Malcolm Playfair Anderson

This paper presents an exploratory study on the taxonomic diversity of pre-Hispanic archaeofaunas in the South-Central Andes (SCA; western South America) from the Pleistocene-Holocene boundary to the Late-Holocene. The SCA is a complex of diverse environments and has undergone distinct climate events for the last 13,000 years, such as the occurrence of warmer and drier conditions in the Middle-Holocene. The South-Central Andean area was part of the larger Andes interaction area, which was a primary center for animal and plant domestication and the emergence of agro-pastoralist economies. Since subsistence was key to these processes, the SCA provides a relevant case study on the interactions among environment, foodways and sociocultural evolution. Taxonomic diversity was used here as a proxy for diet breadth. A total of 268 archaeofaunal assemblages were sampled from the zooarchaeological literature. Reviewed variables included the cultural chronology and spatial coordinates of the assemblages, as well as the presence and abundance of taxa at the family rank. Taxonomic diversity covered two dimensions: composition (families present in each assemblage) and structure (quantitative relationships among taxa), which was measured through richness (NTAXA), ubiquity and relative abundance (NISP based rank-order). Despite the uneven distribution of samples, the analyses revealed the following trends: (1) a moderate relationship between NTAXA and distance from coastline for most of the Holocene; (2) a potential decrease in assemblage richness for coastal ecoregions during the Late-Holocene; and (3) a generalized increase in the relative abundance of Camelidae.

Northern bog lemmings, Mictomys (Synaptomys) borealis, are currently being assessed for protections under the U.S. Endangered Species Act. A major impediment to comprehensive evaluation is a deficiency of data towards understanding the biology of these rodents. Inherent rarity and scarce specimen sampling, despite a continent-wide distribution, has precluded our ability to implement modern methods for resolving taxonomy, evolutionary history, and investigating multiple other species traits. Here we use a maternally inherited locus (mitochondrial cytochrome b) and between 5939 and 11 513 nuclear loci from reduced representation sequencing (ddRADseq) to investigate the evolutionary history of northern bog lemmings. We (1) qualify evidence based on morphological and early molecular studies for the genus assignment of Mictomys, (2) test the validity of multiple sub-species designations, (3) provide spatial and temporal historical biogeographic perspectives, and (4) discuss how incomplete sampling might influence conservation efforts. Both mitochondrial and nuclear datasets exhibit deep divergence and paraphyly between two recognized species, the northern (Mictomys borealis) and southern (Synaptomys cooperi) bog lemmings. Based on mtDNA, the geographically isolated subspecies (M. b. sphagnicola) was found to be divergent from all other specimens. The remainder of the species exhibited shallow intra-specific differentiation in mtDNA, however, nuclear data supports genetic distinction consistent with four geographic subspecies. Recent coalescence of all northern bog lemmings (except for M. b. sphagnicola) reflects divergence in multiple refugia through the last glacial cycle, including a well-known coastal center of endemism and multiple regions south of continental ice sheets. Regional lineages across North America suggest strong latitudinal displacement with global climate change, coupled with isolation-reconnection dynamics. This taxon suffers from a lack of modern samples through most of its distribution, severely limiting the interpretation of ongoing evolutionary processes, particularly in southern portions of the species’ range. Limited voucher specimen sampling of vulnerable populations could aid in rigorous conservation decision-making.

Climate change is a global phenomenon that will generate profound changes in biodiversity in the near future. Studies have reported negative impacts of climate change for South American amphibians; however, for Andean species such as Rhinella spinulosa, the potential response to the effects of climate change is unknown. Using ecological niche models, we estimate the potential distribution of R. spinulosa, identifying the environmental variables that explain its distribution and projecting predictions in climate change scenarios to elucidate their impact on the distribution pattern. The results revealed that the variables of elevation (48.7%), mean temperature of the hottest quarter (44.2%), and topographic humidity index (3.2%) were the most important contributors to the model and are predictors of the distribution of R. spinulosa. The most suitable areas for its distribution are its current range, extending to the north, as well as on the western Andean slope and Argentine Patagonia. Predictions for the future (year 2080) under two scenarios (benign and severe) coincide with the distribution predicted for the current one. Climatic conditions will not be considerably different in the distribution area of R. spinulosa, which may be due to the buffer effect of the mountain range. However, freshwater ecosystems will be more at risk from climate change, which could affect the reproductive success and survival of amphibians. Therefore, we recommend evaluating water availability at a local scale to understand the potential changes in the geographic distribution of R. spinulosa.

Identifying the association between the patterns of niche occupation and phylogenetic relationships among sister clades and assisting conservation planning implications are of the most important applications of species distribution models (SDMs). However, most studies have been carried out regardless of within taxon genetic differentiation and the potential of local adaptation occurring within the species level. The Pallas's cat (Otocolobus manul) is a less‐studied species with unknown biogeography and phylogenetic structure across a widespread yet isolated range from the Caucasus to eastern China. In the current study, by considering a previously proposed genetic structure and based on a cluster analysis on climatic variables, we supposed three clades for this species, including O. m. manul, O. m. ferrugineus, and O. m. nigripectus. We developed SDM for each clade separately and compared it with a general distribution model of the species to determine whether the hypothesized taxonomic resolution affects the predicted ecological niche of the within‐species structures. We assessed the effect of climate change on the future distribution of the species to detect the most sensitive clades to global warming scenarios. Our results showed that for all clades' models, the AUC and TSS were greater than the general model. Access to the preferred prey of the Pallas's cat, that is, pika, had a significant effect on the distribution of O. m. manul and O. m. ferrugineus, whereas the most influential variable affecting O. m. nigripectus habitat suitability was terrain slope. Based on our future projections, we found that future climate change likely threatens the clades O. m. ferrugineus and O. m. nigripectus more than O. m. manul, findings that were hidden in the general model. Our results highlight the proficiency of SDMs in recognizing within‐taxon habitat use of widespread species and the necessity of this procedure for implementing effective conservation planning of these species.

Climate change is a global phenomenon that will generate profound changes in biodiversity in the near future. Studies have reported negative impacts of climate change for South American amphibians; however, for Andean species such as Rhinella spinulosa, the potential response to the effects of climate change is unknown. Using ecological niche models, we estimate the potential distribution of R. spinulosa, identifying the environmental variables that explain its distribution and projecting predictions in climate change scenarios to elucidate their impact on the distribution pattern. The results revealed that the variables of elevation (48.7%), mean temperature of the hottest quarter (44.2%), and topographic humidity index (3.2%) were the most important contributors to the model and are predictors of the distribution of R. spinulosa. The most suitable areas for its distribution are its current range, extending to the north, as well as on the western Andean slope and Argentine Patagonia. Predictions for the future (year 2080) under two scenarios (benign and severe) coincide with the distribution predicted for the current one. Climatic conditions will not be considerably different in the distribution area of R. spinulosa, which may be due to the buffer effect of the mountain range. However, freshwater ecosystems will be more at risk from climate change, which could affect the reproductive success and survival of amphibians. Therefore, we recommend evaluating water availability at a local scale to understand the potential changes in the geographic distribution of R. spinulosa.

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.

Emerging diseases caused by coronaviruses of likely bat origin (e.g., SARS, MERS, SADS, COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this spillover may help target prevention programs. We derive current range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human viral seroprevalence, and antibody duration to estimate that a median of 66,280 people (95% CI: 65,351–67,131) are infected with SARSr-CoVs annually in Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence. Coronaviruses may spill over from bats to humans. This study uses epidemiological data, species distribution models, and probabilistic risk assessment to map overlap among people and SARSr-CoV bat hosts and estimate how many people are infected with bat-origin SARSr-CoVs in Southeast Asia annually.

Renewable energy is one of the most important sources of energy for a decarbonized future. The use of renewable energy necessitates the thorough study of interlinkages with social issues such as the Sustainable Development Goals (SDGs). However, there are no high-resolution renewable energy datasets for analyzing interlinkages. The goal of this research is to 1) create a high-resolution geographically explicit renewable energy potential map, 2) evaluate the SDGs nexus using the potential map, 3) discuss the improvement of renewable energy dataset, and 4) discuss nexus issues for implementing renewable energy systems in Japan. Our potential map has the same resolution of 500 m and unit of annual electricity generation on each energy. The occurence of endangered birds was overlapping with the area having a lot of solar energy potential. Local renewable energy is difficult to access on a small spatial scale, especially in urban regions like Tokyo. Our potential map can be used as a database for site selection and area zoning. The findings suggest that implementing decentralized renewable energy systems in today's highly concentrated megacities, such as the Tokyo Metropolitan Area, is extremely challenging, and that this type of centralized-oriented land design is likely to exacerbate the problem of energy poverty.

The Amazon has high biodiversity, which has been attributed to different geological events such as the formation of rivers. The Old and Young Amazon hypotheses have been proposed regarding the date of the formation of the Amazon basin. Different studies of historical biogeography support the Young A…

Species Distribution Models (SDMs) are a cornerstone of climate change conservation research but temporal extrapolations into future climate scenarios cannot be verified until later this century. One way of assessing the robustness of projections is to compare their consistency between different mod…