Plastic and evolutionary responses of Chlamydomonas reinhardtii to multiple environmental drivers

In my thesis I present data collected from a long-term selection experiment using the freshwater model organism Chlamydomonas reinhardtii. The selection experiment was designed to disentangle the effects of the number of multiple environmental drivers (MEDs) and the identity of those environmental drivers including high CO2, high temperature, general nutrient depletion, reduced light intensity, reduced phosphate availability, the addition of a herbicide, UV radiation and reduced pH. Using up to eight environmental drivers, I show how simple organisms such as C. reinhardtii evolve in response to MEDs. The first step in this investigation is to examine the short-term response of MEDs. Data collected at the beginning of the selection experiment will provide insight into the early stages of microevolution by investigating key differences in the short-term (plastic) responses to few vs. many MEDs. Here, I focus on how the data collected from the responses to single environmental drivers can help us predict the responses to MEDs by using ecological models (additive, comparative, multiplicative). I show that the short-term plastic responses to single environmental drivers can predict the effect of MEDs using the comparative model because the response is largely driven by the single dominant driver present. I also demonstrate the importance of the number of environmental drivers (NED) for making predictions from the single environmental drivers and show that predictions become more reliable as the NED increases. The results gathered from short-term responses provide evidence that single environmental driver studies are useful for predicting the effect of MEDs. After evolution, I found that the strength of selection varies with NED in a predictable way, which connects the NED to the evolutionary response (size of the direct response) through the strength of selection. Here, I used statistical models to quantify the effect of NED on the evolutionary response to MEDs and then interpreted this by considering the possible genetic constraints on adaptation to MEDs. A subset of populations evolved in environments with five environmental drivers and all populations evolved in the single environmental driver environments are used to examine how adapting to single vs. many environmental drivers affect local adaptation. I examine how populations selected in environments with one environmental driver, five environmental drivers and the evolved control, differ in their response to new environments with the same NED, environments with different NED, and a novel environment. I found that there is a relationship between local adaptation and the strength of selection in the local environment and patterns of local adaptation are affected by the NED of new environments. Lastly, I present the phenotypic consequences of evolution under MEDs. I found that before evolution, measures of chlorophyll content and cell size decline with increasing NED. However, after evolution the relationship between chlorophyll content and cell size with NED is weaker because populations converge on the same phenotypes as they evolve. I also present a case-study of how mass spectrometry methods can be used to better understand underlying molecular mechanisms of two phenotypes (chlorophyll positive and chlorophyll negative cells). This selection experiment is a good example of how laboratory investigations and model organisms can be used to design experiments with enough replication to have high statistical power in order to make more accurate predictions on the short- long-term effects of MEDs. Whilst there have been some studies on the effects of MEDs, these studies rarely have more than three environmental drivers (sometimes 5 environmental drivers) and there are only a handful of long-term MED studies. This study can be used to develop a priori hypotheses for investigating how environmental change will shape natural microbial communities, and is especially useful for organisms where long-term studies with multiple environmental drivers are unfeasible

Seasonal progression and differences in major floral resource use by bees and hoverflies in a diverse horticultural and agricultural landscape revealed by DNA metabarcoding

12 pages, 6 figures, 2 tables, supporting information .-- Data Availability Statement: Raw sequence data are available on the Sequence Read Archive at PRJNA763761. Data available via the Dryad Digital Repository https://doi.org/10.5061/dryad.rjdfn2z9s (Lowe et al., 2022). All code is available at https://github.com/colford/nbgw-plant-illumina-pipelineGardens are important habitats for pollinators, providing floral resources and nesting sites. There are high levels of public support for growing ‘pollinator-friendly’ plants but while plant recommendation lists are available, they are usually inconsistent, poorly supported by scientific research and target a narrow group of pollinators. In order to supply the most appropriate resources, there is a clear need to understand foraging preferences, for a range of pollinators, across the season within horticultural landscapes. Using an innovative DNA metabarcoding approach, we investigated foraging preferences of four groups of pollinators in a large and diverse, horticultural and agricultural landscape, across the flowering season and over 2 years, significantly improving on the spatial and temporal scale that can be achieved using observational studies. Bumblebees, honeybees, non-corbiculate bees and hoverflies visited 191 plant taxa. Overall floral resources were shared between the different types of pollinators, but significant differences were seen between the plants used most abundantly by bees (Hymenoptera) and hoverflies (Diptera). Floral resource use by pollinators is strongly associated with seasonal changes in flowering plants, with pollinators relying on dominant plants found within each season, with preferences consistent across both years. The plants identified were categorised according to their native status to investigate the value of native and non-native plants. The majority of floral resources used were of native and near-native origin, but the proportion of horticultural and naturalised plants increased during late summer and autumn. Synthesis and applications. Plant recommendation lists for pollinators should distinguish between bees and hoverflies and provide evidence-based floral recommendations throughout the year that include native as well as non-native plants for use in the United Kingdom and Northern Europe. Specific management recommendations include reducing mowing to encourage plants such as dandelion Taraxacum officinale and buttercups Ranunculus spp., and reducing scrub management to encourage bramble Rubus fruticosusN.d.V., L.J. and A.L. have received funding through the Welsh Government Rural Communities – Rural Development Programme 2014–2020, which is funded by the European Agricultural Fund for Rural Development and the Welsh Government. A.L. was supported by a Knowledge Economy Skills Scholarship (KESS2), part-funded by the Welsh Government's European Social Fund (ESF). Pollinator icons contained in the plant recommendation list were created by Thomas McBride. We acknowledge the support of the Supercomputing Wales project, which is part-funded by the European Regional Development Fund (ERDF) via Welsh GovernmentWith the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe

Temporal change in floral availability leads to periods of resource limitation and affects diet specificity in a generalist pollinator

Special issue Insights into Ecological & Evolutionary Processes Via Community Metabarcoding.-- 14 pages, 4 figures, 2 tables, supporting Information https://doi.org/10.1111/mec.16719.-- Data Availability Statement: Raw sequence data can be obtained from the Sequence Read Archive (SRA) accession no. PRJNA749263. Code for the bioinformatic pipeline to process raw sequence data is available at https://github.com/colford/nbgw-plant-illumina-pipeline. Floral survey data, processed sequence data and code for data handling and statistical analysis are available in Dryad at https://doi.org/10.5061/dryad.8w9ghx3qrGeneralist species are core components of ecological networks and crucial for the maintenance of biodiversity. Generalist species and networks are expected to be more resilient, and therefore understanding the dynamics of specialization and generalization in ecological networks is a key focus in a time of rapid global change. Whilst diet generalization is frequently studied, our understanding of how it changes over time is limited. Here we explore temporal variation in diet specificity in the honeybee (Apis mellifera), using pollen DNA metabarcoding of honey samples, through the foraging season, over two years. We find that, overall, honeybees are generalists that visit a wide range of plants, but there is temporal variation in the degree of specialization. Temporal specialization of honeybee colonies corresponds to periods of resource limitation, identified as a lack of honey stores. Honeybees experience a lack of preferred resources in June when switching from flowering trees in spring to shrubs and herbs in summer. Investigating temporal patterns in specialization can identify periods of resource limitation that may lead to species and network vulnerability. Diet specificity must therefore be explored at different temporal scales in order to fully understand species and network stability in the face of ecological changeN.dV., L.J. and A.L. received funding through the Welsh Government Rural Communities – Rural Development Programme 2014–2020, which is funded by the European Agricultural Fund for Rural Development and the Welsh Government. A.L. was supported by a Knowledge Economy Skills Scholarship (KESS2), part funded by the Welsh Government's European Social Fund (ESF)With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe

Shifts in honeybee foraging reveal historical changes in floral resources

Decreasing floral resources as a result of habitat loss is one of the key factors in the decline of pollinating insects worldwide. Understanding which plants pollinators use is vital to inform the provision of appropriate floral resources to help prevent pollinator loss. Using a globally important pollinator, the honeybee, we show how changes in agricultural intensification, crop use and the spread of invasive species, have altered the nectar and pollen sources available in the UK. Using DNA metabarcoding, we analysed 441 honey samples from 2017 and compared these to a nationwide survey of honey samples from 1952. We reveal that shifts in major plants foraged by honeybees are driven by changes in the availability of these plants within the landscape. Improved grasslands are the most widespread habitat type in the UK, and management changes within this habitat have the greatest potential to increase floral resource availability

Ocean acidification increases iodine accumulation in kelp-based coastal food webs

Kelp are main iodine accumulators in the ocean, and their growth and photosynthesis are likely to benefit from elevated seawater CO2 levels due to ocean acidification. However, there are currently no data on the effects of ocean acidification on iodine metabolism in kelp. As key primary producers in coastal ecosystems worldwide, any change in their iodine metabolism caused by climate change will potentially have important consequences for global geochemical cycles of iodine, including iodine levels of coastal food webs that underpin the nutrition of billions of humans around the world. Here, we found that elevated pCO2 enhanced growth and increased iodine accumulation not only in the model kelp Saccharina japonica using both short‐term laboratory experiment and long‐term in situ mesocosms, but also in several other edible and ecologically significant seaweeds using long‐term in situ mesocosms. Transcriptomic and proteomic analysis of S. japonica revealed that most vanadium‐dependent haloperoxidase genes involved in iodine efflux during oxidative stress are down‐regulated under increasing pCO2, suggesting that ocean acidification alleviates oxidative stress in kelp, which might contribute to their enhanced growth. When consumed by abalone (Haliotis discus), elevated iodine concentrations in S. japonica caused increased iodine accumulation in abalone, accompanied by reduced synthesis of thyroid hormones. Thus, our results suggest that kelp will benefit from ocean acidification by a reduction in environmental stress however, iodine levels in kelp‐based coastal food webs will increase, with potential impacts on biogeochemical cycles of iodine in coastal ecosystems

Elevated CO2 reduces copper accumulation and toxicity in the diatom Thalassiosira pseudonana

The projected ocean acidification (OA) associated with increasing atmospheric CO2 alters seawater chemistry and hence the bio-toxicity of metal ions. However, it is still unclear how OA might affect the long-term resilience of globally important marine microalgae to anthropogenic metal stress. To explore the effect of increasing pCO2 on copper metabolism in the diatom Thalassiosira pseudonana (CCMP 1335), we employed an integrated eco-physiological, analytical chemistry, and transcriptomic approach to clarify the effect of increasing pCO2 on copper metabolism of Thalassiosira pseudonana across different temporal (short-term vs. long-term) and spatial (indoor laboratory experiments vs. outdoor mesocosms experiments) scales. We found that increasing pCO2 (1,000 and 2,000 μatm) promoted growth and photosynthesis, but decreased copper accumulation and alleviated its bio-toxicity to T. pseudonana. Transcriptomics results indicated that T. pseudonana altered the copper detoxification strategy under OA by decreasing copper uptake and enhancing copper-thiol complexation and copper efflux. Biochemical analysis further showed that the activities of the antioxidant enzymes glutathione peroxidase (GPX), catalase (CAT), and phytochelatin synthetase (PCS) were enhanced to mitigate oxidative damage of copper stress under elevated CO2. Our results provide a basis for a better understanding of the bioremediation capacity of marine primary producers, which may have profound effect on the security of seafood quality and marine ecosystem sustainability under further climate change

The intrinsic predictability of ecological time series and its potential to guide forecasting

Successfully predicting the future states of systems that are complex, stochastic, and potentially chaotic is a major challenge. Model forecasting error (FE) is the usual measure of success; however model predictions provide no insights into the potential for improvement. In short, the realized predictability of a specific model is uninformative about whether the system is inherently predictable or whether the chosen model is a poor match for the system and our observations thereof. Ideally, model proficiency would be judged with respect to the systems’ intrinsic predictability, the highest achievable predictability given the degree to which system dynamics are the result of deterministic vs. stochastic processes. Intrinsic predictability may be quantified with permutation entropy (PE), a model‐free, information‐theoretic measure of the complexity of a time series. By means of simulations, we show that a correlation exists between estimated PE and FE and show how stochasticity, process error, and chaotic dynamics affect the relationship. This relationship is verified for a data set of 461 empirical ecological time series. We show how deviations from the expected PE–FE relationship are related to covariates of data quality and the nonlinearity of ecological dynamics. These results demonstrate a theoretically grounded basis for a model‐free evaluation of a system's intrinsic predictability. Identifying the gap between the intrinsic and realized predictability of time series will enable researchers to understand whether forecasting proficiency is limited by the quality and quantity of their data or the ability of the chosen forecasting model to explain the data. Intrinsic predictability also provides a model‐free baseline of forecasting proficiency against which modeling efforts can be evaluated

Evolutionary consequences of multidriver environmental change in an aquatic primary producer

Climate change is altering aquatic environments in a complex way, and simultaneous shifts in many properties will drive evolutionary responses in primary producers at the base of both freshwater and marine ecosystems. So far, evolutionary studies have shown how changes in environmental drivers, either alone or in pairs, affect the evolution of growth and other traits in primary producers. Here, we evolve a primary producer in 96 unique environments with different combinations of between one and eight environmental drivers to understand how evolutionary responses to environmental change depend on the identity and number of drivers. Even in multidriver environments, only a few dominant drivers explain most of the evolutionary changes in population growth rates. Most populations converge on the same growth rate by the end of the evolution experiment. However, populations adapt more when these dominant drivers occur in the presence of other drivers. This is due to an increase in the intensity of selection in environments with more drivers, which are more likely to include dominant drivers. Concurrently, many of the trait changes that occur during the initial short-term response to both single and multidriver environmental change revert after about 450 generations of evolution. In future aquatic environments, populations will encounter differing combinations of drivers and intensities of selection, which will alter the adaptive potential of primary producers. Accurately gauging the intensity of selection on key primary producers will help in predicting population size and trait evolution at the base of aquatic food webs

Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health

This is the final version. Available on open access from Elsevier via the DOI in this recordData and Code Availability Statement: Data collected using qPCR is archived and on NERC EIDC [https://doi.org/10.5285/28208be4-0163-45e6-912c-2db205126925]. Standard pollen monitoring ‘count’ data were sourced from the MEDMI database, with the exception of data from Bangor which were produced as part of the present study and are available on request. Prescribing datasets are publicly available, as are weather, air pollution, deprivation (IMD) and rural-urban category data. Hospital episode statistics (HES) datasets are sensitive, individual-level health data, which are subject to strict privacy regulations and are not publicly available. The study did not generate any unique codeGrass (Poaceae) pollen is the most important outdoor aeroallergen, exacerbating a range of respiratory conditions, including allergic asthma and rhinitis (‘hay fever’). Understanding the relationships between respiratory diseases and airborne grass pollen with view to improving forecasting has broad public health and socioeconomic relevance. It is estimated that there are over 400 million people with allergic rhinitis and over 300 million with asthma, globally, often comorbidly . In the UK, allergic asthma has an annual cost of around US$ 2.8 billion (2017). The relative contributions of the >11,000 (worldwide) grass species to respiratory health have been unresolved, as grass pollen cannot be readily discriminated using standard microscopy. Instead, here we used novel environmental DNA (eDNA) sampling and quantitative PCR (qPCR) , to measure the relative abundances of airborne pollen from common grass species, during two grass pollen seasons (2016 and 2017), across the UK. We quantitatively demonstrate discrete spatiotemporal patterns in airborne grass pollen assemblages. Using a series of generalised additive models (GAMs), we explore the relationship between the incidences of airborne pollen and severe asthma exacerbations (sub-weekly) and prescribing rates of drugs for respiratory allergies (monthly). Our results indicate that a subset of grass species may have disproportionate influence on these population-scale respiratory health responses during peak grass pollen concentrations. The work demonstrates the need for sensitive and detailed biomonitoring of harmful aeroallergens in order to investigate and mitigate their impacts on human health.Natural Environment Research Council (NERC)National Institute for Health Research (NIHR)Public Health EnglandUniversity of ExeterUniversity College LondonMet Offic

Evaluating the Impact of a ‘Virtual Clinic’ on Patient Experience, Personal and Provider Costs of Care in Urinary Incontinence: A Randomised Controlled Trial.

Objective: To evaluate the impact of using a ‘virtual clinic’ on patient experience and cost in the care of women with urinary incontinence. Materials and Methods: Women, aged > 18 years referred to a urogynaecology unit were randomised to either (1) A Standard Clinic or (2) A Virtual Clinic. Both groups completed a validated, web-based interactive, patient-reported outome measure (ePAQ-Pelvic Floor), in advance of their appointment followed by either a telephone consultation (Virtual Clinic) or face-to-face consultation (Standard Care). The primary outcome was the mean ‘short-term outcome scale’ score on the Patient Experience Questionnaire (PEQ). Secondary Outcome Measures included the other domains of the PEQ (Communications, Emotions and Barriers), Client Satisfaction Questionnaire (CSQ), Short-Form 12 (SF-12), personal, societal and NHS costs. Results: 195 women were randomised: 98 received the intervention and 97 received standard care. The primary outcome showed a non-significant difference between the two study arms. No significant differences were also observed on the CSQ and SF-12. However, the intervention group showed significantly higher PEQ domain scores for Communications, Emotions and Barriers (including following adjustment for age and parity). Whilst standard care was overall more cost-effective, this was minimal (£38.04). The virtual clinic also significantly reduced consultation time (10.94 minutes, compared with a mean duration of 25.9 minutes respectively) and consultation costs compared to usual care (£31.75 versus £72.17 respectively), thus presenting potential cost-savings in out-patient management. Conclusions: The virtual clinical had no impact on the short-term dimension of the PEQ and overall was not as cost-effective as standard care, due to greater clinic re-attendances in this group. In the virtual clinic group, consultation times were briefer, communication experience was enhanced and personal costs lower. For medical conditions of a sensitive or intimate nature, a virtual clinic has potential to support patients to communicate with health professionals about their condition