A New Species of Grigiotermes (Apicotermitinae, Termitidae) from the Northern Atlantic Forest, Delimited by Morphological and Molecular Data

In this paper, we described a new species of Grigiotermes, G. piassava sp. n., from the Brazilian Atlantic Forest. The imago and worker caste are described, including the gut morphology. The inclusion of the new species in Grigiotermes was based on morphological and DNA data. Apparently, the distribution of the species is limited to the northern region of the Atlantic Forest, located above the São Francisco River, which is considered one of the most threatened sectors of the biome

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

The global EPTO database:worldwide occurrences of aquatic insects

Abstract Motivation: Aquatic insects comprise 64% of freshwater animal diversity and are widely used as bioindicators to assess water quality impairment and freshwater ecosystem health, as well as to test ecological hypotheses. Despite their importance, a comprehensive, global database of aquatic insect occurrences for mapping freshwater biodiversity in macroecological studies and applied freshwater research is missing. We aim to fill this gap and present the Global EPTO Database, which includes worldwide geo-referenced aquatic insect occurrence records for four major taxa groups: Ephemeroptera, Plecoptera, Trichoptera and Odonata (EPTO). Main type of variables contained: A total of 8,368,467 occurrence records globally, of which 8,319,689 (99%) are publicly available. The records are attributed to the corresponding drainage basin and sub-catchment based on the Hydrography90m dataset and are accompanied by the elevation value, the freshwater ecoregion and the protection status of their location. Spatial location and grain: The database covers the global extent, with 86% of the observation records having coordinates with at least four decimal digits (11.1 m precision at the equator) in the World Geodetic System 1984 (WGS84) coordinate reference system. Time period and grain: Sampling years span from 1951 to 2021. Ninety-nine percent of the records have information on the year of the observation, 95% on the year and month, while 94% have a complete date. In the case of seven sub-datasets, exact dates can be retrieved upon communication with the data contributors. Major taxa and level of measurement: Ephemeroptera, Plecoptera, Trichoptera and Odonata, standardized at the genus taxonomic level. We provide species names for 7,727,980 (93%) records without further taxonomic verification. Software format: The entire tab-separated value (.csv) database can be downloaded and visualized at https://glowabio.org/project/epto_database/. Fifty individual datasets are also available at https://fred.igb-berlin.de, while six datasets have restricted access. For the latter, we share metadata and the contact details of the authors

The global EPTO database : Worldwide occurrences of aquatic insects

Motivation: Aquatic insects comprise 64% of freshwater animal diversity and are widely used as bioindicators to assess water quality impairment and freshwater ecosystem health, as well as to test ecological hypotheses. Despite their importance, a comprehensive, global database of aquatic insect occurrences for mapping freshwater biodiversity in macroecological studies and applied freshwater research is missing. We aim to fill this gap and present the Global EPTO Database, which includes worldwide geo-referenced aquatic insect occurrence records for four major taxa groups: Ephemeroptera, Plecoptera, Trichoptera and Odonata (EPTO).Main type of variables contained: A total of 8,368,467 occurrence records globally, of which 8,319,689 (99%) are publicly available. The records are attributed to the corresponding drainage basin and sub-catchment based on the Hydrography90m dataset and are accompanied by the elevation value, the freshwater ecoregion and the protection status of their location.Spatial location and grain: The database covers the global extent, with 86% of the observation records having coordinates with at least four decimal digits (11.1 m precision at the equator) in the World Geodetic System 1984 (WGS84) coordinate reference system.Time period and grain: Sampling years span from 1951 to 2021. Ninety-nine percent of the records have information on the year of the observation, 95% on the year and month, while 94% have a complete date. In the case of seven sub-datasets, exact dates can be retrieved upon communication with the data contributors.Major taxa and level of measurement: Ephemeroptera, Plecoptera, Trichoptera and Odonata, standardized at the genus taxonomic level. We provide species names for 7,727,980 (93%) records without further taxonomic verification.Software format: The entire tab-separated value (.csv) database can be downloaded and visualized at . Fifty individual datasets are also available at , while six datasets have restricted access. For the latter, we share metadata and the contact details of the authors.Peer reviewe