ORCID Profile
0000-0002-3420-5210
Current Organisations
University of Oxford
,
University of Bristol
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Publisher: Wiley
Date: 12-11-2022
DOI: 10.1111/GCB.16485
Abstract: Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional ersity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of bio ersity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait‐based indicators. There is consequently a knowledge gap regarding when functioning changes relative to bio ersity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance‐based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non‐linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. In idual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of bio ersity when considered at the system level.
Publisher: Springer Science and Business Media LLC
Date: 23-11-2023
DOI: 10.1007/S00338-022-02323-X
Abstract: In marine environments, mutualisms such as those between corals or sea anemones and their algal symbionts (Symbiodiniaceae) play a key role for supporting surrounding bio ersity. However, as the breakdown of the mutualism between corals and/or anemones and Symbiodiniaceae (i.e. bleaching) become increasingly frequent and severe, the risk of losing the additional species that rely on them may also increase. While the effects of anemone bleaching on the biology and ecology of anemone-associated fishes have been the subject of recent research, relatively little is known about the impacts that anemone bleaching might have on the recruitment of larval fish. Here, we report that climate change-induced anemone bleaching impairs a secondary mutualism between anemones and an anemone-associated fish species, the threespot dascyllus ( Dascyllus trimaculatus ). Field-based monitoring over a 1-year period showed anemones that bleached experienced decreased recruitment of larval D. trimaculatus compared to those that did not bleach, with abundances of newly settled D. trimaculatus three times lower in bleached versus unbleached anemones. A visual choice experiment showed that this pattern is associated with fish being less attracted to bleached anemones, and a predation experiment demonstrated that fish associated with bleached anemones experienced higher mortality compared to those associated with unbleached anemones. These results suggests that the decreased recruitment of D. trimaculatus observed in bleached anemones may be driven by h ered pre-settlement (habitat selection) and post-settlement (survival to predation) processes for larval D. trimaculatus in bleached hosts. This study highlights the risk of cascading mutualism breakdowns in coral reefs as conditions deteriorate and stresses the importance of protecting these mutualisms for the maintenance of coral reef bio ersity.
Publisher: Cold Spring Harbor Laboratory
Date: 25-09-2023
Publisher: Wiley
Date: 09-2023
DOI: 10.1002/ECE3.V13.9
Publisher: Cold Spring Harbor Laboratory
Date: 09-06-2022
DOI: 10.1101/2022.06.07.495076
Abstract: Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional ersity (FD) appears a viable monitoring metric due to its mechanistic influence on ecological processes, but it is unclear whether changes in FD occur prior to state responses or vice versa. We examine the lagged relationship between planktonic FD and abundance-based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and non-linear causality approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. This suggests that FD is unlikely to be a viable early indicator, but has value as an alternative state measure if considered at the lake level. Lake Kinneret and Lake Kasumigaura data are available on request, with all other data publicly available and referenced throughout. All code for analysis is available in the Zenodo record (to be released) and the associated GitHub repository ( uncanobrien lankton-FD ).
Publisher: Cold Spring Harbor Laboratory
Date: 13-05-2023
DOI: 10.1101/2023.05.11.540304
Abstract: Quantifying the potential for abrupt non-linear changes in ecological communities is a key managerial goal, leading to a significant body of research aimed at identifying indicators of approaching regime shifts. Most of this work has built on the theory of bifurcations, with the assumption that critical transitions are a common feature of complex ecological systems. This has led to the development of a suite of often inaccurate early warning signals (EWSs), with more recent techniques seeking to overcome their limitations by analysing multivariate time series or applying machine learning. However, it remains unclear whether regime shifts and/or critical transitions are common occurrences in natural systems, and – if they are present – whether classic and second-generation EWS methods predict rapid community change. Here, using multitrophic data on nine lakes from around the world, we both identify the type of transition a lake is exhibiting, and the reliability of classic and second generation EWSs methods to predict whole ecosystem change. We find few instances of critical transitions in our lake dataset, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly technique dependant, with multivariate EWSs generally classifying correctly, classical rolling window univariate EWSs performing not better than chance, and recently developed machine learning techniques performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions and develop methods suitable for predicting change in the absence of the strict bounds of bifurcation theory.
Publisher: Inter-Research Science Center
Date: 18-02-2021
DOI: 10.3354/MEPS13589
Abstract: While definitions of elasmobranch nurseries remain fluid within the literature, the identification and description of nursery habitats for batoids remain relatively scarce. The Atlantic chupare stingray Styracura schmardae , a large-bodied demersal ray that was recently described from The Bahamas, is considered Data Deficient by the International Union for the Conservation of Nature. Using a combination of mark-recapture and benthic habitat surveying, we describe long-term site fidelity of S. schmardae for the first time, and provide evidence and characteristics of a nursery environment for this species in South Eleuthera, The Bahamas. Overall, 190 capture events were recorded from 86 tagged in iduals from April 2014 to August 2017 (1222 d), with 51% of in iduals recaptured at least once, 36% at least twice and 2% 6 times. Most (95%) of the captured rays were considered immature (mean disc width 553.5 mm) and had a mean ± SD residence time of 243 ± 177 d. Residence time did not differ among sites, sex or size (disc width) of in idual rays at time of capture. Of 4 creeks s led, Deep Creek had the highest prevalence of captures and recaptures, and correspondingly the highest values for soft sediment cover and sediment depth among sites, suggesting these habitat characteristics in particular may be important in supporting populations of juvenile S. schmardae . Results of this study will better inform effective management and conservation efforts for S. schmardae, including concentrating localised conservation efforts on these ecosystems.
Publisher: The Royal Society
Date: 12-2021
Abstract: Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the emergence of disease outbreaks, offering hope that policymakers can make predictive rather than reactive management decisions. Here, using a novel, sequential analysis in combination with daily COVID-19 case data across 24 countries, we suggest that composite EWSs consisting of variance, autocorrelation and skewness can predict nonlinear case increases, but that the predictive ability of these tools varies between waves based upon the degree of critical slowing down present. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policymakers to improve the accuracy of urgent intervention decisions but best characterize hypothesized critical transitions.
Publisher: Wiley
Date: 15-12-2022
Abstract: Temperature is a fundamental driver of species' vital rates and thus coexistence, extinctions and community composition. While temperature is neither static in space nor in time, little work has incorporated spatiotemporal dynamics into community‐level investigations of thermal variation. We conducted a microcosm experiment using ciliate protozoa to test the effects of temperatures fluctuating synchronously or asynchronously on communities in two‐patch landscapes connected by short or long corridors. We monitored the abundance of each species for 4 weeks—equivalent to ~28 generations—measuring the effects of four temperature regimes and two corridor lengths on community ersity and composition. While corridor length significantly altered the trajectory of ersity change in the communities, this did not result in different community structures at the end of the experiment. The type of thermal variation significantly affected both the temporal dynamics of ersity change and final community composition, with synchronous fluctuation causing deterministic extinctions that were consistent across replicates and spatial variation causing the greatest ersity declines. Our results suggest that the presence and type of thermal variation can play an important role in structuring ecological communities, especially when it interacts with dispersal between habitat patches.
Publisher: Wiley
Date: 10-07-2023
DOI: 10.1111/ECOG.06674
Abstract: Early warning signals (EWSs) represent a potentially universal tool for identifying whether a system is approaching a tipping point, and have been applied in fields including ecology, epidemiology, economics, and physics. This potential universality has led to the development of a suite of computational approaches aimed at improving the reliability of these methods. Classic methods based on univariate data have a long history of use, but recent theoretical advances have expanded EWSs to multivariate datasets, particularly relevant given advancements in remote sensing. More recently, novel machine learning approaches have been developed but have not been made accessible in the R ( www.r‐project.org ) environment. Here, we present EWSmethods – an R package ( www.r‐project.org ) that provides a unified syntax and interpretation of the most popular and cutting edge EWSs methods applicable to both univariate and multivariate time series. EWSmethods provides two primary functions for univariate and multivariate systems respectively, with two forms of calculation available for each: classical rolling window time series analysis, and the more robust expanding window. It also provides an interface to the Python machine learning model EWSNet which predicts the probability of a sudden tipping point or a smooth transition, the first of its form available to R ( www.r‐project.org ) users. This note details the rationale for this open‐source package and delivers an introduction to its functionality for assessing resilience. We have also provided vignettes and an external website to act as further tutorials and FAQs.
Publisher: Cold Spring Harbor Laboratory
Date: 26-06-2021
DOI: 10.1101/2021.06.24.21259444
Abstract: Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the initial emergence of disease outbreaks, offering hope that policy makers can make predictive rather than reactive management decisions. Here, using daily COVID-19 case data in combination with a novel, sequential analysis, we show that composite EWSs consisting of variance, autocorrelation, and return rate not only pre-empt the initial emergence of COVID-19 in the UK by 14 to 29 days, but also the following wave six months later. We also predict there is a high likelihood of a third wave as of the data available on 9th June 2021. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policy makers to improve the accuracy of time critical decisions based solely upon surveillance data.
Publisher: Springer Science and Business Media LLC
Date: 05-04-2021
DOI: 10.1007/S00227-021-03865-4
Abstract: Long held notions of the universally asocial octopus are being challenged due to the identification of high-density and interacting octopus populations in Australia, Indonesia, Japan and the deep sea. This study experimentally assessed the social tolerance and presence of potential prey items of Caribbean reef octopus , Octopus briareus, in a tropical marine lake (25°21′40″N, 76°30′40″W) on the island of Eleuthera, The Bahamas, by deploying artificial dens in multi-den groups or ‘units’ in the months of May and June 2019. Fifteen octopus were observed occupying dens ( n = 100), resulting in 13 den units being occupied ( n = 40). Two ex les of adjacent occupation within a single den unit were identified but with zero ex les of cohabitation/den sharing. Ecological models showed den and den unit occupation was predicted to increase with depth and differ between sites. Octopus also displayed no preference for isolated or communal units but preferred isolated dens over dens adjacent to others. Additionally, 47 % of occupied dens contained bivalve or crustacean items with no epifauna on their interior surface. The lack of epifauna suggests that these items have been recently ‘cleaned’ by occupying octopus and so represent likely prey. This study presents evidence of possible antisocial den use by O. briareus , a modification of the default ‘asocial’ ignoring of conspecifics typically attributed to octopus. This is likely in response to the high population density and may imply behavioural plasticity, making this system appropriate for further scrutiny as a research location on the influence of large, insular environments on marine species.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Duncan O'Brien.