A comprehensive database of squirrel distribution and occurrence in South Asia

The Squirrels of South Asia (SOSA) database compiles comprehensive distribution and occurrence information on all squirrel species that occur in this region (34 species). These 34 squirrel species, including tree, flying and ground squirrels, represent 14% of global sciurid diversity. The database collates curated data from various sources such as museums, literature, primary fieldwork, citizen science and social media platforms and covers the entire distributional ranges of the target species, including countries in Central Asia and Southeast Asia when required. The SOSA database enhances our understanding of squirrel distribution, population dynamics and their conservation needs in South Asia by consolidating information. It aims to be a valuable resource for researchers, conservationists and wildlife enthusiasts.As of March 2023, the database comprises over 40,000 records of 34 species in over 30 countries globally. Spending an average of 334 hours on each species, more than 20 data collectors put in over 10,000 hours to gather, curate and build this database. The database has resulted in novel records of species occurrence in regions and countries that are poorly represented in currently available global data repositories. The current version which has been made public via GBIF comprises of 1187 records of all 34 species across multiple sources. This is a subset of the SOSA database

Nivetha_poster.pdf

<p>Sexual size dimorphism is common across many species. Males being larger than females is the commonly observed pattern among mammals, and is explained as sexual selection favouring larger males. Some gliding mammals are known to exhibit the opposite pattern, with females larger than males. Functional advantages to large size (efficient gliding while pregnant and carrying young) have been shown to determine this pattern in flying squirrels. In this study, we examine whether female-biased dimorphism is consistent across gliding mammals belonging to different families (nine species in four families).</p

Evolution of Estrildid Mouth markings in light of brood parasitism

<ul> <li>Are there a few important characters that describe the evolution of color and mouth patterns? </li> <li>Does the evolution of mouth patterns trace the evolution of mouth colors?</li><li> Does habitat and related food availabilty affect begging behavior and associated evolution of mouth patterns? Do finches in low resource conditions have more complex mouth markings?</li> </ul

Building a Database using Unconventional Sources Squirrels of India.pdf

Building a Database using Unconventional Sources Squirrels of India</h4

Building a Database using Unconventional Sources: Squirrels of India

Squirrels, like most other small mammals, have been poorly documented in the Indian subcontinent, which deters us from understanding species declines and prioritizing research on sensitive taxa (McKinney 1999, Koprowski and Nandini 2008). They are diverse in their habits and morphology and perform important ecological roles, including seed dispersal, pollination, and regulating plant growth. They also form a significant prey base for many predators. Squirrels respond strongly to pressures around them, including urbanization, habitat modification, and climate change, and can thus act as model study systems (Sol et al. 2013). The first step in understanding how species respond to such changes is by gaining knowledge of where they occur.The rapid spread of internet connectivity and access to mobile technology across India allow us to access large-scale secondary data in ways that were not possible around a decade ago. We created a pan-India database for 30 species of squirrels using primary data (from fieldwork) and secondary sources (museum records, published and gray literature), citizen science portals (six sources), and social media platforms (14 sources). The use of social media platforms is increasing exponentially across India, yet these remain a largely unexplored source for harvesting biodiversity information. Given low public awareness of squirrel species, we expected high error rates with contributors' assignment of species identity. A key of species images and calls was used while data gathering to maintain consistency across the team. A pipeline for the data collection and curation was created, and all volunteers on the project were trained to maintain consistency in data collection. To ensure verification of species identity, media (photographs, audio, and video data) are collected when possible or are cross-checked on the source site. Some (iNaturalist, Project Noah) citizen science platforms allow script-based or search-based downloads of bulk records without media. Each media record on such citizen science sites is manually checked to confirm species identification. On social media platforms (Fig. 1), species-wise searches were performed (using common and scientific names) within each platform. For all social media records, media (photograph, audio, video) data was downloaded along with location, date, observer, and relevant notes. Each entry was manually entered into a database by researchers (12 over two years, including volunteer interns). Each record was then manually verified for species by one or two of four curators (more curators for less-familiar species). Duplicates were manually removed by a curator, who compares species-specific data across multiple sources. The location for each entry was also curated, and a georeference was added when unavailable in the original post. All location data were imported into Google Sheets, and the map tool Geocode by Awesome Table were used to obtain latitude and longitude data for places. On many occasions, curators contacted observers on social media to confirm details before an entry was finalized. Over two years, the database grew to include 24,170 records with approximately 14,000 media files, with the team working for over 2200+ hours. About 48% (12,035) of the occurrence records came from social media sources, followed by 30% of records (7375) from traditional sources and 22% (4660) from citizen science portals (Fig. 1).We examined the temporal trends and bias for squirrel occurrence data for all three sources and assess the over and under-representation of squirrel occurrence based on body size, activity period, body-color, International Union for Conservation of Nature (IUCN) Red List status, range size, and habitat type.The majority of the occurrence records were that of tree squirrels (Fig. 2), followed by flying and ground squirrels. This is likely because tree squirrels are diurnal and more abundant, and hence are easier to record when compared to flying squirrels which are cryptic and nocturnal. The two species of ground squirrels in India are restricted to higher elevations in the Himalayas, making them difficult to record.There are, however, differences in records across regions in India. Based on a quick examination of the occurrence records, most of them are from urban areas, reflecting either bias in data collection (concentrated human densities) or species response to urbanization. Some species like Funambulus palmarum and Funambulus pennantii are known to be abundant in areas with higher human densities, which might be reflected in the number of occurrence records. In contrast, most other species seem restricted to areas with less anthropogenic disturbance. Therefore, recording fine-scale occurrences for this diverse group is crucial to understand species' responses to rapid landscape modifications such as urbanization.Our understanding of biodiversity in a changing world has been greatly improved by combining, harmonizing, and analyzing large amounts of heterogeneous ecological data (Hampton et al. 2013). The availability of more accurate data enables studies to address questions at increasingly large spatial and temporal scales with stronger inference and more accurate and predictive models, which, in turn, yield important biological insights (Lewis et al. 2018)

A comprehensive database of squirrel distribution and occurrence in South Asia

The Squirrels of South Asia (SOSA) database compiles comprehensive distribution and occurrence information on all squirrel species that occur in this region (34 species). These 34 squirrel species, including tree, flying and ground squirrels, represent 14% of global sciurid diversity. The database collates curated data from various sources such as museums, literature, primary fieldwork, citizen science and social media platforms and covers the entire distributional ranges of the target species, including countries in Central Asia and Southeast Asia when required. The SOSA database enhances our understanding of squirrel distribution, population dynamics and their conservation needs in South Asia by consolidating information. It aims to be a valuable resource for researchers, conservationists and wildlife enthusiasts.As of March 2023, the database comprises over 40,000 records of 34 species in over 30 countries globally. Spending an average of 334 hours on each species, more than 20 data collectors put in over 10,000 hours to gather, curate and build this database. The database has resulted in novel records of species occurrence in regions and countries that are poorly represented in currently available global data repositories. The current version which has been made public via GBIF comprises of 1187 records of all 34 species across multiple sources. This is a subset of the SOSA database

A comprehensive database of squirrel distribution and occurrence in South Asia

The Squirrels of South Asia (SOSA) database compiles comprehensive distribution and occurrence information on all squirrel species that occur in this region (34 species). These 34 squirrel species, including tree, flying and ground squirrels, represent 14% of global sciurid diversity. The database collates curated data from various sources such as museums, literature, primary fieldwork, citizen science, and social media platforms and covers the entire distributional ranges of the target species, including countries in Central Asia and Southeast Asia when required. The SOSA database enhances our understanding of squirrel distribution, population dynamics, and their conservation needs in South Asia by consolidating information. It aims to be a valuable resource for researchers, conservationists, and wildlife enthusiasts.As of March 2023, the database comprises over 40,000 records of 34 species in over 30 countries globally. Spending an average of 334 hours on each species, more than 20 data collectors put in over 10,000 hours to gather, curate, and build this database. The database has resulted in novel records of species occurrence in regions and countries that are poorly represented in currently available global data repositories. The current vesrion which has been made public via GBIF comprises of 1187 records of all 34 species across multiple sources. This is a subset of the SOSA database

Genetic drift among isolated populations of tree Euphorbias in the Western Ghats

Poster presentation at the International Biogeography Society 2017 meeting, Bangalore, India

Integrating microclimatic variation in phenological responses to climate change: a 28-year study in a hibernating mammal. Running head: Phenology and microclimate

International audienc

Integrating microclimatic variation in phenological responses to climate change: A 28-year study in a hibernating mammal

Phenological shifts associated with directional changes in climate, resulting in earlier spring activities, have been documented in several animal species. However, the extent to which species respond to overall climate change versus local climate variation is rarely studied. In addition, climate data are usually averaged over large spatial scales, even though local heterogeneity in habitats may be high, and species might be more susceptible to changes in local rather than global climate conditions. In this study, we examined the effects of spatiotemporal climate variation and climate change on the phenology of a hibernating mountain rodent, the Columbian ground squirrel (Urocitellus columbianus). Over 28 years of research (1992–2019), we studied the relationship between the microclimatic conditions experienced by adult and juvenile ground squirrels from four neighboring meadows, and their dates of emergence from hibernation. We used a microclimate model to calculate microclimate variables (local snow depth, soil temperature, air temperature, wind speed, and humidity) at an hourly scale, a 5-m spatial resolution, and at animal height on the study sites over 28 years. Emergence dates varied with age and sex, among years, as well as among and within meadows, with some areas averaging up to 10 days earlier emergence dates from hibernation than others. While emergence dates tended to be delayed throughout the study period, long-term temporal changes and interannual variability in emergence dates differed among meadows and depended on individual age and sex. Dates of hibernation emergence were correlated with local climate variables considered either during hibernation or during the preceding summer. Ground squirrels emerged earlier in years or at locations when/where snow melted earlier (years: all individuals excluding 2-year-old males, locations: yearlings and older females), and when the previous summer was less windy (≥3-year-old individuals) and more humid (2-year-old males). Two-year-old male ground squirrels also emerged later in locations where snow depth during winter was higher. Using a microclimate model allowed realistic predictions of phenological responses to climate, highlighting its potential for research on animal responses to abiotic change