Feeding ecology of juvenile Pacific salmon (Oncorhynchus spp.) in a northeast Pacific fjord: diet, availability of zooplankton, selectivity for prey, and potential competition for prey resources

We investigated the feeding ecology of juvenile salmon during the critical early life-history stage of transition from shallow to deep marine waters by sampling two stations (190 m and 60 m deep) in a northeast Pacific fjord (Dabob Bay, WA) between May 1985 and October 1987. Four species of Pacific salmon—Oncorhynchus keta (chum) , O. tshawytscha (Chinook), O. gorbuscha (pink), and O. kisutch (coho)—were examined for stomach contents. Diets of these fishes varied temporally, spatially, and between species, but were dominated by insects, euphausiids, and decapod larvae. Zooplankton assemblages and dry weights differed between stations, and less so between years. Salmon often demonstrated strongly positive or negative selection for specific prey types: copepods were far more abundant in the zooplankton than in the diet, whereas Insecta, Araneae, Cephalapoda, Teleostei, and Ctenophora were more abundant in the diet than in the plankton. Overall diet overlap was highest for Chinook and coho salmon (mean=77.9%)—species that seldom were found together. Chum and Chinook salmon were found together the most frequently, but diet overlap was lower (38.8%) and zooplankton biomass was not correlated with their gut fullness (%body weight). Thus, despite occasional occurrences of significant diet overlap between salmon species, our results indicate that interspecific competition among juvenile salmon does not occur in Dabob Bay

What sets lower limits to phytoplankton stocks in high-nitrate, low-chlorophyll regions of the open ocean?

Phytoplankton biomass in high-nitrate, low-chlorophyll (HNLC) ocean regions exhibits a pronounced stability: variation occurs only within a narrow range of values. The magnitude of this variation has profound ecological and geochemical consequences. While mechanisms believed to set the upper limits to HNLC phytoplankton biomass (iron limitation, microherbivore grazing) have received much recent attention, mechanisms setting the lower limits are largely unknown. The demonstrated importance of planktonic micrograzers, largely protists, in removing phytoplankton biomass in HNLC regions suggests that micrograzer behavioral and physiological capabilities may hold the key. This will be the case at any level of phytoplankton cell division greater than zero, regardless of the extent of growth rate limitation by resource (e.g. iron, light) availability. Indeed, HNLC plankton dynamics models almost universally include several biological responses that set lower phytoplankton biomass limits and confer temporal stability, including substantial feeding thresholds, zero micrograzer metabolic costs, and no micrograzer mortality at low food levels. Laboratory observations of these same biological responses in protist grazers are equivocal. There are no direct observations of substantive feeding thresholds, and many heterotrophic protists exhibit significant rates of respiration and mortality (cell lysis) at very low food levels. We present several candidate explanations for the discrepancy between laboratory observations and model biological 'requirements'. Firstly, laboratory-derived rate measurements may be biased by use of species and prey concentrations that are not representative of HNLC communities. Secondly, model micrograzer features may be a proxy for other stabilizing phenomena such as spatial heterogeneity ('patchiness') or carnivory (top-down control of rnicroherbivores), though a logical analysis indicates that neither is likely to provide robust stabilization of lower phytoplankton biomass limits. Lastly, the highly plastic feeding capabilities of protist grazers, which include switching between phytoplankton and alternative prey such as bacteria, detritus, and other microherbivores, are a probable locus for stabilization of biomass limits. The extent to which such behavioral plasticity functions on the level of individuals or of species assemblages is unknown. We advocate a coupled modeling and experimental approach to further progress in understanding this key feature of HNLC ecosystems.Keywords: Planktonic food webs, Phytoplankton, Microzooplankton, Plankton dynamics models, Feeding behavior, Grazer

New models of health and social care for people in later life:mapping of innovation in services in two regions of the United Kingdom using a mixed method approach

Background:Innovation for reforming health and social care is high on the policy agenda in the United Kingdom in response to the growing needs of an ageing population. However, information about new innovations of care being implemented is sparse. MethodsWe mapped innovations for people in later life in two regions, North East England and South East Scotland. Data collection included discussions with stakeholders (n=51), semi-structured interviews (n=14) and website searches that focused on technology, evaluation and health inequalities. We analysed qualitative data using framework and thematic analyses. Quantitative data were analysed descriptively. Results111 innovations were identified across the two regions. Interviewees reported a wide range of technologies that had been rapidly introduced during the COVID-19 pandemic and many remained in use. Digital exclusion of certain groups of older people was an ongoing concern. Innovations fell into two groups; system-level ones that aimed to alleviate systems pressures such as preventing hospital (re)admissions, and patient-level ones which sought to enhance health and wellbeing directly. Interviewees were aware of the importance of health inequalities but lacked data to monitor the impact of innovations on these, and evaluation was challenging due to lack of time, training, and support. Quantitative findings revealed that two thirds of innovations (n=74, 67%) primarily focused on the system level, whilst a third (n=37, 33%) primarily focused on the patient-level. Overall, over half (n=65, 59%) of innovations involved technologies although relatively few (n=12, 11%) utilised advanced technologies. Very few (n=16, 14%) focused on reducing health inequalities, and only a minority of innovations (n=43, 39%) had undergone evaluation (most of which were conducted by the service providers themselves). ConclusionsWe found a wide range of innovative care services being developed for people in later life, yet alignment with key policy priorities, such as addressing health inequalities, was limited. There was a strong focus on technology, with little consideration for the potential to widen the health inequality gap. The absence of robust evaluation was also a concern as most innovations were implemented without support to monitor effectiveness and/or without plans for sustainability and spread.<br/

8. Remote Sensing Of Vegetation Fires And Its Contribution To A Fire Management Information System

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then precedes a description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate the practical use of remotely sensed fire information. As indicated in previous chapters, fire management usually comprises activities designed to control the frequency, area, intensity or impact of fire. These activities are undertaken in different institutional, economic, social, environmental and geographical contexts, as well as at different scales, from local to national. The range of fire management activities also varies considerably according to the management issues at stake, as well as the available means and capacity to act. Whatever the level, effective fire management requires reliable information upon which to base appropriate decisions and actions. Information will be required at many different stages of this fire management system. To illustrate this, we consider a typical and generic description of a fire management loop , as provided in Figure 8.1. Fire management objectives result from fire related knowledge . For example, they may relate to sound ecological reasons for prescribed burning in a particular land management context, or to frequent, uncontrolled fires threatening valuable natural or human resources. Whatever the issues, appropriate objectives require scientific knowledge (such as fire impact on ecosystems components, such as soil and vegetation), as well as up-to date monitoring information (such as vegetation status, fire locations, land use, socioeconomic context, etc.). Policies, generally at a national and governmental level, provide the official or legal long term framework (e.g. five to ten years) to undertake actions. A proper documentation of different fire issues, and their evolution, will allow their integration into appropriate policies, whether specific to fire management, or complementary to other policies in areas such as forestry, rangeland, biodiversity, land tenure, etc. Strategies are found at all levels of fire management. They provide a shorter-term framework (e.g. one to five years) to prioritise fire management activities. They involve the development of a clear set of objectives and a clear set of activities to achieve these objectives. They may also include research and training inputs required, in order to build capacity and to answer specific questions needed to improve fire management. The chosen strategy will result from a trade-off between priority fire management objectives and the available capacity to act (e.g. institutional framework, budget, staff, etc.), and will lead towards a better allocation of resources for fire management operations to achieve specific objectives. One example in achieving an objective of conserving biotic diversity may be the implementation of a patch-mosaic burning system (Brockett et al., 200 1 ) instead of a prescribed block burning system, based on an assumption that the former should better promote biodiversity in the long-term than the latter (Parr & Brockett, 1999). This strategy requires the implementation of early season fires to reduce the size of later season fires. The knowledge of population movements, new settlements or a coming El Nino season, should help focus the resources usage, as these factors might influence the proportion as well as the locations of area burned. Another strategy may be to prioritise the grading of fire lines earlier than usual based on information on high biomass accumulation. However, whatever the strategies, they need to be based on reliable information

8. Remote Sensing Of Vegetation Fires And Its Contribution To A Fire Management Information System

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then precedes a description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate the practical use of remotely sensed fire information. As indicated in previous chapters, fire management usually comprises activities designed to control the frequency, area, intensity or impact of fire. These activities are undertaken in different institutional, economic, social, environmental and geographical contexts, as well as at different scales, from local to national. The range of fire management activities also varies considerably according to the management issues at stake, as well as the available means and capacity to act. Whatever the level, effective fire management requires reliable information upon which to base appropriate decisions and actions. Information will be required at many different stages of this fire management system. To illustrate this, we consider a typical and generic description of a fire management loop , as provided in Figure 8.1. Fire management objectives result from fire related knowledge . For example, they may relate to sound ecological reasons for prescribed burning in a particular land management context, or to frequent, uncontrolled fires threatening valuable natural or human resources. Whatever the issues, appropriate objectives require scientific knowledge (such as fire impact on ecosystems components, such as soil and vegetation), as well as up-to date monitoring information (such as vegetation status, fire locations, land use, socioeconomic context, etc.). Policies, generally at a national and governmental level, provide the official or legal long term framework (e.g. five to ten years) to undertake actions. A proper documentation of different fire issues, and their evolution, will allow their integration into appropriate policies, whether specific to fire management, or complementary to other policies in areas such as forestry, rangeland, biodiversity, land tenure, etc. Strategies are found at all levels of fire management. They provide a shorter-term framework (e.g. one to five years) to prioritise fire management activities. They involve the development of a clear set of objectives and a clear set of activities to achieve these objectives. They may also include research and training inputs required, in order to build capacity and to answer specific questions needed to improve fire management. The chosen strategy will result from a trade-off between priority fire management objectives and the available capacity to act (e.g. institutional framework, budget, staff, etc.), and will lead towards a better allocation of resources for fire management operations to achieve specific objectives. One example in achieving an objective of conserving biotic diversity may be the implementation of a patch-mosaic burning system (Brockett et al., 200 1 ) instead of a prescribed block burning system, based on an assumption that the former should better promote biodiversity in the long-term than the latter (Parr & Brockett, 1999). This strategy requires the implementation of early season fires to reduce the size of later season fires. The knowledge of population movements, new settlements or a coming El Nino season, should help focus the resources usage, as these factors might influence the proportion as well as the locations of area burned. Another strategy may be to prioritise the grading of fire lines earlier than usual based on information on high biomass accumulation. However, whatever the strategies, they need to be based on reliable information

Distinct tau prion strains propagate in cells and mice and define different tauopathies

Prion-like propagation of tau aggregation might underlie the stereotyped progression of neurodegenerative tauopathies. True prions stably maintain unique conformations (“strains”) in vivo that link structure to patterns of pathology. We now find that tau meets this criterion. Stably expressed tau repeat domain indefinitely propagates distinct amyloid conformations in a clonal fashion in culture. Reintroduction of tau from these lines into naive cells reestablishes identical clones. We produced two strains in vitro that induce distinct pathologies in vivo as determined by successive inoculations into three generations of transgenic mice. Immunopurified tau from these mice recreates the original strains in culture. We used the cell system to isolate tau strains from 29 patients with 5 different tauopathies, finding that different diseases are associated with different sets of strains. Tau thus demonstrates essential characteristics of a prion. This might explain the phenotypic diversity of tauopathies and could enable more effective diagnosis and therapy