Allometric relationships of ecologically important Antarctic and Arctic zooplankton and fish species

Allometric relationships between body properties of animals are useful for a wide variety of purposes, such as estimation of biomass, growth, population structure, bioenergetic modelling and carbon flux studies. This study summarizes allometric relationships of zooplankton and nekton species that play major roles in polar marine food webs. Measurements were performed on 639 individuals of 15 species sampled during three expeditions in the Southern Ocean (winter and summer) and 2374 individuals of 14 species sampled during three expeditions in the Arctic Ocean (spring and summer). The information provided by this study fills current knowledge gaps on relationships between length and wet/dry mass of understudied animals, such as various gelatinous zooplankton, and of animals from understudied seasons and maturity stages, for example, for the krill Thysanoessa macrura and larval Euphausia superba caught in winter. Comparisons show that there is intra-specific variation in length–mass relationships of several species depending on season, e.g. for the amphipod Themisto libellula. To investigate the potential use of generalized regression models, comparisons between sexes, maturity stages or age classes were performed and are discussed, such as for the several krill species and T. libellula. Regression model comparisons on age classes of the fish E. antarctica were inconclusive about their general use. Other allometric measurements performed on carapaces, eyes, heads, telsons, tails and otoliths provided models that proved to be useful for estimating length or mass in, e.g. diet studies. In some cases, the suitability of these models may depend on species or developmental stages.

Composition of nests constructed by species in the Motacillidae, Sylviidae and Prunellidae

Bird nests can be complex bio-engineered structures constructed from a range of materials to provide a site for incubation, and in many species chick rearing. Reports of the materials used in nest walls and cup linings are typically qualitative and do not assist in understanding the functional properties of the structure as a whole. This paper provides size and composition data for nests from four species of the Motacillidae family: the meadow pipit ( Anthus pratensis), pied wagtail ( Motacilla alba), grey wagtail ( Motacilla cinerea), and the yellow wagtail ( Motacilla flava), three species of the Sylviidae family: willow warbler ( Phylloscopus trochilus), Eurasian reed warbler ( Acrocephalus scirpaceus) and Eurasian blackcap ( Sylvia atricapilla), and the dunnock ( Prunella modularis) of the Prunellidae family. Three hypotheses were tested: do nest dimensions correlate with body mass? Is it possible to distinguish among species based on their nest composition; and for individual species? Is it possible to distinguish between the cup lining and outer nest wall based on the materials used in construction? Nest composition and size varied among species although the degree of intra-specific variation was different. Size of a nest was unrelated to average female adult body mass. Composition relied on similar types of materials but in differing quantities between species. It was possible to distinguish among species in terms of nest construction, and between the cup lining and the outer nest, on the basis of at least one of the component materials. By providing quantitative data on composition, it may be possible in the future to understand better the structural, insulative and hydrological properties of the nest. Such information will be invaluable as we begin to develop an understanding of the factors that have driven evolution of nest architecture.

A Modified TurboID Approach Identifies Tissue-Specific Centriolar Components In C. elegans

Proximity-dependent labeling approaches such as BioID have been a great boon to studies of protein-protein interactions in the context of cytoskeletal structures such as centrosomes which are poorly amenable to traditional biochemical approaches like immunoprecipitation and tandem affinity purification. Yet, these methods have so far not been applied extensively to invertebrate experimental models such as C. elegans given the long labeling times required for the original promiscuous biotin ligase variant BirA*. Here, we show that the recently developed variant TurboID successfully probes the interactomes of both stably associated (SPD-5) and dynamically localized (PLK-1) centrosomal components. We further develop an indirect proximity labeling method employing a GFP nanobody- TurboID fusion, which allows the identification of protein interactors in a tissue-specific manner in the context of the whole animal. Critically, this approach utilizes available endogenous GFP fusions, avoiding the need to generate multiple additional strains for each target protein and the potential complications associated with overexpressing the protein from transgenes. Using this method, we identify homologs of two highly conserved centriolar components, Cep97 and Bld10/Cep135, which are present in various somatic tissues of the worm. Surprisingly, neither protein is expressed in early embryos, likely explaining why these proteins have escaped attention until now. Our work expands the experimental repertoire for C. elegans and opens the door for further studies of tissue-specific variation in centrosome architecture.

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data

Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis-REs. For this purpose, we developed a deep learning framework (CoRE-ATAC) with novel data encoders that integrate DNA sequence (reference or personal genotypes) with ATAC-seq cut sites and read pileups. CoRE-ATAC was trained on 4 cell types (n = 6 samples/replicates) and accurately predicted known cis-RE functions from 7 cell types (n = 40 samples) that were not used in model training (mean average precision = 0.80, mean F1 score = 0.70). CoRE-ATAC enhancer predictions from 19 human islet samples coincided with genetically modulated gain/loss of enhancer activity, which was confirmed by massively parallel reporter assays (MPRAs). Finally, CoRE-ATAC effectively inferred cis-RE function from aggregate single nucleus ATAC-seq (snATAC) data from human blood-derived immune cells that overlapped with known functional annotations in sorted immune cells, which established the efficacy of these models to study cis-RE functions of rare cellswithout the need for cell sorting. ATAC-seq maps from primary human cells reveal individual- and cell-specific variation in cis-RE activity. CoRE-ATAC increases the functional resolution of these maps, a critical step for studying regulatory disruptions behind diseases.

Inter-Specific Variation in the Potential for Upland Rush Management Advocated by Agri-Environment Schemes to Increase Breeding Wader Densities

Encroachment of rush Juncus spp. in the United Kingdom uplands poses a threat to declining wader populations due to taller, denser swards that can limit foraging and breeding habitat quality for some species. Rush management via cutting, implemented through agri-environment schemes (AESs), could thus increase wader abundance, but there is insufficient assessment and understanding of how rush management influences upland waders. Across two upland regions of England [South West Peak (SWP) and Geltsdale nature reserve, Cumbria], we surveyed waders over four visits in fields where rush was managed according to AES prescriptions (treatment; n = 21) and fields without rush management that were otherwise ecologically similar (control; n = 22) to assess how the densities of breeding wader pairs respond to rush management in the short-term. We find evidence for regional variation in the response of waders to rush management, with densities of Common Snipe Gallinago gallinago significantly higher in treatment than control fields in the SWP, but not Geltsdale. There were no statistically significant responses to treatment on densities of Eurasian Curlew Numenius arquata or Northern Lapwing Vanellus vanellus. The 95% confidence intervals for the treatment parameter estimates suggest that this may be due to limited statistical power in the case of Lapwing. For Curlew, however, any potential increases in densities are negligible. There was no evidence that variation in rush cover, which ranged from 10 to 70%, influenced densities of any of our three focal species. Our results suggest that rush management through AES prescriptions delivered in isolation of other interventions may not lead to general increases in breeding wader densities in the short-term, but benefits may arise in some situations due to regional and inter-specific variation in effectiveness. Rush management supported with interventions that improve soil conditions and thus food availability, or reduce predation pressure, may enable AES rush management to generate benefits. Additional research is required to maximise the potential benefits of rush management for each species through the development of prescriptions that tailor to individual species’ optimum sward structure.

New Interval-Specific Phylodynamic Models Improve Inference of the Geographic History of Disease Outbreaks

Phylodynamic methods reveal the spatial and temporal dynamics of viral geographic spread, and have featured prominently in studies of the COVID-19 pandemic. Virtually all previous studies are based on phylodynamic models that assume—despite direct and compelling evidence to the contrary—that rates of viral geographic dispersal are constant through time. Here, we: (1) extend phylodynamic models to allow both the average and relative rates of viral dispersal to vary independently between pre-specified time intervals; (2) implement methods to infer the number and timing of viral dispersal events between areas; and (3) develop statistics to assess the absolute fit of phylodynamic models to empirical datasets. We first validate our new methods using analyses of simulated data, and then apply them to a SARS-CoV-2 dataset from the early phase of the COVID-19 pandemic. We show that: (1) under simulation, failure to accommodate interval-specific variation in the study data will severely bias parameter estimates; (2) in practice, our interval-specific phylodynamic models can significantly improve the relative and absolute fit to empirical data; and (3) the increased realism of our interval-specific phylodynamic models provides qualitatively different inferences regarding key aspects of the COVID-19 pandemic—revealing significant temporal variation in global viral dispersal rates, viral dispersal routes, and number of viral dispersal events between areas—and alters interpretations regarding the efficacy of intervention measures to mitigate the pandemic.

Seasonal and age-specific dynamics of the Griffon Vulture’s home range and movements in the Eastern Rhodopes

The spatial ecology of the Eurasian Griffon Vulture (Gyps fulvus) has been a subject of scientific interest for long due to its conservation status, critical ecosystem role, gregarious lifestyle and complex foraging behavior. The trans-border Eastern Rhodope Mountain in Bulgaria and Greece holds an increasing population of the species and one of the largest on the Balkan Peninsula. We used high-frequency GPS data from 13 Griffon Vultures from this population to study their movements, home range size and its seasonal or age specific dynamics. The overall foraging home range (95% kernel) was 3,204 km2 and the core area of activity (50% kernel) was 256.5 km2. We found high seasonal variation of the home range size. Vultures were foraging over larger areas in the summer and spring but their activity was limited to four times smaller areas in winter. We found no age specific variation in the home range sizes but the non-adult vultures showed tendency to conduct exploratory movements far from the breeding colony. Our results can be used for planning conservation efforts in the areas of high importance for the species.

Two New Species of the Genus Longipedia Claus, 1863 (Copepoda: Harpacticoida: Longipediidae) from Korea, with an Update and a Key to Species

Benthic harpacticoids were collected from Korean waters. Two species were identified as members of the genus Longipedia Claus, 1863, because they have an extremely elongated distal segment of the P2 endopod. Longipedia koreana sp. nov. is morphologically most closely related to L. nichollsi Wells, 1980 and L. scotti Sars, 1903, but it can clearly be distinguished from both species based on the following morphological characteristics: P1 coxa with strong spinules near the outer margin and the distal element being much bigger than the proximal elements, P2 coxa with a small inner seta on the anterior surface, P4 exopod first segment without an inner element, and the P5 with a rectangular exopod (more than 3.5 times as long as wide). L. ulleungensis sp. nov. is similar to L. brevispinosa Gurney, 1927, L. spinulosa Itô, 1981, and L. weberi Scott A., 1909. However, L. ulleungensis sp. nov. is characterized by the P2 coxa with a reduced inner seta, the P4 exopod second segment without an inner seta, and the anal operculum with a long median projection, a single spine, and a group of outer spines on each side. In a molecular analysis using the mitochondrial cytochrome c oxidase subunit I (COI) and 18S ribosomal RNA (18S rRNA) genes, the inter-specific variation was 22.525–23.102% and 1.325–1.382% of COI and 18S rRNA between the two new species, respectively. A key to the family Longipediidae is provided herein.

Adapting a Hyper-heuristic to Respond to Scalability Issues in Combinatorial Optimisation

<p>The development of a heuristic to solve an optimisation problem in a new domain, or a specific variation of an existing problem domain, is often beyond the means of many smaller businesses. This is largely due to the task normally needing to be assigned to a human expert, and such experts tend to be scarce and expensive. One of the aims of hyper-heuristic research is to automate all or part of the heuristic development process and thereby bring the generation of new heuristics within the means of more organisations. A second aim of hyper-heuristic research is to ensure that the process by which a domain specific heuristic is developed is itself independent of the problem domain. This enables a hyper-heuristic to exist and operate above the combinatorial optimisation problem “domain barrier” and generalise across different problem domains. A common issue with heuristic development is that a heuristic is often designed or evolved using small size problem instances and then assumed to perform well on larger problem instances. The goal of this thesis is to extend current hyper-heuristic research towards answering the question: How can a hyper-heuristic efficiently and effectively adapt the selection, generation and manipulation of domain specific heuristics as you move from small size and/or narrow domain problems to larger size and/or wider domain problems? In other words, how can different hyperheuristics respond to scalability issues? Each hyper-heuristic has its own strengths and weaknesses. In the context of hyper-heuristic research, this thesis contributes towards understanding scalability issues by firstly developing a compact and effective heuristic that can be applied to other problem instances of differing sizes in a compatible problem domain. We construct a hyper-heuristic for the Capacitated Vehicle Routing Problem domain to establish whether a heuristic for a specific problem domain can be developed which is compact and easy to interpret. The results show that generation of a simple but effective heuristic is possible. Secondly we develop two different types of hyper-heuristic and compare their performance across different combinatorial optimisation problem domains. We construct and compare simplified versions of two existing hyper-heuristics (adaptive and grammar-based), and analyse how each handles the trade-off between computation speed and quality of the solution. The performance of the two hyper-heuristics are tested on seven different problem domains compatible with the HyFlex (Hyper-heuristic Flexible) framework. The results indicate that the adaptive hyper-heuristic is able to deliver solutions of a pre-defined quality in a shorter computational time than the grammar-based hyper-heuristic. Thirdly we investigate how the adaptive hyper-heuristic developed in the second stage of this thesis can respond to problem instances of the same size, but containing different features and complexity. We investigate how, with minimal knowledge about the problem domain and features of the instance being worked on, a hyper-heuristic can modify its processes to respond to problem instances containing different features and problem domains of different complexity. In this stage we allow the adaptive hyper-heuristic to select alternative vectors for the selection of problem domain operators, and acceptance criteria used to determine whether solutions should be retained or discarded. We identify a consistent difference between the best performing pairings of selection vector and acceptance criteria, and those pairings which perform poorly. This thesis shows that hyper-heuristics can respond to scalability issues, although not all do so with equal ease. The flexibility of an adaptive hyper-heuristic enables it to perform faster than the more rigid grammar-based hyper-heuristic, but at the expense of losing a reusable heuristic.</p>

Adapting a Hyper-heuristic to Respond to Scalability Issues in Combinatorial Optimisation

<p>The development of a heuristic to solve an optimisation problem in a new domain, or a specific variation of an existing problem domain, is often beyond the means of many smaller businesses. This is largely due to the task normally needing to be assigned to a human expert, and such experts tend to be scarce and expensive. One of the aims of hyper-heuristic research is to automate all or part of the heuristic development process and thereby bring the generation of new heuristics within the means of more organisations. A second aim of hyper-heuristic research is to ensure that the process by which a domain specific heuristic is developed is itself independent of the problem domain. This enables a hyper-heuristic to exist and operate above the combinatorial optimisation problem “domain barrier” and generalise across different problem domains. A common issue with heuristic development is that a heuristic is often designed or evolved using small size problem instances and then assumed to perform well on larger problem instances. The goal of this thesis is to extend current hyper-heuristic research towards answering the question: How can a hyper-heuristic efficiently and effectively adapt the selection, generation and manipulation of domain specific heuristics as you move from small size and/or narrow domain problems to larger size and/or wider domain problems? In other words, how can different hyperheuristics respond to scalability issues? Each hyper-heuristic has its own strengths and weaknesses. In the context of hyper-heuristic research, this thesis contributes towards understanding scalability issues by firstly developing a compact and effective heuristic that can be applied to other problem instances of differing sizes in a compatible problem domain. We construct a hyper-heuristic for the Capacitated Vehicle Routing Problem domain to establish whether a heuristic for a specific problem domain can be developed which is compact and easy to interpret. The results show that generation of a simple but effective heuristic is possible. Secondly we develop two different types of hyper-heuristic and compare their performance across different combinatorial optimisation problem domains. We construct and compare simplified versions of two existing hyper-heuristics (adaptive and grammar-based), and analyse how each handles the trade-off between computation speed and quality of the solution. The performance of the two hyper-heuristics are tested on seven different problem domains compatible with the HyFlex (Hyper-heuristic Flexible) framework. The results indicate that the adaptive hyper-heuristic is able to deliver solutions of a pre-defined quality in a shorter computational time than the grammar-based hyper-heuristic. Thirdly we investigate how the adaptive hyper-heuristic developed in the second stage of this thesis can respond to problem instances of the same size, but containing different features and complexity. We investigate how, with minimal knowledge about the problem domain and features of the instance being worked on, a hyper-heuristic can modify its processes to respond to problem instances containing different features and problem domains of different complexity. In this stage we allow the adaptive hyper-heuristic to select alternative vectors for the selection of problem domain operators, and acceptance criteria used to determine whether solutions should be retained or discarded. We identify a consistent difference between the best performing pairings of selection vector and acceptance criteria, and those pairings which perform poorly. This thesis shows that hyper-heuristics can respond to scalability issues, although not all do so with equal ease. The flexibility of an adaptive hyper-heuristic enables it to perform faster than the more rigid grammar-based hyper-heuristic, but at the expense of losing a reusable heuristic.</p>