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ABSTRACT Molecular tools are increasingly being used to survey the presence of biodiversity and their interactions within ecosystems. Indirect methods, like environmental DNA (eDNA) and invertebrate‐derived DNA (iDNA), are dependent on sequence databases with accurate and sufficient taxonomic representation. These methods are increasingly being used in regions and habitats where direct detection or observations can be difficult for a variety of reasons. Madagascar is a biodiversity hotspot with a high proportion of endemic species, many of which are threatened or endangered. Here we describe a new resource, VoronaGasyCodes, a curated database of newly published genetic sequences from Malagasy birds. Our database is currently populated with six mitochondrial genes or DNA barcodes for 142 species including 70% of the birds endemic to the island and will be periodically updated as new data become available. We demonstrate the utility of our database with an iDNA study of leech blood meals where we successfully identified 77% of the hosts to species. These types of resources for characterising biodiversity are critical for insights into species distribution, discovery of new taxa, novel ecological connections and advancing conservation and restoration measures. 

ABSTRACT Hantaviruses are globally distributed zoonotic pathogens capable of causing fatal disease in humans. Addressing the risk of hantavirus spillover from animal reservoirs to humans requires identifying the local reservoirs (usually rodents and other small mammals) and the predictors of infection, such as habitat characteristics and human exposure. We screened a collection of 1663 terrestrial small mammals and 227 bats for hantavirus RNA, comprised of native and non‐native species from northeastern Madagascar, trapped over 5 successive years. We specifically investigated the influence of diverse habitat types: villages, agricultural fields, regrowth areas, secondary and semi‐intact forests on infection with hantaviruses. We detected Hantavirus RNA closely related to the previously described Anjozorobe virus in 9.5% ofRattus rattussampled, with an absence of detection in other species. Land‐use had a complex impact on hantavirus infections: intensive land‐use positively correlated with the abundance ofR. rattusand the averageR. rattusbody size varied between habitats. Larger individuals had a higher probability of infection, regardless of sex. Thus, villages and pristine forests which host the smallest, and hence, least infected rats, represent the lowest risk for hantavirus exposure to people while flooded rice fields which were home to the largest rats, and subsequently most infected rats, represent the greatest exposure risk. These findings provide new insights into the relationship between rat ecology and the gradients of hantavirus exposure risk for farmers in northeastern Madagascar as they work in different land‐use types. 

Small terrestrial mammals are major hosts of infectious agents responsible for zoonotic diseases. Astroviruses (AstVs)–the cause of non-bacterial gastroenteritis mainly affecting young children–have been detected in a wide array of mammalian and avian host species. However, understanding the factors that influence AstV infection within and across hosts is limited. Here, we investigated the impact of land use changes on AstVs in terrestrial small mammals in rural northeastern Madagascar. We sampled 515 small mammals, representing seven endemic and four introduced species. Twenty-two positive samples were identified, all but one of which were found in the introduced speciesMus musculusandRattus rattus(family Muridae), with a positivity rate of 7.7% (6/78) and 5.6% (15/266), respectively. The non-introduced rodent case was from an endemic shrew-tenrec (family Tenrecidae). We found the highest positivity rate of AstVs infection in brushy regrowth (17.5%, 7/40) as compared to flooded rice fields (4.60%, 8/174), secondary forest (4.1%, 3/74), agroforest (3.6%, 1/28), village (2.61%, 3/115), and semi-intact forest (0%, 0/84). A phylogenetic analysis revealed an association between AstVs and their rodent host species. None of the viruses were phylogenetically related to AstVs previously described in Malagasy bats. This study supports AstV circulation in synanthropic animals in agricultural habitats of Madagascar and highlights the need to assess the spillover risk to human populations in rural areas. 

Abstract Global biodiversity is under accelerating threats, and species are succumbing to extinction before being described. Madagascar’s biota represents an extreme example of this scenario, with the added complication that much of its endemic biodiversity is cryptic. Here we illustrate best practices for clarifying cryptic diversification processes by presenting an integrative framework that leverages multiple lines of evidence and taxon-informed cut-offs for species delimitation, while placing special emphasis on identifying patterns of isolation by distance. We systematically apply this framework to an entire taxonomically controversial primate clade, the mouse lemurs (genusMicrocebus, family Cheirogaleidae). We demonstrate that species diversity has been overestimated primarily due to the interpretation of geographic variation as speciation, potentially biasing inference of the underlying processes of evolutionary diversification. Following a revised classification, we find that crypsis within the genus is best explained by a model of morphological stasis imposed by stabilizing selection and a neutral process of niche diversification. Finally, by clarifying species limits and defining evolutionarily significant units, we provide new conservation priorities, bridging fundamental and applied objectives in a generalizable framework. 

Automated sound recognition tools can be a useful complement to d/Deaf and hard of hearing (DHH) people's typical communication and environmental awareness strategies. Pre-trained sound recognition models, however, may not meet the diverse needs of individual DHH users. While approaches from human-centered machine learning can enable non-expert users to build their own automated systems, end-user ML solutions that augment human sensory abilities present a unique challenge for users who have sensory disabilities: how can a DHH user, who has difficulty hearing a sound themselves, effectively record samples to train an ML system to recognize that sound? To better understand how DHH users can drive personalization of their own assistive sound recognition tools, we conducted a three-part study with 14 DHH participants: (1) an initial interview and demo of a personalizable sound recognizer, (2) a week-long field study of in situ recording, and (3) a follow-up interview and ideation session. Our results highlight a positive subjective experience when recording and interpreting training data in situ, but we uncover several key pitfalls unique to DHH users---such as inhibited judgement of representative samples due to limited audiological experience. We share implications of these results for the design of recording interfaces and human-the-the-loop systems that can support DHH users to build sound recognizers for their personal needs.