A quantitative narrative on movement, disease and patch exploitation in nesting agent groups

Abstract Animal relocation data has recently become considerably more ubiquitous, finely structured (collection frequencies measured in minutes) and co-variate rich (physiology of individuals, environmental and landscape information, and accelerometer data). To better understand the impacts of ecological interactions, individual movement and disease on global change ecology, including wildlife management and conservation, it is important to have simulators that will provide demographic, movement, and epidemiology null models against which to compare patterns observed in empirical systems. Such models may then be used to develop quantitative narratives that enhance our intuition and understanding of the relationship between population structure and generative processes: in essence, along with empirical and experimental narratives, quantitative narratives are used to advance ecological epistemology. Here we describe a simulator that accounts for the influence of consumer-resource interactions, existence of social groups anchored around a central location, territoriality, group-switching behavior, and disease dynamics on population size. We use this simulator to develop new and reinforce existing quantitative narratives and point out areas for future study. Author summary The health and viability of species are of considerable concern to all nature lovers. Population models are central to our efforts to assess the numerical and ecological status of species and threats posed by climate change. Models, however, are crude caricatures of complex ecological systems. So how do we construct reliable assessment models able to capture processes essential to predicating the impacts of global change on population viability without getting tied up in their vast complexities? We broach this question and demonstrate how models focusing at the level of the individual (i.e., agent-based models) are tools for developing robust, narratives to augment narratives arising purely from empirical data sources and experimental outcomes. We do this in the context of nesting social groups, foraging for food, while exhibiting territoriality and group-switching behavior; and, we evaluate the impact of disease on the viability of such populations

Adequacy of SEIR models when epidemics have spatial structure: Ebola in Sierra Leone.

Dynamic SEIR (Susceptible, Exposed, Infectious, Removed) compartmental models provide a tool for predicting the size and duration of both unfettered and managed outbreaks-the latter in the context of interventions such as case detection, patient isolation, vaccination and treatment. The reliability of this tool depends on the validity of key assumptions that include homogeneity of individuals and spatio-temporal homogeneity. Although the SEIR compartmental framework can easily be extended to include demographic (e.g. age) and additional disease (e.g. healthcare workers) classes, dependence of transmission rates on time, and metapopulation structure, fitting such extended models is hampered by both a proliferation of free parameters and insufficient or inappropriate data. This raises the question of how effective a tool the basic SEIR framework may actually be. We go some way here to answering this question in the context of the 2014-2015 outbreak of Ebola in West Africa by comparing fits of an SEIR time-dependent transmission model to both country- and district-level weekly incidence data. Our novel approach in estimating the effective-size-of-the-populations-at-risk ( Neff) and initial number of exposed individuals ( E0) at both district and country levels, as well as the transmission function parameters, including a time-to-halving-the-force-of-infection ( tf/2) parameter, provides new insights into this Ebola outbreak. It reveals that the estimate R0 ≈ 1.7 from country-level data appears to seriously underestimate R0 ≈ 3.3 - 4.3 obtained from more spatially homogeneous district-level data. Country-level data also overestimate tf/2 ≈ 22 weeks, compared with 8-10 weeks from district-level data. Additionally, estimates for the duration of individual infectiousness is around two weeks from spatially inhomogeneous country-level data compared with 2.4-4.5 weeks from spatially more homogeneous district-level data, which estimates are rather high compared with most values reported in the literature. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'

Simulation and Analysis of Animal Movement Paths using Numerus Model Builder

ABSTRACT Animal movement paths are represented by point-location time series called relocation data. How well such paths can be simulated, when the rules governing movement depend on the internal state of individuals and environmental factors (both local and, when memory is involved, global) remains an open question. To answer this, we formulate and test models able to capture the essential statistics of multiphase versions of such paths (viz., movement-phase-specific step-length and turning-angle means, variances, auto-correlation, and cross correlation values), as well as broad scale movement patterns. The latter may include patchy coverage of the landscape, as well as the existence of home-range boundaries and gravitational centers-of-movement (e.g., centered around nests). Here we present a Numerus Model Builder implementation of two kinds of models: a high-frequency, multi-mode, biased, correlated random walk designed to simulate real movement data at a scale that permits simulation and identification of path segments that range from minutes to days; and a model that uses statistics extracted from relocation data—either empirical or simulated—to construct movement modes and phases at subhourly to daily scales. We evaluate how well our derived statistical movement model captures patterns produced by our more detailed simulation model as a way to evaluate how well derived statistical movement models may capture patterns occurring in empirical data

A Nova Web Application for Population Viability and Sustainable Harvesting Analyses

Population viability analyses are used to assess the probability that a particular population of individuals will persist as a self-reproducing, ecologically viable entity for a specified period of time. Such models are typically cast as Markov processes that may inter alia include demographic structure (e.g. age, stage, sex), ecological processes through the incorporation of density-dependent reproduction or survival functions, viability thresholds that trigger remedial interventions when breached (e.g. removal of individuals to protect environments), metapopulation structure, stocking, harvesting or translocations of the population. These models can also be used to assess the impacts of harvesting strategies when they include population removal options. Here we present a general Nova modeling framework that integrates all of the above features and generates distributions of outcomes through repeated simulations. The framework incorporates the most relevant ecosystem structures, including metapopulation structure with associated connectivity and movement parameters, age/stage class structure with population-specific life history data, demographic and environmental stochasticity components, and management interventions including off-take, translocation, and stocking components. The NOVA PVA model is available as a responsively configured web application that can be run locally in a browser or on high performance computing systems controlled by a browser-based dashboard. In this talk the structure of the model will be discussed and the operation of the web application will be demonstrated

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) family

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) enzymes are secreted, multi-domain matrix-associated zinc metalloendopeptidases that have diverse roles in tissue morphogenesis and patho-physiological remodeling, in inflammation and in vascular biology. The human family includes 19 members that can be sub-grouped on the basis of their known substrates, namely the aggrecanases or proteoglycanases (ADAMTS1, 4, 5, 8, 9, 15 and 20), the procollagen N-propeptidases (ADAMTS2, 3 and 14), the cartilage oligomeric matrix protein-cleaving enzymes (ADAMTS7 and 12), the von-Willebrand Factor proteinase (ADAMTS13) and a group of orphan enzymes (ADAMTS6, 10, 16, 17, 18 and 19). Control of the structure and function of the extracellular matrix (ECM) is a central theme of the biology of the ADAMTS, as exemplified by the actions of the procollagen-N-propeptidases in collagen fibril assembly and of the aggrecanases in the cleavage or modification of ECM proteoglycans. Defects in certain family members give rise to inherited genetic disorders, while the aberrant expression or function of others is associated with arthritis, cancer and cardiovascular disease. In particular, ADAMTS4 and 5 have emerged as therapeutic targets in arthritis. Multiple ADAMTSs from different sub-groupings exert either positive or negative effects on tumorigenesis and metastasis, with both metalloproteinase-dependent and -independent actions known to occur. The basic ADAMTS structure comprises a metalloproteinase catalytic domain and a carboxy-terminal ancillary domain, the latter determining substrate specificity and the localization of the protease and its interaction partners; ancillary domains probably also have independent biological functions. Focusing primarily on the aggrecanases and proteoglycanases, this review provides a perspective on the evolution of the ADAMTS family, their links with developmental and disease mechanisms, and key questions for the future

The ocean sampling day consortium

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits

The Ocean Sampling Day Consortium

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead