Making marine life count: a new baseline for policy

The Census of Marine Life aids practical work of the Convention on Biological Diversity, discovers and tracks ocean biodiversity, and supports marine environmental planning.     

Using nest captures and video cameras to estimate survival and abundance of breeding Piping Plovers Charadrius melodus

The estimation of abundance is fundamental to ecology and conservation but often is difficult or impossible to accomplish reliably. Recent improvements in wildlife cameras and ecological modelling have allowed for improved accuracy in estimates of abundance. In this study, we paired nest captures and high-definition nest video camera monitoring with modelling for a novel approach to estimate survival and abundance of threatened Piping Plovers Charadrius melodus breeding on Missouri River sandbars. From 2005 to 2014, we captured individuals on nests and uniquely marked them and recaptured previously marked individuals. In 2015–2017, we resighted marked individuals using small, high-definition video cameras deployed at nests, and counted the number of marked and unmarked breeding individuals associated with nests. We estimated apparent survival and derived estimates of the abundance of breeding individuals and population growth each year using a state-space Jolly–Seber superpopulation model with the addition of a binomial band ratio model for data collected using nest video cameras. Apparent survival averaged 0.73 ± 0.03 (mean ± sd) throughout the study. The number of breeding individuals varied, with the population increasing from 2012 to 2017 following a major habitat creation event. This study provides one of the few examples of camera data being used to produce demographic parameter and abundance estimates for an avian species. The camera and modelling methods described in this study may be applicable to other avian species in which some portion of the breeding population is uniquely marked.     

Limitations of trait‐based approaches for stressor assessment: The case of freshwater invertebrates and climate drivers

The appeal of trait‐based approaches for assessing environmental vulnerabilities arises from the potential insight they provide into the mechanisms underlying the changes in populations and community structure. Traits can provide ecologically based explanations for observed responses to environmental changes, along with predictive power gained by developing relationships between traits and environmental variables. Despite these potential benefits, questions remain regarding the utility and limitations of these approaches, which we explore focusing on the following questions: (a) How reliable are predictions of biotic responses to changing conditions based on single trait–environment relationships? (b) What factors constrain detection of single trait–environment relationships, and how can they be addressed? (c) Can we use information on meta‐community processes to reveal conditions when assumptions underlying trait‐based studies are not met? We address these questions by reviewing published literature on aquatic invertebrate communities from stream ecosystems. Our findings help to define factors that influence the successful application of trait‐based approaches in addressing the complex, multifaceted effects of changing climate conditions on hydrologic and thermal regimes in stream ecosystems. Key conclusions are that observed relationships between traits and environmental stressors are often inconsistent with predefined hypotheses derived from current trait‐based thinking, particularly related to single trait–environment relationships. Factors that can influence findings of trait‐based assessments include intercorrelations of among traits and among environmental variables, spatial scale, strength of biotic interactions, intensity of habitat disturbance, degree of abiotic stress, and methods of trait characterization. Several recommendations are made for practice and further study to address these concerns, including using phylogenetic relatedness to address intercorrelation. With proper consideration of these issues, trait‐based assessment of organismal vulnerability to environmental changes can become a useful tool to conserve threatened populations into the future.     

MHC class II association study in eight breeds of dog with hypoadrenocorticism

Canine hypoadrenocorticism is an endocrine disorder characterised by inadequate secretion of steroid hormones from the adrenal glands. Pathology results from immune-mediated destruction of the adrenal cortex, which is similar to that seen in the human Addison’s disease. Both the canine and human diseases have similar clinical presentation, with the diagnosis based on performing a dynamic adrenocorticotropic hormone stimulation test. MHC class II has previously been associated with the human and canine diseases. In the current study, we conducted an MHC class II association study in eight breeds of dog with diagnoses of hypoadrenocorticism. We demonstrated significant differences in dog leukocyte antigen (DLA) haplotype frequencies in six of these breeds: Cocker spaniel, Springer spaniel, Labrador, West Highland white terrier (WHWT), Bearded collie, and Standard poodle. In the Springer spaniel, the DLA-DRB1*015:01--DQA1*006:01--DQB1*023:01 haplotype was significantly associated with disease risk (p?=?0.014, odds ratio (OR)?=?5.14) and showed a similar trend in the Cocker spaniel. This haplotype is related to one associated with hypoadrenocorticism in the Nova Scotia duck tolling retriever. Similar haplotypes shared between breeds were demonstrated, with DLA-DRB1*001:01--DQA1*001:01--DQB1*002:01 more prevalent in both affected Labrador (p?=?0.0002, OR?=?3.06) and WHWT (p?=?0.01, OR?=?2.11). Other haplotypes that have not previously been associated with the disease were identified. The inter-breed differences in DLA haplotypes associated with susceptibility to canine hypoadrenocorticism could represent divergent aetiologies. This could have implications for clinical diagnosis and future comparative studies. Alternatively, it may suggest that the gene of interest is closely linked to the MHC.     

Familial X-linked mental retardation, verbal disability, and marker X chromosomes.

Cytogenetic and verbal studies were done on members of four families with non-specific X-linked mental retardation. Cytogenetic analysis was done using media 199 and GTG-banding; one family had a marker X with a fragile site in band Xq27 or 28. Preliminary results indicate variation of culture conditions can effect the frequency of the marker X. A generalized language disability was found which tended to concentrate in the areas of auditory reception, auditory sequential memory, visual closure and grammatic closure. Articulation errors involved the same sounds which are late in normal development and occur most frequently in both the general population and a Down syndrome population.     

Ultrastructural analysis of conidiophore development in the fungusAspergillus nidulans using freeze-substitution

Summary Conidiation inAspergillus nidulans can be divided conveniently into five morphologically distinct stages. These are development of the conidiophore stalk, formation of the conidiophore vesicle, differentiation of metulae, differentiation of phialides, and production of conidia. The results presented here demonstrate that freeze-substitution fixation greatly facilitates the study of most of these stages. Ultrastructural features of vesicles, mitochondria, microtubules and nuclei were more easily resolved in freeze-substituted samples than in chemically fixed samples. In addition, certain structures and events simply not visible in chemically fixed samples were found routinely in freeze-substituted samples. Examples include Golgi bodies and multivesicular bodies and mitotic divisions associated with various stages of conidiation.Abbreviations C conidium - CI conidium initial - CV conidiophore vesicle - FC foot cell - GB Golgi body - M mitochondrion - ME metula - MT microtubule - MVB multivesicular body - N nucleus - PM plasma membrane - P phialide - RER rough endoplasmic reticulum - S spindle apparatus - SPB spindle pole body - V vacuole - W fungal wall - WB Woronin body