Movement Decisions and Foraging Behaviour in Shoals of Fish The influence of internal and external stimuli

This thesis explores the mechanisms and functions of decision-making in groups, specifically in the context of social foraging in fish shoals. While many animal groups may seem homogeneous to the naked-eye, closer inspection reveals considerable heterogeneity, as they are composed of individuals with different phenotypes and different motivations living in stochastic, complex environments. The question then, is how do individual behavioural decisions change under varying internal and external conditions and what effect does this have on group level decision-making? How do animals address conflicts of interest and competition effects whilst ensuring benefits of group living are maintained? The approach taken in this thesis has been to address these questions from many angles, using a range of freshwater and marine species and employing an array of novel experimental set-ups. Of particular importance has been the utilization of automated, multi agent tracking software, which has allowed for the description of the movement and interaction of individually identified fish at a much finer scale than in the past. This project has direct significance to our understanding of the individual and group dynamics of social species, which is a central theme in behavioural ecology, and will inform researchers in a variety of fields from theoretical biology to sociological studies of human grouping patterns. The inclusion of internal nutritional state and external environmental factors into studies of group movement and decision-making in a foraging context is a practical way of linking the mechanistic forces behind individual behaviour to functional group-level responses. This will help expand our understanding of the evolutionary causes of group living and its ecological consequences, influencing conservation management plans and strategies to improve fisheries and aquacultural practices

Bone biodeterioration-The effect of marine and terrestrial depositional environments on early diagenesis and bone bacterial community.

Bacteria play an important role in the degradation of bone material. However, much remains to be learnt about the structure of their communities in degrading bone, and how the depositional environment influences their diversity throughout the exposure period. We genetically profiled the bacterial community in an experimental series of pig bone fragments (femur and humeri) deposited at different well-defined environments in Denmark. The bacterial community in the bone fragments and surrounding depositional environment were studied over one year, and correlated with the bioerosion damage patterns observed microscopically in the bones. We observed that the bacterial communities within the bones were heavily influenced by the local microbial community, and that the general bone microbial diversity increases with time after exposure. We found the presence of several known collagenase producing bacterial groups, and also observed increases in the relative abundance of several of these in bones with tunneling. We anticipate that future analyses using shotgun metagenomics on this and similar datasets will be able to provide insights into mechanisms of microbiome driven bone degradation

Constraining the Scatter in the Mass-Richness Relation of maxBCG Clusters With Weak Lensing and X-ray Data

We measure the logarithmic scatter in mass at fixed richness for clusters in the maxBCG cluster catalog, an optically selected cluster sample drawn from SDSS imaging data. Our measurement is achieved by demanding consistency between available weak lensing and X-ray measurements of the maxBCG clusters, and the X-ray luminosity--mass relation inferred from the 400d X-ray cluster survey, a flux limited X-ray cluster survey. We find \sigma_{\ln M|N_{200}}=0.45^{+0.20}_{-0.18} (95% CL) at N_{200} ~ 40, where N_{200} is the number of red sequence galaxies in a cluster. As a byproduct of our analysis, we also obtain a constraint on the correlation coefficient between \ln Lx and \ln M at fixed richness, which is best expressed as a lower limit, r_{L,M|N} >= 0.85 (95% CL). This is the first observational constraint placed on a correlation coefficient involving two different cluster mass tracers. We use our results to produce a state of the art estimate of the halo mass function at z=0.23 -- the median redshift of the maxBCG cluster sample -- and find that it is consistent with the WMAP5 cosmology. Both the mass function data and its covariance matrix are presented.Comment: 14 pages, 6 figures, submitted to Ap

The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography

Obtaining accurate and widespread measurements of the vertical structure of the Earths forests has been a longsought goal for the ecological community. Such observations are critical for accurately assessing the existing biomass of forests, and how changes in this biomass caused by human activities or variations in climate may impact atmospheric CO2 concentrations. Additionally, the three-dimensional structure of forests is a key component of habitat quality and biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6 N & S latitude. The GEDI instrument is a geodetic-class laser altimeter/waveform lidar comprised of 3 lasers that produce 8 transects of structural information. Over its two-year nominal lifetime GEDI is anticipated to provide over 10 billion waveforms at a footprint resolution of 25 m. These data will be used to derive a variety of footprint and gridded products, including canopy height, canopy foliar profiles, Leaf Area Index (LAI), sub-canopy topography and biomass. Additionally, data from GEDI are used to demonstrate the efficacy of its measurements for prognostic ecosystem modeling, habit and biodiversity studies, and for fusion using radar and other remote sensing instruments. GEDI science and technology are unique: no other space-based mission has been created that is specifically optimized for retrieving vegetation vertical structure. As such, GEDI promises to advance our understanding of the importance of canopy vertical variations within an ecological paradigm based on structure, composition and function

The clinically led worforcE and activity redesign (CLEAR) programme: a novel data-driven healthcare improvement methodology

Background: The NHS is facing substantial pressures to recover from the COVID-19 pandemic. Optimising workforce modelling is a fundamental component of the recovery plan. The Clinically Lead workforcE and Activity Redesign (CLEAR) programme is a unique methodology that trains clinicians to redesign services, building intrinsic capacity and capability, optimising patient care and minimising the need for costly external consultancy. This paper describes the CLEAR methodology and the evaluation of previous CLEAR projects, including the return on investment. Methods: CLEAR is a work-based learning programme that combines qualitative techniques with data analytics to build innovations and new models of care. It has four unique stages: (1) Clinical engagement- used to gather rich insights from stakeholders and clinicians. (2) Data interrogation- utilising clinical and workforce data for cohort analysis. (3) Innovation- using structured innovation methods to develop new models of care. (4) Recommendations- report writing, impact assessment and presentation of key findings to executive boards. A mixed-methods formative evaluation was carried out on completed projects, which included semi-structured interviews and surveys with CLEAR associates and stakeholders, and a health economic logic model that was developed to link the inputs, processes, outputs and the outcome of CLEAR as well as the potential impacts of the changes identified from the projects. Results: CLEAR provides a more cost-effective delivery of complex change programmes than the alternatives – resulting in a cost saving of £1.90 for every £1 spent independent of implementation success. Results suggest that CLEAR recommendations are more likely to be implemented compared to other complex healthcare interventions because of the levels of clinical engagement and have a potential return on investment of up to £14 over 5 years for every £1 invested. CLEAR appears to have a positive impact on staff retention and wellbeing, the cost of a CLEAR project is covered if one medical consultant remains in post for a year. Conclusions: The unique CLEAR methodology is a clinically effective and cost-effective complex healthcare innovation that optimises workforce and activity design, as well as improving staff retention. Embedding CLEAR methodology in the NHS could have substantial impact on patient care, staff well-being and service provision

Cosmological Constraints from the SDSS maxBCG Cluster Catalog

We use the abundance and weak lensing mass measurements of the SDSS maxBCG cluster catalog to simultaneously constrain cosmology and the richness--mass relation of the clusters. Assuming a flat \LambdaCDM cosmology, we find \sigma_8(\Omega_m/0.25)^{0.41} = 0.832\pm 0.033 after marginalization over all systematics. In common with previous studies, our error budget is dominated by systematic uncertainties, the primary two being the absolute mass scale of the weak lensing masses of the maxBCG clusters, and uncertainty in the scatter of the richness--mass relation. Our constraints are fully consistent with the WMAP five-year data, and in a joint analysis we find \sigma_8=0.807\pm 0.020 and \Omega_m=0.265\pm 0.016, an improvement of nearly a factor of two relative to WMAP5 alone. Our results are also in excellent agreement with and comparable in precision to the latest cosmological constraints from X-ray cluster abundances. The remarkable consistency among these results demonstrates that cluster abundance constraints are not only tight but also robust, and highlight the power of optically-selected cluster samples to produce precision constraints on cosmological parameters.Comment: comments welcom

Precision Measurements of the Cluster Red Sequence using an Error Corrected Gaussian Mixture Model

The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment.Comment: 33 pages, 14 Figures; A typo in Eq.A11 is fixed. The C++/Python codes for ECGMM can be downloaded from: https://sites.google.com/site/jiangangecgmm

Global warming in the pipeline

Improved knowledge of glacial-to-interglacial global temperature change implies that fast-feedback equilibrium climate sensitivity is at least ~4{\deg}C for doubled CO2 (2xCO2), with likely range 3.5-5.5{\deg}C. Greenhouse gas (GHG) climate forcing is 4.1 W/m2 larger in 2021 than in 1750, equivalent to 2xCO2 forcing. Global warming in the pipeline is greater than prior estimates. Eventual global warming due to today's GHG forcing alone -- after slow feedbacks operate -- is about 10{\deg}C. Human-made aerosols are a major climate forcing, mainly via their effect on clouds. We infer from paleoclimate data that aerosol cooling offset GHG warming for several millennia as civilization developed. A hinge-point in global warming occurred in 1970 as increased GHG warming outpaced aerosol cooling, leading to global warming of 0.18{\deg}C per decade. Aerosol cooling is larger than estimated in the current IPCC report, but it has declined since 2010 because of aerosol reductions in China and shipping. Without unprecedented global actions to reduce GHG growth, 2010 could be another hinge point, with global warming in following decades 50-100% greater than in the prior 40 years. The enormity of consequences of warming in the pipeline demands a new approach addressing legacy and future emissions. The essential requirement to "save" young people and future generations is return to Holocene-level global temperature. Three urgently required actions are: 1) a global increasing price on GHG emissions, 2) purposeful intervention to rapidly phase down present massive geoengineering of Earth's climate, and 3) renewed East-West cooperation in a way that accommodates developing world needs.Comment: 48 pages, 27 figures. Correction of formatting error on page 21, which messed up placement of all following figure

GEDI launches a new era of biomass inference from space

Accurate estimation of aboveground forest biomass stocks is required to assess the impacts of land use changes such as deforestation and subsequent regrowth on concentrations of atmospheric CO2. The Global Ecosystem Dynamics Investigation (GEDI) is a lidar mission launched by NASA to the International Space Station in 2018. GEDI was specifically designed to retrieve vegetation structure within a novel, theoretical sampling design that explicitly quantifies biomass and its uncertainty across a variety of spatial scales. In this paper we provide the estimates of pan-tropical and temperate biomass derived from two years of GEDI observations. We present estimates of mean biomass densities at 1 km resolution, as well as estimates aggregated to the national level for every country GEDI observes, and at the sub-national level for the United States. For all estimates we provide the standard error of the mean biomass. These data serve as a baseline for current biomass stocks and their future changes, and the mission's integrated use of formal statistical inference points the way towards the possibility of a new generation of powerful monitoring tools from space