Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Growth of non-English-language literature on biodiversity conservation

English is widely recognized as the language of science, and English-language publications (ELPs) are rapidly increasing. It is often assumed that the number of non-ELPs is decreasing. This assumption contributes to the underuse of non-ELPs in conservation science, practice, and policy, especially at the international level. However, the number of conservation articles published in different languages is poorly documented. Using local and international search systems, we searched for scientific articles on biodiversity conservation published from 1980 to 2018 in English and 15 non-English languages. We compared the growth rate in publications across languages. In 12 of the 15 non-English languages, published conservation articles significantly increased every year over the past 39 years, at a rate similar to English-language articles. The other three languages showed contrasting results, depending on the search system. Since the 1990s, conservation science articles in most languages increased exponentially. The variation in the number of non-English-language articles identified among the search systems differed markedly (e.g., for simplified Chinese, 11,148 articles returned with local search system and 803 with Scopus). Google Scholar and local literature search systems returned the most articles for 11 and 4 non-English languages, respectively. However, the proportion of peer-reviewed conservation articles published in non-English languages was highest in Scopus, followed by Web of Science and local search systems, and lowest in Google Scholar. About 20% of the sampled non-English-language articles provided no title or abstract in English; thus, in theory, they were undiscoverable with English keywords. Possible reasons for this include language barriers and the need to disseminate research in countries where English is not widely spoken. Given the known biases in statistical methods and study characteristics between English- and non-English-language studies, non-English-language articles will continue to play an important role in improving the understanding of biodiversity and its conservation.     

Meta-analysis of the differential effects of habitat fragmentation and degradation on plant genetic diversity

Genetic diversity is a key factor for population survival and evolution. However, anthropogenic habitat disturbance can erode it, making populations more prone to extinction. Aiming to assess the global effects of habitat disturbance on plant genetic variation, we conducted a meta-analysis based on 92 case studies obtained from published literature. We compared the effects of habitat fragmentation and degradation on plant allelic richness and gene diversity (equivalent to expected heterozygosity) and tested whether such changes are sensitive to different life-forms, life spans, mating systems, and commonness. Anthropogenic disturbance had a negative effect on allelic richness, but not on gene diversity. Habitat fragmentation had a negative effect on genetic variation, whereas habitat degradation had no effect. When we examined the individual effects in fragmented habitats, allelic richness and gene diversity decreased, but this decrease was strongly dependent on certain plant traits. Specifically, common long-lived trees and self-incompatible species were more susceptible to allelic richness loss. Conversely, gene diversity decreased in common short-lived species (herbs) with self-compatible reproduction. In a wider geographical context, tropical plant communities were more sensitive to allelic richness loss, whereas temperate plant communities were more sensitive to gene diversity loss. Our synthesis showed complex responses to habitat disturbance among plant species. In many cases, the absence of effects could be the result of the time elapsed since the disturbance event or reproductive systems favoring self-pollination, but attention must be paid to those plant species that are more susceptible to losing genetic diversity, and appropriate conservation should be actions taken.     

Effects of crowding due to habitat loss on species assemblage patterns

Terrestrial animals are negatively affected by habitat loss, which is assessed on a landscape scale, whereas secondary effects of habitat loss, such as crowding, are usually disregarded. Such impacts are inherently hard to address and poorly understood, and there is a growing concern that they could have dire consequences. We sampled birds throughout a deforestation process to assess crowding stress in an adjacent habitat remnant in the southern Brazilian Atlantic Forest. Crowding is expected of highly mobile taxa, especially given the microhabitat heterogeneity of Neotropical forests, and we hypothesized that the arrival of new individuals or species in refuges shifts assemblage patterns. We used point counts to obtain bird abundances in a before-after-control-impact design sampling of a deforestation event. Temporal changes in taxonomic and functional diversity were examined with metrics used to assess alpha and beta diversity, turnover of taxonomic and functional similarity, and taxonomic and functional composition. Over time increased abundance of some species altered the Simpson index and affected the abundance-distribution of traits in the habitat remnant. Taxonomic composition and functional composition changed in the remnant, and thus bird assemblages changed over time. Taxonomic and functional metrics indicated that fugitives affected resident assemblages in refuges, and effects endured >2 years after the deforestation processes had ceased. Dissimilarity of taxonomic composition between pre- and postdeforestation assemblages increased, whereas functional composition reverted to preimpact conditions. We found that ecological disruptions resulted from crowding and escalated into disruptions of species’ assemblages and potentially compromising ecosystem functioning. It is important to consider crowding effects of highly mobile taxa during impact assessments, especially in large-scale infrastructure projects that may affect larger areas than is assumed.