to answering biogeographical and macroecological questions. Here, we tested the hypothesis that diversity estimates from stacked ecological niche models (staked ENMs) are positively related to the diversity observed from checklists areas (i.e., “well-sampled” localities), while this relationship will be more ambiguous when diversity estimates are made from curate species occurrence (presence-only dataset). We used these tree diversity sources to evaluated alpha and beta diversity, per-site range size total nestedness and completeness at five geographic scales (1/2°, 1/4°, 1/8°, 1/16° and 1/32°). Estimates from presence-only dataset and stacked ENMs were poor correlated with alpha diversity from checklists areas (except to stacked ENMs at 1/32°), and beta diversity from checklists areas was strongly correlated with presence-only dataset and stacked ENMs at finer scales. The nestedness pattern from stacked ENMs remained relatively constant over all geographic scales; conversely, presence-only datasets nestedness was influenced by finer scales, affecting community traits such as incidence and composition of species. Our study demonstrates that stacked ENMs was reliable to inferring effective diversities over all scales, and presence-only datasets are not adequate to estimate effective diversities, and may fail to infer diversity patterns. We recommend complementary analysis of completeness properties of the sample coverage to get reliability over diversity assessments.