Charles Lawrence Bellamy

In this work, the 25 species of the flea beetle genus Calotheca Heyden recorded for South Africa are considered. Starting from the updated species distribution and the topographic, temperature, and precipitation variables, as well as the vegetation types in the occurrence sites, through an analysis of ecological niche modelling, a possible ecological profile is provided, both for each species and the entire genus, highlighting some of the factors that drive their occurrence and distribution patterns. Along with the vegetation type, some climatic variables were found to be particularly influential, such as the mean temperature of both the wettest and driest quarters and also the mean precipitation of the wettest period. Finally, comparing the distribution of the areas of highest suitability returned by the model obtained for Calotheca, they largely overlap with the highest-density areas of Searsia, genus of Anacardiaceae, including the main host plants for these flea beetles.

The Mojave and Sonoran Deserts, recognized as a global hotspot for bee biodiversity, are experiencing habitat degradation from urbanization, utility‐scale solar energy (USSE) development, and climate change. In this study, we evaluated the current and future distribution of bee diversity, assessed how protected areas safeguard bee species richness, and predicted how global change may affect bees across the region. Using Joint Species Distribution Models (JSDMs) of 148 bee species, we project changes in species distributions, occurrence area, and richness under four global change scenarios between 1971 and 2050. We evaluated the threat posed by USSE development and predicted how climate change will affect the suitability of protected areas for conservation. Our findings indicate that changes in temperature and precipitation do not uniformly affect bee richness. Lower elevation protected areas are projected to experience mean losses of up to 5.8 species, whereas protected areas at higher elevations and transition zones may gain up to 7.8 species. Areas prioritized for future USSE development have an average species richness of 4.2 species higher than the study area average, and lower priority “variance” areas have 8.2 more species. USSE zones are expected to experience declines of up to 8.0 species by 2050 due to climate change alone. Despite the importance of solitary bees for pollination, their diversity is often overlooked in land management decisions. Our results show the utility of JSDMs for leveraging existing collection records to ease the inclusion of data‐limited insect species in land management decision‐making.

Island ecosystems have significant conservation value owing to their higher endemic biotas. Moreover, studies of regional communities that compare differences in species composition (species dissimilarity) among islands and the mainland suggest that community assembly on islands is different from that on the mainland. However, the uniqueness of island biotic assembly has been little studied at the global scale, nor have phylogenetic information or alien species been considered in these patterns. We evaluate taxonomic and phylogenetic change from one community to the next, focusing on differences in species composition between mainland-mainland (M-M) pairs compared to differences between mainland-island pairs (M-I) and between island-island pairs (I-I), using herpetofauna on islands and adjacent mainland areas worldwide. Our analyses detect greater taxonomic and phylogenetic dissimilarity for M-I and I-I comparisons than predicted by M-M model, indicating different island herpetofauna assembly patterns compared with mainland counterparts across the world. However, this higher M-I dissimilarity has been significantly decreased after considering alien species. Our results provide global evidence on the importance of island biodiversity conservation from the aspect of both the taxonomic and phylogenetic uniqueness of island biotic assembly.

BACKGROUND Kissing bugs are the vectors of Trypanosoma cruzi, the etiological agent of Chagas disease (CD). Despite their epidemiological relevance, kissing bug species are under sampled in terms of their diversity and it is unclear what biases exist in available kissing bug data. Under climate change, range maps for kissing bugs may become less accurate as species shift their ranges to track climatic tolerance. OBJECTIVES Quantify inventory completeness in available kissing bug data. Assess how well range maps are at conveying information about current distributions and potential future distributions subject to shift under climate change. Intersect forecasted changes in kissing bug distributions with contemporary sampling gaps to identify regions for future sampling of the group. Identify whether a phylogenetic signal is present in expert range knowledge as more closely related species may be similarly well or lesser understood. METHODS We used species distribution models (SDM), specifically constructed from Bayesian additive regression trees, with Bioclim variables, to forecast kissing bug distributions into 2100 and intersect these with current sampling gaps to identify priority regions for sampling. Expert range maps were assessed by the agreement between the expert map and SDM generated occurrence probability. We used classical hypothesis testing methods as well as tests of phylogenetic signal to meet our objectives. FINDINGS Expert range maps vary in their quality of depicting current kissing bug distributions. Most expert range maps decline in their ability to convey information about kissing bug occurrence over time, especially in under sampled areas. We found limited evidence for a phylogenetic signal in expert range map performance. MAIN CONCLUSIONS Expert range maps are not a perfect account of species distributions and may degrade in their ability to accurately convey distribution knowledge under future climates. We identify regions where future sampling of kissing bugs will be crucial for completing biodiversity inventories.

Biological invasions are among the threats to global biodiversity and social sustainability, especially on islands. Identifying the threshold of area at which non-native species begin to increase abruptly is crucial for early prevention strategies. The small-island effect (SIE) was proposed to quantify the nonlinear relationship between native species richness and area but has not yet been applied to non-native species and thus to predict the key breakpoints at which established non-native species start to increase rapidly. Based on an extensive global dataset, including 769 species of non-native birds, mammals, amphibians and reptiles established on 4277 islands across 54 archipelagos, we detected a high prevalence of SIEs across 66.7% of archipelagos. Approximately 50% of islands have reached the threshold area and thus may be undergoing a rapid increase in biological invasions. SIEs were more likely to occur in those archipelagos with more non-native species introduction events, more established historical non-native species, lower habitat diversity and larger archipelago area range. Our findings may have important implications not only for targeted surveillance of biological invasions on global islands but also for predicting the responses of both non-native and native species to ongoing habitat fragmentation under sustained land-use modification and climate change.

While global patterns of bee diversity have been modelled, our understanding of fine‐scale regional patterns is more limited, particularly for under‐sampled regions such as Africa. South Africa is among the exceptions on the African continent; its bee fauna (ca. 1253 species) has been well collected and documented, including mass digitising of its natural history collections. It is a region with high floral diversity, high habitat heterogeneity and variable rainfall seasonality.Here, we combine a South African bee species distributional database (877 bee species) with a geospatial modelling approach to determine fine‐scale (~11 × 11 km grid cell resolution) hotspots of bee species richness, endemism and range‐restricted species.Our analyses, based on the probabilities of occurrence surfaces for each species across 108,803 two‐minute grid cells, reveal three bee hotspots of richness: Winter rainfall, Aseasonal rainfall and Early‐to‐late summer rainfall. These hotspots contain large numbers of endemic and geographically restricted taxa. Hotspots with particularly high bee diversity include the Fynbos, Succulent Karoo and Desert biomes; the latter showing 6–20 times more species per unit area than other biomes. Our results conform with global species‐area patterns: areas of higher‐than‐expected bee density are largely concentrated in Mediterranean and arid habitats.This study further enhances our knowledge in identifying regional and global hotspots of richness and endemism for a keystone group of insects and enabling these to be accounted for when setting conservation priorities.

South Africa is considered a megadiverse country, with exceptionally high plant and relatively high animal species richness and endemism. The country’s species have been surveyed and studied for over 200 years, resulting in extensive natural science collections and a vast number of scientific papers and books. This study assessed whether existing data portals provide access to occurrence data and investigated the extent of the data in Global Biodiversity Information Facility and its completeness for plants and selected invertebrate taxa. The main focus was preserved specimen data, but some observation data from iNaturalist were also considered for selected analyses. Records that include species-level identification and co-ordinates were mapped in QGIS to show the coverage of collection localities across the country. The records that fall within the mountain range spatial layer were then extracted and counted to identify density of records per mountain range for various taxa. Forty percent of plant records are from mountain localities, and the Atlantic Cape Fold Mountains had the highest density of records. Table Mountain has been extensively collected for plants and invertebrates. A large proportion of the records for invertebrates lacked species-level identification and co-ordinates, resulting in a low number of records for analyses. The accessible data are only a relatively small subset of existing collections, and digitisation and data upgrading is considered a high priority before collecting gaps can be addressed by targeted surveys.

One of the best ways to share and disseminate biodiversity information is through the digitization of data and making it available via online databases. The rapid growth of publicly available biodiversity data is not without problems which may decrease the utility of online databases. In this study we analyze taxonomic, geographic and temporal data gaps, and bias related to existing data on selected marine invertebrate occurrences along the coastline of two African countries, Mozambique and São Tomé and Príncipe. The final marine invertebrate dataset comprises of 19.910 occurrences, but 32% of the original dataset occurrences were excluded due to data gaps. Most marine invertebrates in Mozambique were collected in seagrasses, whereas in São Tomé and Príncipe they were mostly collected offshore. The dataset has a temporal coverage from 1816 to 2019, with most occurrences collected in the last two decades. This study provides baseline information relevant to a better understanding of marine invertebrate biodiversity data gaps and bias in these habitats along the coasts of these countries. The information can be further applied to complete marine invertebrate data gaps contributing to design informed sampling strategies and advancing refined datasets that can be used in management and conservation plans in both countries.

Plant–herbivore relationships involve a significant amount of global biodiversity within complex interaction networks. Buprestidae (Coleoptera) are highly specialized herbivores, and several species have important economic and ecological impacts. We used tools derived from network theory to evaluate the structure of a plant-buprestid metaweb at three different organizational levels (network, subnetwork, and species-levels) and test whether trophic guilds and taxa differ in their patterns within the network. We also tested whether taxonomically closely related buprestid species are more likely to share the same host plant species. We found that the plant-buprestid metaweb exhibits a non-nested and significantly highly modular pattern, and most buprestid and host plant species have specialized interactions. Florivorous buprestids showed the highest diversity of host preferences and, together with Fabaceae, were the most important for the network structure as they are highly connected species. Leaf-mining buprestids had the most extreme interaction pattern among trophic guilds, with high modularity and specialized interactions. We also found a low probability to share the same group of host plants among buprestids, which decreased with taxonomic distance. Our findings uncover patterns within a plant–herbivore network at large spatial scales and at different taxonomic levels, which are shaped by the diversity of host and resources preferences, more than taxonomic relatedness. Those network patterns might reflect different ecological roles for each trophic guild and taxa. We highlight the relevance of considering the diversity of feeding habits within networks of a single type of interaction and emphasize the importance of analyze network patterns at high levels of organization.

Aim Aggregated species occurrence data are increasingly accessible through public databases for the analysis of temporal trends in the geographic distributions of species. However, biases in these data present challenges for statistical inference. We assessed potential biases in data available through GBIF on the occurrences of four flower-visiting taxa: bees (Anthophila), hoverflies (Syrphidae), leaf-nosed bats (Phyllostomidae) and hummingbirds (Trochilidae). We also assessed whether and to what extent data mobilization efforts improved our ability to estimate trends in species' distributions. Location The Neotropics. Methods We used five data-driven heuristics to screen the data for potential geographic, temporal and taxonomic biases. We began with a continental-scale assessment of the data for all four taxa. We then identified two recent data mobilization efforts (2021) that drastically increased the quantity of records of bees collected in Chile available through GBIF. We compared the dataset before and after the addition of these new records in terms of their biases and estimated trends in species' distributions. Results We found evidence of potential sampling biases for all taxa. The addition of newly-mobilized records of bees in Chile decreased some biases but introduced others. Despite increasing the quantity of data for bees in Chile sixfold, estimates of trends in species' distributions derived using the postmobilization dataset were broadly similar to what would have been estimated before their introduction, albeit more precise. Main conclusions Our results highlight the challenges associated with drawing robust inferences about trends in species' distributions using publicly available data. Mobilizing historic records will not always enable trend estimation because more data do not necessarily equal less bias. Analysts should carefully assess their data before conducting analyses: this might enable the estimation of more robust trends and help to identify strategies for effective data mobilization. Our study also reinforces the need for targeted monitoring of pollinators worldwide.