Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics
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An updated landslide susceptibility model and a log-Gaussian Cox process extension for Scotland
Get PDFAt the time of its development, GeoSure was created using expert knowledge based on a thorough understanding of the engineering geology of the rocks and soils of Great Britain. The ability to use a data-driven methodology to develop a national-scale landslide susceptibility was not possible due to the relatively small size of the landslide inventory at the time. In the intervening 20 years, the National Landslide Database has grown from around 6000 points to over 18,000 records today and continues to be added to. With the availability of this additional inventory, new data-driven solutions could be utilised. Here, we tested a Bernoulli likelihood model to estimate the probability of debris flow occurrence and a log-Gaussian Cox process model to estimate the rate of debris flow occurrence per slope unit. Scotland was selected as the test site for a preliminary experiment, which could potentially be extended to the whole British landscape in the future. Inference techniques for both of these models are applied within a Bayesian framework. The Bayesian framework can work with the two models as additive structures, which allows for the incorporation of spatial and covariate information in a flexible way. The framework also provides uncertainty estimates with model outcomes. We also explored consideration on how to communicate uncertainty estimates together with model predictions in a way that would ensure an integrated framework for master planners to use with ease, even if administrators do not have a specific statistical background. Interestingly, the spatial predictive patterns obtained do not stray away from those of the previous GeoSure methodology, but rigorous numerical modelling now offers objectivity and a much richer predictive description
The future of algal blooms in lakes globally is in our hands
Get PDFLakes are fundamental to society and nature, yet they are currently exposed to excessive nutrients and climate change, resulting in algal blooms. In the future, this may change, but how and where still needs more scientific attention. Here, we explore future trends in algal blooms in lakes globally for >3,500 ‘representative lakes’ for the year 2050, considering the attribution of both nutrient and climate factors. We soft-coupled a process-based lake ecosystem model (PCLake+) with a watershed nutrient model (MARINA-Multi) to assess trends in algal blooms in terms of the Trophic State Index for chlorophyll-a (TSI-Chla). Globally between 2010 and 2050, we show a rising trend in algal blooms under fossil-fuelled development (TSI-Chla increase in 91% of lakes) and a declining trend under sustainable development (TSI-Chla decrease in 63% of lakes). These changes are significantly attributed to nutrients. While not always significant, climate change attributions point to being unfavourable for lakes in 2050, exacerbating lake water quality. Our study stresses prioritising responsible nutrient and climate management on policy agendas. This implies that the future of algal blooms in lakes is in our hands
Surveying the deep: A review of computer vision in the benthos
Get PDFThe analysis of image data for benthic biodiversity monitoring is now commonplace within the domain of marine ecology. Whilst advances in imaging technologies have allowed for the collection of vast quantities of data, the curation of this has traditionally been performed manually, resulting in a bottleneck whereby data is collected faster than it can be processed. Recent years have seen marine ecologists turn to the domain of computer vision to help automate this curation process. However, as the knowledge required to build such systems spans both domains, there is a high barrier to entry. To help reduce this barrier, this paper aims to provide an introduction to computer vision-based benthic biodiversity monitoring via a comprehensive literature review. To aid ecologists, key computer vision concepts are described and example use-cases highlighted. The major challenges inherent to benthic imagery for computer vision systems are explored, alongside a discussion of how current systems attempt to mitigate against these. To aid computer scientists wishing to enter the domain, an exploration of currently available open-source benthic datasets is also provided. Recommendations for future research are explored, including a move towards human-centric techniques, committing to ablation studies, reaching community agreement on open-source benchmarking datasets, and an increased use of innovative methods to allow for improved answering of key benthic ecology questions
Advancing operational flood forecasting, early warning and risk management with new emerging science: gaps, opportunities and barriers in Kenya
Get PDFKenya and the wider East African region suffer from significant flood risk, as illustrated by major losses of lives, livelihoods and assets in the most recent years. This is likely to increase in future as exposure rises and rainfall intensifies under climate change. Accordingly, flood risk management is a priority action area in Kenya's national climate change adaptation planning. Here, we outline the opportunities and challenges to improve end-to-end flood early warning systems, considering the scientific, technical and institutional/governance dimensions. We demonstrate improvements in rainfall forecasts, river flow, inundation and baseline flood risk information. Notably, East Africa is a ‘sweetspot’ for rainfall predictability at sub-seasonal to seasonal timescales for extending forecast lead times beyond a few days and for ensemble flood forecasting. Further, we demonstrate coupled ensemble flow forecasting, new flood inundation simulation, vulnerability and exposure data to support Impact based Forecasting (IbF). We illustrate these advances in the case of fluvial and urban flooding and reflect on the potential for improved flood preparedness action. However, we note that, unlike for drought, there remains no national flood risk management framework in Kenya and there is need to enhance institutional capacities and arrangements to take full advantage of these scientific advances
Chapter 11 - Southern Annular Mode
No full textThe Southern Annular Mode (SAM) is an important pattern of Southern Hemisphere circulation variability: it accounts for between 15 and 30 or more percent of the total variability of the Southern Hemisphere extratropical circulation on daily to annual time scales and significantly modulates weather variability across the middle and higher latitudes. It is an expression of feedback between the mean westerly flow over the Southern Ocean and its associated storm track. The discovery in the late 1990s of a trend in SAM behavior led to the realization that stratospheric ozone depletion and greenhouse gas increase both influence SAM behavior, and will do through coming decades. This chapter surveys the mechanism of the SAM, the history of our understanding of the SAM, its impacts upon surface climate, and the outlook for the SAM’s future
Drivers of interspecific spatial segregation in two closely-related seabird species at a Pan-Atlantic scale
Get PDFAim: Ecologically similar species living in sympatry are expected to segregate to reduce the effects of competition where re-sources are limiting. Segregation from heterospecifics commonly occurs in space, but it is often unknown whether such segregation has underlying environmental causes. Indeed, species could segregate because of different fundamental environmental requirements (i.e., ‘niche divergence’), because competitive exclusion at sympatric sites can force species to either change the habitat use they would have at allopatric sites (i.e., ‘niche displacement’) or to avoid certain areas, independently of habitat (i.e.,‘spatial avoidance’). Testing these hypotheses requires the comparison between sympatric and allopatric sites. Understanding the competitive mechanisms that underlie patterns of spatial segregation could improve predictions of species responses to environmental change, as competition might exacerbate the effects of environmental change.
Location: North Atlantic and Arctic.
Taxa: Common guillemots Uria aalge and Brünnich's guillemots Uria lomvia
Multi-scale influences on Escherichia coli concentrations in shellfish: from catchment to estuary
Get PDFSustainability of bivalve shellfish farming relies on clean coastal waters, however, high levels of faecal indicator organisms (FIOs, e.g. Escherichia coli) in shellfish results in temporary closure of shellfish harvesting beds to protect human health, but with economic consequences for the shellfish industry. Active Management Systems which can predict FIO contamination may help reduce shellfishery closures. This study evaluated predictors of E. coli concentrations in two shellfish species, the blue mussel (Mytilus edulis) and the Pacific oyster (Crassostrea gigas), at different spatial and temporal scales, within 12 estuaries in England and Wales. We aimed to: (i) identify consistent catchment-scale or within-estuary predictors of elevated E. coli levels in shellfish, (ii) evaluate whether high river flows associated with rainfall events were a significant predictor of shellfish E. coli concentrations, and the time lag between these events and E. coli accumulation, and (iii) whether operation of Combined Sewer Overflows (CSO) is associated with higher E. coli concentrations in shellfish. A cross-catchment analysis gave a good predictive model for contamination management (R2 = 0.514), with positive relationships between E. coli concentrations and river flow (p=0.001), turbidity (p=0.002) and nitrate (p=0.042). No effect was observed for catchment area, the number of point source discharges, or agricultural land use type. 64% of all shellfish beds showed a significant relationship between E. coli and river flow, with typical lag-times of 1-3 days. Detailed analysis of the Conwy estuary indicated that E. coli counts were consistently higher when the CSO had been active the previous week. In conclusion, we demonstrate that real-time river flow and water quality data may be used to predict potential risk of E. coli contamination in shellfish at the catchment level, however, further refinement (coupling to fine-scale hydrodynamic models) is needed to make accurate predictions for individual shellfish beds within estuaries
Interacting impacts of hydrological changes and air temperature warming on lake temperatures highlight the potential for adaptive management
Get PDFGlobally, climate warming is increasing air temperatures and changing river flows, but few studies have explicitly considered the consequences for lake temperatures of these dual effects, or the potential to manage lake inflows to mitigate climate warming impacts. Using a one-dimensional model, we tested the sensitivity of lake temperatures to the separate and interacting effects of changes in air temperature and inflow on a small, short-residence time (annual average ≈ 20 days), temperate lake. Reducing inflow by 70% increased summer lake surface temperatures 1.0–1.2 °C and water column stability by 11–19%, equivalent to the effect of 1.2 °C air temperature warming. Conversely, similar increases in inflow could result in lake summer cooling, sufficient to mitigate 0.75 °C air temperature rise, increasing to more than 1.1 °C if inflow temperature does not rise. We discuss how altering lake inflow volume and temperature could be added to the suite of adaptation measures for lakes
Investigation of the October effect in very low-frequency (VLF) signals
No full textSubionospheric very low-frequency (VLF) radio signals are reflected by free electrons in the ionospheric D-region at about 60–90 km altitude and can propagate over long distances, which makes them useful for monitoring the state of the D-region or perturbations due to solar flares. At the D-region height, the ionosphere is mainly ionized by solar Lyman-α radiation. The reflection characteristics of VLF signals depend on the state and dynamics of the D-region, which is highly influenced by Lyman-α radiation. Although the amplitude of the received terrestrial VLF signal changes as a function of solar zenith angle over the course of the year, the VLF amplitude shows a distinctive sharp decrease around October, which is hence called the “October effect”. This study investigates the occurrence of the October effect and its dependencies on latitude and longitude. We developed a method to detect the occurrence of the October effect in the long-term VLF data and derive key parameters characterizing (start and end date, intensity) the sudden decrease in the signal amplitude. This investigation using a network of VLF stations distributed over low-, middle-, and high-latitude regions shows that the occurrence of the October effect has a clear latitudinal dependency, occurring earlier in high-latitude regions than at midlatitudes. No low-latitude signature is found
The potential for AI to revolutionize conservation: a horizon scan
Get PDFArtificial Intelligence (AI) is an emerging tool that could be leveraged to identify the effective conservation solutions demanded by the urgent biodiversity crisis. We present the results of our horizon scan of AI applications likely to significantly benefit biological conservation. An international panel of conservation scientists and AI experts identified 21 key ideas. These included species recognition to uncover 'dark diversity', multimodal models to improve biodiversity loss predictions, monitoring wildlife trade, and addressing human–wildlife conflict. We consider the potential negative impacts of AI adoption, such as AI colonialism and loss of essential conservation skills, and suggest how the conservation field might adapt to harness the benefits of AI while mitigating its risks
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