Concurrent Exposure of Bottlenose Dolphins (Tursiops truncatus) to Multiple Algal Toxins in Sarasota Bay, Florida, USA

Sentinel species such as bottlenose dolphins (Tursiops truncatus) can be impacted by large-scale mortality events due to exposure to marine algal toxins. In the Sarasota Bay region (Gulf of Mexico, Florida, USA), the bottlenose dolphin population is frequently exposed to harmful algal blooms (HABs) of Karenia brevis and the neurotoxic brevetoxins (PbTx; BTX) produced by this dinoflagellate. Live dolphins sampled during capture-release health assessments performed in this region tested positive for two HAB toxins; brevetoxin and domoic acid (DA). Over a ten-year study period (2000–2009) we have determined that bottlenose dolphins are exposed to brevetoxin and/or DA on a nearly annual basis (i.e., DA: 2004, 2005, 2006, 2008, 2009; brevetoxin: 2000, 2004, 2005, 2008, 2009) with 36% of all animals testing positive for brevetoxin (n = 118) and 53% positive for DA (n = 83) with several individuals (14%) testing positive for both neurotoxins in at least one tissue/fluid. To date there have been no previously published reports of DA in southwestern Florida marine mammals, however the May 2008 health assessment coincided with a Pseudo-nitzschia pseudodelicatissima bloom that was the likely source of DA observed in seawater and live dolphin samples. Concurrently, both DA and brevetoxin were observed in common prey fish. Although no Pseudo-nitzschia bloom was identified the following year, DA was identified in seawater, fish, sediment, snails, and dolphins. DA concentrations in feces were positively correlated with hematologic parameters including an increase in total white blood cell (p = 0.001) and eosinophil (p<0.001) counts. Our findings demonstrate that dolphins within Sarasota Bay are commonly exposed to two algal toxins, and provide the impetus to further explore the potential long-term impacts on bottlenose dolphin health

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Vitamin D status predicts reproductive fitness in a wild sheep population

Vitamin D deficiency has been associated with the development of many human diseases, and with poor reproductive performance in laboratory rodents. We currently have no idea how natural selection directly acts on variation in vitamin D metabolism due to a total lack of studies in wild animals. Here, we measured serum 25 hydroxyvitamin D (25(OH)D) concentrations in female Soay sheep that were part of a long-term field study on St Kilda. We found that total 25(OH)D was strongly influenced by age, and that light coloured sheep had higher 25(OH)D(3) (but not 25(OH)D(2)) concentrations than dark sheep. The coat colour polymorphism in Soay sheep is controlled by a single locus, suggesting vitamin D status is heritable in this population. We also observed a very strong relationship between total 25(OH)D concentrations in summer and a ewe’s fecundity the following spring. This resulted in a positive association between total 25(OH)D and the number of lambs produced that survived their first year of life, an important component of female reproductive fitness. Our study provides the first insight into naturally-occurring variation in vitamin D metabolites, and offers the first evidence that vitamin D status is both heritable and under natural selection in the wild

The genetic architecture of helminth-specific immune responses in a wild population of Soay sheep (Ovis aries)

Much of our knowledge of the drivers of immune variation, and how these responses vary over time, comes from humans, domesticated livestock or laboratory organisms. While the genetic basis of variation in immune responses have been investigated in these systems, there is a poor understanding of how genetic variation influences immunity in natural, untreated populations living in complex environments. Here, we examine the genetic architecture of variation in immune traits in the Soay sheep of St Kilda, an unmanaged population of sheep infected with strongyle gastrointestinal nematodes. We assayed IgA, IgE and IgG antibodies against the prevalent nematode Teladorsagia circumcincta in the blood plasma of > 3,000 sheep collected over 26 years. Antibody levels were significantly heritable (h2 = 0.21 to 0.57) and highly stable over an individual’s lifespan. IgA levels were strongly associated with a region on chromosome 24 explaining 21.1% and 24.5% of heritable variation in lambs and adults, respectively. This region was adjacent to two candidate loci, Class II Major Histocompatibility Complex Transactivator (CIITA) and C-Type Lectin Domain Containing 16A (CLEC16A). Lamb IgA levels were also associated with the immunoglobulin heavy constant loci (IGH) complex, and adult IgE levels and lamb IgA and IgG levels were associated with the major histocompatibility complex (MHC). This study provides evidence of high heritability of a complex immunological trait under natural conditions and provides the first evidence from a genome-wide study that large effect genes located outside the MHC region exist for immune traits in the wild

A review of zoonotic infection risks associated with the wild meat trade in Malaysia.

The overhunting of wildlife for food and commercial gain presents a major threat to biodiversity in tropical forests and poses health risks to humans from contact with wild animals. Using a recent survey of wildlife offered at wild meat markets in Malaysia as a basis, we review the literature to determine the potential zoonotic infection risks from hunting, butchering and consuming the species offered. We also determine which taxa potentially host the highest number of pathogens and discuss the significant disease risks from traded wildlife, considering how cultural practices influence zoonotic transmission. We identify 51 zoonotic pathogens (16 viruses, 19 bacteria and 16 parasites) potentially hosted by wildlife and describe the human health risks. The Suidae and the Cervidae families potentially host the highest number of pathogens. We conclude that there are substantial gaps in our knowledge of zoonotic pathogens and recommend performing microbial food safety risk assessments to assess the hazards of wild meat consumption. Overall, there may be considerable zoonotic risks to people involved in the hunting, butchering or consumption of wild meat in Southeast Asia, and these should be considered in public health strategies

To trade or not to trade? Using Bayesian Belief Networks to assess how to manage commercial wildlife trade in a complex world

International commercial trade in wildlife, whether legal or illegal, is one of the greatest threats to multiple species of wildlife today. Opinions on how to address it are deeply divided across the conservation community. Approaches fall into two broad categories: making the trade illegal to protect against any form of commercial trade or allowing some or all of the trade to be legal and seeking to manage it through sustainable trade. The conservation community is often deeply polarized on which is the better option. We posit that a way to choose between these options is by considering species-specific attributes of biological productivity, management context, and demand. We develop a conceptual framework to assess which option is more likely to result in successful conservation of a species. We show how to construct a Bayesian Belief Network (BBN) to model how these attributes (1) interact to affect the sustainability of the species’ population and (2) vary under different trade management regimes. This approach can support scientifically based decision-making, by predicting the likely sustainability outcome for a population of a species under different trade management regimes, given its particular characteristics and context. The BBN allows identification of key points at which conservation interventions could change the potential outcome. It also provides the opportunity to explore how different assumptions about how humans might respond to different trade regimes affects outcomes. We illustrate these ideas by using the BBN for a hypothetical terrestrial mammal species population and discuss how the BBN can be extended for species with different characteristics, for example, those that can be stockpiled or when there are multiple products. This approach has the potential to help the conservation community to assess the most appropriate regime for managing wildlife trade in a transparent, open, and scientifically based way

To trade or not to trade? Using Bayesian Belief Networks to assess how to manage commercial wildlife trade in a complex world

International commercial trade in wildlife, whether legal or illegal, is one of the greatest threats to multiple species of wildlife today. Opinions on how to address it are deeply divided across the conservation community. Approaches fall into two broad categories: making the trade illegal to protect against any form of commercial trade or allowing some or all of the trade to be legal and seeking to manage it through sustainable trade. The conservation community is often deeply polarized on which is the better option. We posit that a way to choose between these options is by considering species-specific attributes of biological productivity, management context, and demand. We develop a conceptual framework to assess which option is more likely to result in successful conservation of a species. We show how to construct a Bayesian Belief Network (BBN) to model how these attributes (1) interact to affect the sustainability of the species’ population and (2) vary under different trade management regimes. This approach can support scientifically based decision-making, by predicting the likely sustainability outcome for a population of a species under different trade management regimes, given its particular characteristics and context. The BBN allows identification of key points at which conservation interventions could change the potential outcome. It also provides the opportunity to explore how different assumptions about how humans might respond to different trade regimes affects outcomes. We illustrate these ideas by using the BBN for a hypothetical terrestrial mammal species population and discuss how the BBN can be extended for species with different characteristics, for example, those that can be stockpiled or when there are multiple products. This approach has the potential to help the conservation community to assess the most appropriate regime for managing wildlife trade in a transparent, open, and scientifically based way