Publications by authors named "C Leigh"

95 Publications

SSNdesign-An R package for pseudo-Bayesian optimal and adaptive sampling designs on stream networks.

PLoS One 2020 22;15(9):e0238422. Epub 2020 Sep 22.

Institute for Future Environments, Queensland University of Technology, Brisbane, QLD, Australia.

Streams and rivers are biodiverse and provide valuable ecosystem services. Maintaining these ecosystems is an important task, so organisations often monitor the status and trends in stream condition and biodiversity using field sampling and, more recently, autonomous in-situ sensors. However, data collection is often costly, so effective and efficient survey designs are crucial to maximise information while minimising costs. Geostatistics and optimal and adaptive design theory can be used to optimise the placement of sampling sites in freshwater studies and aquatic monitoring programs. Geostatistical modelling and experimental design on stream networks pose statistical challenges due to the branching structure of the network, flow connectivity and directionality, and differences in flow volume. Geostatistical models for stream network data and their unique features already exist. Some basic theory for experimental design in stream environments has also previously been described. However, open source software that makes these design methods available for aquatic scientists does not yet exist. To address this need, we present SSNdesign, an R package for solving optimal and adaptive design problems on stream networks that integrates with existing open-source software. We demonstrate the mathematical foundations of our approach, and illustrate the functionality of SSNdesign using two case studies involving real data from Queensland, Australia. In both case studies we demonstrate that the optimal or adaptive designs outperform random and spatially balanced survey designs implemented in existing open-source software packages. The SSNdesign package has the potential to boost the efficiency of freshwater monitoring efforts and provide much-needed information for freshwater conservation and management.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238422PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508409PMC
October 2020

Detecting Technical Anomalies in High-Frequency Water-Quality Data Using Artificial Neural Networks.

Environ Sci Technol 2020 11 16;54(21):13719-13730. Epub 2020 Oct 16.

Univ. Pau & Pays de l'Adour E2S UPPALaboratoire des Mathématiques et de leurs applications, CNRS, 64600 Anglet, France.

Anomaly detection (AD) in high-volume environmental data requires one to tackle a series of challenges associated with the typical low frequency of anomalous events, the broad-range of possible anomaly types, and local nonstationary environmental conditions, suggesting the need for flexible statistical methods that are able to cope with unbalanced high-volume data problems. Here, we aimed to detect anomalies caused by technical errors in water-quality (turbidity and conductivity) data collected by automated in situ sensors deployed in contrasting riverine and estuarine environments. We first applied a range of artificial neural networks that differed in both learning method and hyperparameter values, then calibrated models using a Bayesian multiobjective optimization procedure, and selected and evaluated the "best" model for each water-quality variable, environment, and anomaly type. We found that semi-supervised classification was better able to detect sudden spikes, sudden shifts, and small sudden spikes, whereas supervised classification had higher accuracy for predicting long-term anomalies associated with drifts and periods of otherwise unexplained high variability.
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http://dx.doi.org/10.1021/acs.est.0c04069DOI Listing
November 2020

Increasing anthropogenic salinisation leads to declines in community diversity, functional diversity and trophic links in mountain streams.

Chemosphere 2021 Jan 16;263:127994. Epub 2020 Aug 16.

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.

Anthropogenic salinisation is becoming an increasing global issue for freshwater ecosystems, leading to serious biodiversity loss and ecosystem degradation. While the effect of anthropogenic salinisation on freshwater ecosystems has been intensively studied in recent years, most studies focus on salinisation effects on the individual or single groups of organisms without considering the effect on the ecosystem levels, such as diversity and trophic links. Therefore, we conducted a long-term field survey from May 2009 to August 2016 at 405 sites in northeast China to investigate the effect of a gradient of salinisation on community diversity, functional diversity and trophic links in mountain streams. Samples of water chemistry, periphyton, macroinvertebrates and fish were collected. Our results showed that as anthropogenic salinisation increased, Ca, Mg, HCO and SO exhibited significant increases (p < 0.05). These increased ions caused decreases in taxonomic evenness and biotic integrity, but an increase in the beta diversity for periphyton and macroinvertebrates, and a slight increase in the evenness of fish. The increased salinisation resulted in the extirpation of salt-sensitive taxa and declines in macroinvertebrate functional richness and functional redundancy, which consequently led to simplified trophic links. Our results implied that if salt-tolerant taxa in high salinisation sites were not functionally redundant with less tolerant taxa, alterations of their functional composition probably decrease the stability of ecosystem functions. Overall, our study suggests that the ongoing anthropogenic salinisation is posing serious threats to biodiversity and trophic links in river ecosystems, and should be considered in future river restoration and biodiversity conservation.
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http://dx.doi.org/10.1016/j.chemosphere.2020.127994DOI Listing
January 2021

Cardiac Metastases in Patients with Neuroendocrine Tumours: Clinical Features, Therapy Outcomes, and Prognostic Implications.

Neuroendocrinology 2021 27;111(10):907-924. Epub 2020 Jul 27.

Neuroendocrine Tumour Unit, Center for Gastroenterology, ENETS Centre of Excellence, Royal Free London NHS Foundation Trust, London, United Kingdom,

Background: Cardiac metastases (CM) from neuroendocrine tumours (NET) are rare; however, with the introduction of new molecular imaging modalities, such as 68Ga-DOTATATE PET-CT for NET diagnosis and re-staging, they are now identified more frequently. This study presents a single-institution experience on the NET CM characteristics, management, and prognostic implications.

Methods: Between January 1998 and January 2020, 25 NET patients with CM were treated in our unit. A retrospective review of electronic records was performed. Overall survival (OS) was assessed by the Kaplan-Meier method. Cox regression models were used to evaluate the association of various clinical variables with OS.

Results: The median age in the NET CM cohort was 64 years, with small intestine being the most common primary (84%). Nearly half of the patients suffered either from shortness of breath (48%) or had palpitations (12%). Peptide receptor radionuclide therapy (PRRT) was applied in more than half of the patients (64%), who had an improved trend for a longer median OS compared to those patients who did not receive PRRT (76.0 vs. 14.0 months, p = 0.196). The multivariate analysis demonstrated that concomitant skeletal or pancreatic metastases, as well as N-terminal pro-B-type natriuretic peptide (NT pro-BNP) >2 × upper limit of normal (ULN), were independent poor prognosticators.

Conclusions: Clinical features of NET CM ranged from asymptomatic patients to heart failure. Concomitant bone or pancreatic metastases and NT pro-BNP levels >2 ULN predicted shorter survival time. PRRT serves as a feasible therapy with promising survival benefits; however, more data are needed.
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http://dx.doi.org/10.1159/000510444DOI Listing
July 2020

Rice-shrimp ecosystems in the Mekong Delta: Linking water quality, shrimp and their natural food sources.

Sci Total Environ 2020 Oct 5;739:139931. Epub 2020 Jun 5.

Australian Rivers Institute, School of Environment and Science, Griffith University, 170 Kessels Road, Nathan, Queensland 4111, Australia.

Aquatic ecosystems are used for extensive rice-shrimp culture where the available water alternates seasonally between fresh and saline. Poor water quality has been implicated as a risk factor for shrimp survival; however, links between shrimp, water quality and their main food source, the natural aquatic biota inhabiting these ponds, are less well understood. We examined the aquatic biota and water quality of three ponds over an entire year in the Mekong Delta, Vietnam, where the growing season for the marine shrimp Penaeus monodon has been extended into the wet season, when waters freshen. The survival (30-41%) and total areal biomass (350-531 kg ha) of shrimp was constrained by poor water quality, with water temperatures, salinity and dissolved oxygen concentrations falling outside known optimal ranges for several weeks. Declines in dissolved oxygen concentration were matched by declines in both shrimp growth rates and lipid content, the latter being indicative of nutritional condition. Furthermore, as the dry season transitioned into the wet, shifts in the taxonomic composition of phytoplankton and zooplankton were accompanied by declines in the biomass of benthic algae, an important basal food source in these systems. Densities of the benthic invertebrates directly consumed by shrimp also varied substantially throughout the year. Overall, our findings suggest that the survival, condition and growth of shrimp in extensive rice-shrimp ecosystems will be constrained when poor water quality and alternating high and low salinity negatively affect the physiology, growth and composition of the natural aquatic biota. Changes in management practices, such as restricting shrimp inhabiting ponds to the dry season, may help to address these issues and improve the sustainable productivity and overall condition of these important aquatic ecosystems.
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http://dx.doi.org/10.1016/j.scitotenv.2020.139931DOI Listing
October 2020
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