Text‐analysis reveals taxonomic and geographic disparities in animal pollination literature

Abstract

Ecological systematic reviews and meta‐analyses have significantly increased our understanding of global biodiversity decline. However, for some ecological groups, incomplete and biased datasets have hindered our ability to construct robust, predictive models. One such group consists of the animal pollinators. Approximately 88% of wild plant species are thought to be pollinated by animals, with an estimated annual value of $230–410 billion dollars. Here we apply text‐analysis to quantify the taxonomic and geographical distribution of the animal pollinator literature, both temporally and spatially. We show that the publication of pollinator literature increased rapidly in the 1980s and 1990s. Taxonomically, we show that the distribution of pollinator literature is concentrated in the honey bees (Apis) and bumble bees (Bombus), and geographically in North America and Europe. At least 25% of pollination‐related abstracts mention a species of honey bee and at least 20% a species of bumble bee, and approximately 46% of abstracts are focussed on either North America (32%) or Europe (14%). Although these results indicate strong taxonomic and geographic biases in the pollinator literature, a large number of studies outside North America and Europe do exist. We then discuss how text‐analysis could be used to shorten the literature search for ecological systematic reviews and meta‐analyses, and to address more applied questions related to pollinator biodiversity, such as the identification of likely interacting plant–pollinator pairs and the number of pollinating species.

Global Variation in Climate, Human Development, and Population Density Has Implications for Urban Ecosystem Services

“…This geographical bias means that little information is available about urban ecosystem services for many parts of the world (Figure 2) and for some types of cities ( Figure 3). The geographic bias in research related to ecosystem services is similar to that in other research areas such as urban development [68], conservation [69], and ecology generally [70,71].…”

“…Mediterranean climates were over-represented in the urban ecosystem services literature, while savanna, tropical rainforest, tropical monsoonal, hot desert, and cold desert climates were under-represented (Figure 3). The climatic bias observed here reflects a well-known bias in ecology away from the tropics [71] and restricts the ability of urban planners in cities with savanna climate, desert, and humid tropical climates to apply ecosystem service concepts in design [25]. The under-representation of lower HDI urban areas is particularly problematic for human well-being, as residents in these areas are typically more dependent on urban ecosystem services [72].…”

The species awareness index as a conservation culturomics metric for public biodiversity awareness

“…To explore how species awareness varied with pollination contribution, we built a list of animal pollinators by combining text analysis and manual inspection of the pollination literature (see Millard et al. [2020] and Appendix S1 for detailed methods). We also used the list of traded vertebrate species released in Scheffers et al.…”

“…the pollination literature (see Millard et al [2020] and Appendix S1 for detailed methods). We also used the list of traded vertebrate species released in Scheffers et al (2019) and the Food and Agriculture Organization (FAO) fisheries statistics (FAO 2020) to compile a data set of traded mammals, birds, squamate reptiles, and ray-finned fish.…”

The Species Awareness Index (SAI): a Wikipedia-derived conservation culturomics metric for public biodiversity awareness

“…Specifically, we explore biodiversity pooled, 6 distinct taxonomic classes (reptiles, ray-finned fishes, mammals, birds, insects, and amphibians), and each taxonomic class in each of 10 languages (Arabic, Chinese, English, French, German, Italian, Japanese, Portuguese, Russian, Spanish). We then predict rate of change in the page level SAI as a function of taxonomic class, Wikipedia language, trade status, and pollination contribution, using a pollinator dataset derived from the academic literature through named-entity recognition (Millard, et al, 2020). We conclude by discussing the limitations of the SAI, suggesting potential avenues for future research, and demonstrating how the SAI might be combined with other approaches for a more holistic understanding of changing biodiversity awareness.…”