Guy Anstruther Knox Marshall

Insect biological control agents may be released in relatively few locations; thus, the rate of spread is critical to predicting the spatial distribution of the agent.Exotic dung beetles have been introduced into Australia since the 1960s to bury dung, reduce bush fly populations, increase pasture productivity and improve livestock health.We use a stochastic cellular automata model to predict the historical occupancy and abundance of introduced dung beetles in the South West agricultural region of Western Australia. The model predicts the spread of four species of dung beetles in six‐month time steps for 10 years following initial release. Our model includes release locations, species‐specific ecological parameters, dung resource availability and weather variables.The average rate of spread varied between species from a high of ca. 79 km/year (Euoniticellus intermedius) to a low of 28 km/year (Onthophagus taurus). Thus, after 10 years, the area of spread varied between 99,175 and 34,175 km2 and abundance varied from 88,100 to 4,189 beetles/km2.These findings provide an estimate of the spread patterns of dung beetles. The model can be used to guide future dung beetle release programmes in Australia and elsewhere.

Climate change has a direct impact on biodiversity, affecting ecosystems and altering their balance. Many taxa, including insects, are likely to be affected by climate change in terms of geographic distribution. Sarcophagid flies, such as Sarcophaga dux and Sarcophaga haemorrhoidalis, are important flies because of their apparent ecological, forensic, and medical significance. Global habitat suitability varies as a result of climate change. In wildlife management, models that predict species’ spatial distribution are being used more and more, which emphasizes the need for reliable methods to evaluate their accuracy. Consequently, the statistical robustness of maximum entropy was implemented in Maxent to model the current and future global distribution of both flies, involving occurrence data of 155 and 87 points for S. dux and S. haemorrhoidalis, respectively. Based on the Pearson correlation and Jackknife test, five bioclimatic variables were used for current and future predictive models. For future models, two representative concentration pathways (RCPs), 2.6 and 8.5, for 2050 and 2070 were applied. Both statistical parameters, AUC and TSS, were used to assess the resulting models with values equal to 0.80 (±0.01) and 0.9, respectively, for S. dux and equal to 0.86 (±0.01) and 0.92 for S. haemorrhoidalis. The resulting models for S. dux showed high and very high suitability in Europe, Tropical Africa, India, Canada, the United States from Alaska to Florida, Brazil, and Australia. In the case of S. haemorrhoidalis Europe and North and South America displayed low to medium suitability, but North Africa, including Egypt; Tropical Africa; Asia, including Saudi Arabia, India, and China; and Australia showed increased suitability. Decision-makers are put in conflict with their duties to avert destruction in the economic, medical, and ecological sectors by such anticipated models, and use these predictive models as a cornerstone for building a control strategy for such forensically important flies at local spatial scales.

Ceratitis capitata (Wiedemann), the Mediterranean fruit fly or medfly, is one of the world's most serious threats to fresh fruits. It is highly polyphagous (recorded from over 300 hosts) and capable of adapting to a wide range of climates. This pest has spread to the EPPO region and is mainly present in the southern part, damaging Citrus and Prunus. In Northern and Central Europe records refer to interceptions or short‐lived adventive populations only. Sustainable programs for surveillance, spread assessment using models and control strategies for pests such as C. capitata represent a major plant health challenge for all countries in Europe. This article includes a review of pest distribution and monitoring techniques in 11 countries of the EPPO region. This work compiles information that was crucial for a better understanding of pest occurrence and contributes to identifying areas susceptible to potential invasion and establishment. The key outputs and results obtained in the Euphresco project included knowledge transfer about early detection tools and methods used in different countries for pest monitoring. A MaxEnt software model resulted in risk maps for C. capitata in different climatic regions. This is an important tool to help decision making and to develop actions against this pest in the different partner countries.

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.

Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.

The black soldier fly, Hermetiaillucens (Linnaeus, 1758), is a saprophagous species used to decompose organic matter. This study proposes a distribution model of H.illucens to illustrate its current and future distribution. The methodology includes data collection from the Global Biodiversity Information Facility (GBIF), complemented with iNaturalist, manual expert curation of occurrence records, six species distribution models algorithms and one ensemble model. The average temperature of the driest annual quarter and the precipitation of the coldest annual quarter were the key variables influencing the potential distribution of H.illucens. The distribution range is estimated to decrease progressively and their suitable habitats could change dramatically in the future due to global warming. On the other hand, current optimal habitats would become uninhabitable for the species, mainly at low latitudes. Under this scenario, the species is projected to move to higher latitudes and elevations in the future. The results of this study provide data on the distribution of H.illucens, facilitating its location, management and sustainable use in current and future scenarios.

BackgroundCrimean-Congo haemorrhagic fever (CCHF) is a widespread tick-borne viral infection, present across Africa and Eurasia, which might pose a cryptic public health problem in Uganda. We aimed to understand the magnitude and distribution of CCHF risk in humans, livestock and ticks across Uganda by synthesising epidemiological (cross-sectional) and ecological (modelling) studies.MethodsWe conducted a cross-sectional study at three urban abattoirs receiving cattle from across Uganda. We sampled humans (n = 478), livestock (n = 419) and ticks (n = 1065) and used commercially-available kits to detect human and livestock CCHF virus (CCHFV) antibodies and antigen in tick pools. We developed boosted regression tree models to evaluate the correlates and geographical distribution of expected tick and wildlife hosts, and of human CCHF exposures, drawing on continent-wide data.FindingsThe cross-sectional study found CCHFV IgG/IgM seroprevalence in humans of 10·3% (7·8–13·3), with antibody detection positively associated with reported history of tick bite (age-adjusted odds ratio = 2·09 (1·09–3·98)). Cattle had a seroprevalence of 69·7% (65·1–73·4). Only one Hyalomma tick (CCHFV-negative) was found. However, CCHFV antigen was detected in Rhipicephalus (5·9% of 304 pools) and Amblyomma (2·9% of 34 pools) species. Modelling predicted high human CCHF risk across much of Uganda, low environmental suitability for Hyalomma, and high suitability for Rhipicephalus and Amblyomma.InterpretationOur epidemiological and ecological studies provide complementary evidence that CCHF exposure risk is widespread across Uganda. We challenge the idea that Hyalomma ticks are consistently the principal reservoir and vector for CCHFV, and postulate that Rhipicephalus might be important for CCHFV transmission in Uganda, due to high frequency of infected ticks and predicted environmental suitability.FundingUCL Global Challenges Research Fund (GCRF) and Pan-African Network on Emerging and Re-Emerging Infections (PANDORA-ID-NET) funded by the European and Developing Countries Clinical Trials Partnership (EDCTP) under the EU Horizon 2020 Framework Programme for Research and Innovation.

Wildlife trade is a major driver of biodiversity loss, yet whilst the impacts of trade in some species are relatively well-known, some taxa, such as many invertebrates are often overlooked. Here we explore global patterns of trade in the arachnids, and detected 1,264 species from 66 families and 371 genera in trade. Trade in these groups exceeds millions of individuals, with 67% coming directly from the wild, and up to 99% of individuals in some genera. For popular taxa, such as tarantulas up to 50% are in trade, including 25% of species described since 2000. CITES only covers 30 (2%) of the species potentially traded. We mapped the percentage and number of species native to each country in trade. To enable sustainable trade, better data on species distributions and better conservation status assessments are needed. The disparity between trade data sources highlights the need to expand monitoring if impacts on wild populations are to be accurately gauged and the impacts of trade minimised. Trade in arachnids includes millions of individuals and over 1264 species, with over 70% of individuals coming from the wild.

von Humboldt’s tree-line concept has dominated mountain ecology for almost two hundred years, and is considered a key indicator for monitoring change in biome boundaries and biodiversity shifts under climate change. Even though the concept of life zones and elevation gradients are a globally observe…