Effects of Anthropogenic Stressors and Changes in Biodiversity on Lower Chesapeake Bay, VA USA Seagrass Systems

Anthropogenic stressors are increasingly changing conditions in coastal areas and impacting important habitats. But, when multiple stressors act simultaneously, their effects on ecosystems become more difficult to predict. In Chesapeake Bay, USA, predictions suggest that anthropogenic stressors from climate change, such as warming temperatures, may increase the frequency and severity of storm events, leading to increased freshwater, nutrient, and sediment inputs. Coastal development, another source of anthropogenic stressors, continues to increase with growing coastal populations, and may lead to altered sediment characteristics, habitat fragmentation, altered food webs, and loss of vegetated habitats. Community processes may interact with stressors, for example, immigration of propagules between habitat patches may alter diversity, and modify community response to stressors. Changes in biodiversity might alter ecosystem functioning and services, but diverse ecosystems may be more stable especially in the face of multiple stressors. Many habitats are vulnerable to anthropogenic stressors, including seagrass systems, which provide many valuable ecosystem services. Understanding how multiple stressors and community processes interact now is key to maintaining ecosystem services in the future. Using a model seagrass (Zostera marina) system, I tested the effects of multiple stressors and their interactions with crustacean grazer immigration and diversity on ecosystem properties in a series of fully-factorial mesocosm experiments. I found that despite grazer species having varied responses to individual stressors, grazing pressure was largely maintained in spite of multiple stressors. More diverse grazer assemblages generally stabilized epiphytic algal biomass in the face of stressors, thereby increasing the resistance stability of this important component of the fouling community. Immigration of crustacean grazers did not interact significantly with stressors, and had little effect overall except to increase grazer biomass. Stressors generally reduced primary producer biomass, although in some cases they favored epiphytic algae. Generally, I did not find interactions among stressors and grazer immigration or diversity, even though diverse grazer assemblages stabilized epiphytic algal biomass. to assess potential impacts of coastal development, I surveyed twenty seagrass beds in lower Chesapeake Bay, VA and assessed local shoreline development effects on adjacent seagrass beds. I sampled primary producers, consumers, water quality, and sediment characteristics in seagrass beds, and characterized development along the adjacent shoreline. I found that development significantly affected sediment characteristics, while epifaunal and epiphytic algal biomass was significantly higher on the Western versus the Eastern side of the bay. Grazer and predator biomass did not differ with either development or bay region. Thus, in seagrass communities, various factors appear to drive sediment and biological community properties on different spatial scales. This may be an important consideration for management, because efforts that incorporate spatial scales of ecosystem processes will likely have more impact. Overall, these results suggest that stressor impacts in seagrass ecosystems generally do not interact but are sometimes context specific, while grazer diversity may have a limited but potentially important role in buffering certain ecosystem properties again stressors. Different factors appear to influence ecosystem properties at various spatial scales, an important consideration for predicting future impacts of multiple anthropogenic stressors in submerged vegetated systems

Invasion disharmony in the global biogeography of native and non‐native beetle species

International audienceAim The concept of "island disharmony" has been widely applied to describe the systematic over- and under-representation of taxa on islands compared to mainland regions. Here, we explore an extension of that concept to biological invasions. We compare biogeographical patterns in native and non-native beetle (Coleoptera) assemblages from around the world to test whether beetle invasions represent a random sample of species or whether some families are more prone to invade than others. Location Global. Methods Numbers of non-native beetle species established in ten regions worldwide were compared with the land area of each region. The distribution of species among families was compared with the distribution among families for all species native to the same region and with the distribution among families for the global pool of all known beetle species. Ordination analysis was used to characterize differences among native and non-native assemblages based upon the distribution of species among families. Results We report a total of 1,967 non-native beetle species across all ten regions, and a classic log-log relationship between numbers of species per region and land area though relationships are generally stronger for native assemblages. Some families (e.g., Dermestidae and Bostrichidae) are over-represented and others (e.g., Carabidae, Scarabaeidae and Buprestidae) are under-represented in non-native assemblages. The distribution of species among families is generally similar among native assemblages with greatest similarities among nearby regions. In contrast, non-native species assemblages are more similar to each other than to native species assemblages. Main conclusions Certain families are over-represented, and others are under-represented in non-native beetle assemblages compared to native assemblages, indicating "invasion disharmony" in the global representation of beetle families. Similarities in composition among non-native assemblages may reflect unobserved associations with invasion pathways and life-history traits that shape invasion success of different insect groups

Expanding NEON biodiversity surveys with new instrumentation and machine learning approaches

A core goal of the National Ecological Observatory Network (NEON) is to measure changes in biodiversity across the 30-yr horizon of the network. In contrast to NEON’s extensive use of automated instruments to collect environmental data, NEON’s biodiversity surveys are almost entirely conducted using traditional human-centric field methods. We believe that the combination of instrumentation for remote data collection and machine learning models to process such data represents an important opportunity for NEON to expand the scope, scale, and usability of its biodiversity data collection while potentially reducing long-term costs. In this manuscript, we first review the current status of instrument-based biodiversity surveys within the NEON project and previous research at the intersection of biodiversity, instrumentation, and machine learning at NEON sites. We then survey methods that have been developed at other locations but could potentially be employed at NEON sites in future. Finally, we expand on these ideas in five case studies that we believe suggest particularly fruitful future paths for automated biodiversity measurement at NEON sites: acoustic recorders for sound-producing taxa, camera traps for medium and large mammals, hydroacoustic and remote imagery for aquatic diversity, expanded remote and ground-based measurements for plant biodiversity, and laboratory-based imaging for physical specimens and samples in the NEON biorepository. Through its data science-literate staff and user community, NEON has a unique role to play in supporting the growth of such automated biodiversity survey methods, as well as demonstrating their ability to help answer key ecological questions that cannot be answered at the more limited spatiotemporal scales of human-driven surveys

Representing kidney development using the gene ontology.

Gene Ontology (GO) provides dynamic controlled vocabularies to aid in the description of the functional biological attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). Here we describe collaboration between the renal biomedical research community and the GO Consortium to improve the quality and quantity of GO terms describing renal development. In the associated annotation activity, the new and revised terms were associated with gene products involved in renal development and function. This project resulted in a total of 522 GO terms being added to the ontology and the creation of approximately 9,600 kidney-related GO term associations to 940 UniProt Knowledgebase (UniProtKB) entries, covering 66 taxonomic groups. We demonstrate the impact of these improvements on the interpretation of GO term analyses performed on genes differentially expressed in kidney glomeruli affected by diabetic nephropathy. In summary, we have produced a resource that can be utilized in the interpretation of data from small- and large-scale experiments investigating molecular mechanisms of kidney function and development and thereby help towards alleviating renal disease

Sleep disturbance in dementia or mild cognitive impairment: a realist review of general practice

Background: Sleep disturbance (SD) is a prevalent condition among people living with dementia (PLwD) or mild cognitive impairment (MCI). Its assessment and management within primary care is complex due to the comorbidities, older age and cognitive impairment typical of this patient group. Aim: This study aimed to explore how primary care clinicians assess, understand, and manage SD for PLwD or MCI; if and why such initiatives work; and how people and their carers experience SD and its treatment. Design and setting: A realist review of existing literature was conducted in 2022. Methods: Six bibliographic databases were searched. Context-Mechanism-Outcome Configurations (CMOCs) were developed and refined. Results: Sixty records were included from 1,869 retrieved hits and 19 CMOCs were developed. Low awareness of and confidence in the treatment of SD among primary care clinicians and service users, combined with time and resource constraints, meant that identifying SD was difficult and not prioritised. Medication was perceived by clinicians and service users as the primary management tool, resulting in inappropriate or long-term prescription. Rigid nursing routines in care homes were reportedly not conducive to good quality sleep. Conclusion: In primary care, SD among PLwD or MCI is not adequately addressed. Over-reliance on medication, under-utilisation of non-pharmacological strategies, and inflexible care home routines were reported due to low confidence and resource constraints. This does not constitute effective and person-centred care. Future work should consider ways to tailor the assessment and management of SD to the needs of individuals and their informal carers without overstretching services

Canine Prostate Cancer Cell Line (Probasco) Produces Osteoblastic Metastases In Vivo

In 2012, over 240,000 men were diagnosed with prostate cancer and over 28,000 died from the disease. Animal models of prostate cancer are vital to understanding its pathogenesis and developing therapeutics. Canine models in particular are useful due to their similarities to late-stage, castration-resistant human disease with osteoblastic bone metastases. This study established and characterized a novel canine prostate cancer cell line that will contribute to the understanding of prostate cancer pathogenesis

A method for increasing expressivity of Gene Ontology annotations using a compositional approach.

BACKGROUND: The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. RESULTS: The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector-target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions. CONCLUSIONS: The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism's gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

BACKGROUND: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. METHODS AND RESULTS: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. CONCLUSIONS: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. Circ Genom Precis Med 2018 Feb; 11(2):e001813

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr