ORCID Profile
0000-0002-1685-3169
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Publisher: AIP Publishing
Date: 12-2022
DOI: 10.1063/5.0096769
Abstract: In recent years, various nonlinear algebraic structures have been obtained in the context of quantum systems as symmetry algebras, Painlevé transcendent models, and missing label problems. In this paper, we treat all these algebras as instances of the class of quadratic (and higher degree) commutator bracket algebras of Poincaré–Birkhoff–Witt type. We provide a general approach for simplifying the constraints arising from the diamond lemma and apply this in particular to give a comprehensive analysis of the quadratic case. We present new ex les of quadratic algebras, which admit a cubic Casimir invariant. The connection with other approaches, such as Gröbner bases, is developed, and we suggest how our explicit and computational techniques can be relevant in other contexts.
Publisher: Cold Spring Harbor Laboratory
Date: 19-01-2021
DOI: 10.1101/2021.01.18.427207
Abstract: The spatial analysis of linear features (lines and curves) is a challenging and rarely attempted problem in ecology. Existing methods are typically expressed in abstract mathematical formalism, making it difficult to assess their relevance and transferability into an ecological setting. A set of concrete and accessible tools is needed. We develop a new method to analyse the spatial patterning of line-segment data. It is based on a generalisation of Ripley’s K -function and includes an analogue of the transformed L -function, together with estimators and theoretical expectation values. We introduce a class of line-segment processes, related to the Boolean model, which we use in conjunction with Monte-Carlo methods and information criteria to generate and compare candidate models. We demonstrate the utility of our method using fallen tree (dead log) data collected from two one-hectare Australian tall eucalypt forest plots. Comparing six line-segment models, we find for both plots that the distribution of fallen logs is best explained by plot-level spatial heterogeneity. The use of non-uniform distributions to model dead-log orientation on the forest floor improves model performance in one of the two sites. Our case study highlights the challenges of model comparison in spatial-pattern analysis, where Monte-Carlo approaches based on the discrepancy of simulated summary functions can generate a different ranking of models than that of information criteria. These methods are of a general nature and are applicable to any line-segment data. In the context of forest ecology, the integration of fallen logs as linear structural features in a landscape with the point locations of living trees, and a quantification of their interactions, will yield new insights into the functional and structural role of tree fall in forest communities and their enduring post-mortem ecological legacy as spatially distributed decomposing logs.
Publisher: IOP Publishing
Date: 18-09-2020
Publisher: Cold Spring Harbor Laboratory
Date: 19-02-2021
DOI: 10.1101/2021.02.18.429855
Abstract: Global road networks facilitate habitat modification and are integral to human expansion. Many animals, particularly scavengers, use roads as they provide a reliable source of food, such as carrion left after vehicle collisions. Tasmania is often cited as the ‘roadkill capital of Australia’, with the isolated offshore islands in the Bass Strait experiencing similar, if not higher, levels of roadkill. However, native mammalian predators on the islands are extirpated, meaning the remaining scavengers are likely to experience lower interference competition. In this study, we use a naturally occurring experiment to examine how the loss of mammalian carnivores within a community impacts roadside foraging behaviour by avian scavengers. We monitored the locations of roadkill and forest ravens ( Corvus tasmanicus ), an abundant scavenger species, on eight road transects across the Tasmanian mainland (high scavenging competition) and the Bass Strait islands (low scavenging competition). We represented raven observations as one-dimensional point patterns, using hierarchical Bayesian models to investigate the dependence of raven spatial intensity on habitat, season, distance to roadkill and route location. We found that roadkill carcasses were a strong predictor of raven presence along road networks. The effect of roadkill was lified on roads on the Bass Strait islands, where roadside carrion was a predictor of raven presence across the entire year. In contrast, ravens were more often associated with roadkill on Tasmanian mainland roads in the autumn, when other resources were low. This suggests that in the absence of competing mammalian scavengers, ravens choose to feed on roadside carrion throughout the year, even in seasons when other resources are available. This low interference competition could be disproportionately benefiting forest ravens, leading to augmented raven populations and changes to the vertebrate community structure. Our study provides evidence that scavengers modify their behaviour in response to reduced scavenger species ersity, potentially triggering trophic shifts and highlighting the importance of conserving or reintroducing carnivores within ecosystems.
Publisher: Wiley
Date: 20-06-2023
Abstract: Correlation across species between two quantitative traits, or between a trait and a habitat property, can suggest that a trait value is effective in sustaining populations in some contexts but not others. It is widely held that such correlations should be controlled for phylogeny, via phylogenetically independent contrasts (PICs) or phylogenetic generalized least squares (PGLS). A weakness of this idea is that a clade's traits tend to confer success in particular habitats or ways of life, and those niches in turn tend to select for the same traits to continue in the clade. This feedback mechanism can bind phylogeny and niche together as a unified cause for present‐day trait configurations. Accordingly, the phylogenetically conservative share of a trait correlation ought not to be excluded from consideration as potentially ecologically functional. Another weakness is that PGLS does not yield a complete or accurate breakdown of covariation between traits A and B because it corresponds to a generating model where B predicts variation in A but not the reverse, and phylogenetic signal in B is not modelled. Multi‐response mixed models using phylogenetic covariance matrices can quantify conservative trait correlation (CTC), a share of A‐B covariation that is phylogenetically conservative. Because the evidence is from correlative data, it is not possible to split CTC into causation by phylogenetic history versus causation by continuing reciprocal selection between A and B. Moreover, it is quite likely biologically that the two influences have acted in concert, through phylogenetic niche conservatism. Synthesis : The CTC concept treats phylogenetic conservatism as a conjoint interpretation alongside ongoing influence of other traits. CTC can be quantified via multi‐response phylogenetic mixed models.
Publisher: IOP Publishing
Date: 11-05-2011
Publisher: Wiley
Date: 03-01-2023
DOI: 10.1002/ECM.1557
Abstract: Specifying, assessing, and selecting among candidate statistical models is fundamental to ecological research. Commonly used approaches to model selection are based on predictive scores and include information criteria such as Akaike's information criterion, and cross validation. Based on data splitting, cross validation is particularly versatile because it can be used even when it is not possible to derive a likelihood (e.g., many forms of machine learning) or count parameters precisely (e.g., mixed‐effects models). However, much of the literature on cross validation is technical and spread across statistical journals, making it difficult for ecological analysts to assess and choose among the wide range of options. Here we provide a comprehensive, accessible review that explains important—but often overlooked—technical aspects of cross validation for model selection, such as: bias correction, estimation uncertainty, choice of scores, and selection rules to mitigate overfitting. We synthesize the relevant statistical advances to make recommendations for the choice of cross‐validation technique and we present two ecological case studies to illustrate their application. In most instances, we recommend using exact or approximate leave‐one‐out cross validation to minimize bias, or otherwise k ‐fold with bias correction if k 10. To mitigate overfitting when using cross validation, we recommend calibrated selection via our recently introduced modified one‐standard‐error rule. We advocate for the use of predictive scores in model selection across a range of typical modeling goals, such as exploration, hypothesis testing, and prediction, provided that models are specified in accordance with the stated goal. We also emphasize, as others have done, that inference on parameter estimates is biased if preceded by model selection and instead requires a carefully specified single model or further technical adjustments.
Publisher: Cold Spring Harbor Laboratory
Date: 16-07-2021
DOI: 10.1101/2021.07.12.21260394
Abstract: Some countries have been crippled by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic while others have emerged with few infections and fatalities the factors underscoring this macro-epidemiological variation is one of the mysteries of this global catastrophe. Variation in immune responses influence SARS-CoV-2 transmission and mortality, and factors shaping this variation at the country level, in addition to other socio-ecological drivers, may be important. Here, we construct spatially explicit Bayesian models that combine data on prevalence of endemic diseases and other socio-ecological characteristics to quantify patterns of confirmed deaths and cases across the globe before mass vaccination. We find that the prevalence of parasitic worms, human immunodeficiency virus and malaria play a surprisingly important role in predicting country-level SARS-CoV-2 patterns. When combined with factors such as population density, our models predict 63% (56-67) and 76% (69-81) of confirmed cases and deaths among countries, respectively. While our findings at this macro-scale are necessarily associative, they highlight a need for studies to consider factors, such as infection by other pathogens, on global SARS-CoV-2 dynamics. These relationships are vital for developing countries that already have the highest burden of endemic disease and are becoming the most affected by the SARS-CoV-2 pandemic.
Publisher: Wiley
Date: 07-06-2021
Abstract: Global road networks facilitate habitat modification and are integral to human expansion. Many animals, particularly scavengers, use roads as they provide a reliable source of food, such as carrion left after vehicle collisions. Tasmania is often cited as the ‘roadkill capital of Australia’, with the isolated offshore islands in the Bass Strait experiencing similar, if not higher, levels of roadkill. However, native mammalian predators on the islands are extirpated, meaning the remaining scavengers are likely to experience lower interference competition. In this study, we used a naturally occurring experiment to examine how the loss of mammalian carnivores within a community impacts roadside foraging behaviour by avian scavengers. We monitored the locations of roadkill and forest ravens Corvus tasmanicus , an abundant scavenger species, on eight road transects across the Tasmanian mainland (high scavenging competition) and the Bass Strait islands (low scavenging competition). We represented raven observations as one‐dimensional point patterns, using hierarchical Bayesian models to investigate the dependence of raven spatial intensity on habitat, season, distance to roadkill and route location. We found that roadkill carcasses were a strong predictor of raven presence along road networks. The effect of roadkill was lified on roads on the Bass Strait islands, where roadside carrion was a predictor of raven presence across the entire year. In contrast, ravens were more often associated with roadkill on Tasmanian mainland roads in the autumn, when other resources were low. This suggests that in the absence of competing mammalian scavengers, ravens choose to feed on roadside carrion throughout the year, even in seasons when other resources are available. This lack of competition could be disproportionately benefiting forest ravens, leading to augmented raven populations and changes to the vertebrate community structure. Our study provides evidence that scavengers modify their behaviour in response to reduced scavenger species ersity, potentially triggering trophic shifts and highlighting the importance of conserving or reintroducing carnivores within ecosystems.
Publisher: IOP Publishing
Date: 09-2020
Abstract: Rising crop production over the last half century has had far-reaching consequences for human welfare and the environment. With food demand projected to rise, one of the central challenges in minimizing agriculture’s impacts on the climate and bio ersity is to increase crop production with higher yields rather than more cropland. However, quantifying progress is challenging. When analyzed at the most aggregated, global level, yields can be defined as the total crop output per unit area per year, but aggregate yields are driven by multiple factors, only some of which have a clear relationship to improved agricultural production. To date, there is no research that simultaneously determines how much of rising crop production has been met by rising aggregate yields versus cropland expansion, while also quantifying the unique contribution of each yield driver. Using LMDI decomposition analysis, we find that rising aggregate yields contributed far more than cropland expansion (89% compared to 11%). That is, growing global food demand has by and large been met by growing more crops on the same amount of land, rather than expanding cropland. Our second-stage decomposition showed that nearly two-thirds of aggregate yield improvements have come from pure yield, or the output of a given crop per unit of harvested cropland area in a given country per unit area per year. The remainder has come from less-discussed drivers of aggregate yields, including cropping intensity, changes in the geographic distribution of cropland, and crop composition. Further, we use attribution analysis to show the contributions to different decomposition factors from countries grouped by climate, income, and region, as well as from different crops. Such granular yet comprehensive breakdowns of crop production and aggregate yields offer more accurate forecasts and can help focus policies on the most promising levers to meet rising food demand sustainably.
Publisher: Cold Spring Harbor Laboratory
Date: 12-08-2023
DOI: 10.1101/2023.08.08.552370
Abstract: Southeast Asia is highly bio erse and currently experiences among the highest rates of tropical deforestation globally, but impacts on bio ersity are not well synthesized. We use Bayesian multi-level modeling to meta-analyse 831 pairwise comparisons of bio ersity in sites subject to human land use change and anthropogenic forest disturbance (for ex le in plantations or logged forest) versus undisturbed sites. After controlling for hierarchical dependences, we show that bio ersity is a fifth lower in sites with these land-use changes (95% credible interval= 16-28%, mean = 22%). This reduction was greater when land use change/anthropogenic forest disturbances were high-intensity (34% reduction in bio ersity) compared to low-intensity (18% reduction), and effects were consistent across biogeographic regions and taxa. Oil-palm plantations lead to the greatest reduction in bio ersity (39%, CI 27-48%), and agroforests the least (24%, CI 10-37%). We also find that bio ersity is reduced in young secondary forest by 26% (CI 4-42%) compared to undisturbed forest, but there is no reduction in bio ersity for intermediate or mature-aged secondary forest (although species composition is potentially altered). Overall, our study provides the clearest evidence yet of the substantial detrimental impact of land-use change and anthropogenic forest disturbance on the bio ersity of Southeast Asia.
Publisher: IOP Publishing
Date: 12-03-2018
Publisher: Wiley
Date: 09-2021
DOI: 10.1002/ECY.3475
Abstract: Information‐theoretic approaches to model selection, such as Akaike's information criterion (AIC) and cross validation, provide a rigorous framework to select among candidate hypotheses in ecology, yet the persistent concern of overfitting undermines the interpretation of inferred processes. A common misconception is that overfitting is due to the choice of criterion or model score, despite research demonstrating that selection uncertainty associated with score estimation is the predominant influence. Here we introduce a novel selection rule that identifies a parsimonious model by directly accounting for estimation uncertainty, while still retaining an information‐theoretic interpretation. The new rule, which is a modification of the existing one‐standard‐error rule, mitigates overfitting and reduces the likelihood that spurious effects will be included in the selected model, thereby improving its inferential properties. We present the rule and illustrative ex les in the context of maximum‐likelihood estimation and Kullback‐Leibler discrepancy, although the rule is applicable in a more general setting, including Bayesian model selection and other types of discrepancy.
Publisher: Wiley
Date: 23-12-2022
DOI: 10.1002/ECY.3597
Abstract: The spatial analysis of linear features (lines and curves) is a challenging and rarely attempted problem in ecology. Existing methods are typically expressed in abstract mathematical formalism, making it difficult to assess their relevance and transferability into an ecological setting. We introduce a set of concrete and accessible methods to analyze the spatial patterning of line‐segment data. The methods include Monte Carlo techniques based on a new generalization of Ripley's ‐function and a class of line‐segment processes that can be used to specify parametric models: parameters are estimated using maximum likelihood and models compared using information‐theoretic principles. We apply the new methods to fallen tree (dead log) data collected from two 1‐ha Australian tall eucalypt forest plots. Our results show that the spatial pattern of the fallen logs is best explained by plot‐level spatial heterogeneity in combination with a slope‐dependent nonuniform distribution of fallen‐log orientations. These methods are of a general nature and are applicable to any line‐segment data. In the context of forest ecology, the integration of fallen logs as linear structural features in a landscape with the point locations of living trees, and a quantification of their interactions, can yield new insights into the functional and structural role of tree fall in forest communities and their enduring post‐mortem ecological legacy as spatially distributed decomposing logs.
Publisher: The Royal Society
Date: 26-10-2022
Abstract: Scavenging by large carnivores is integral for ecosystem functioning by limiting the build-up of carrion and facilitating widespread energy flows. However, top carnivores have declined across the world, triggering trophic shifts within ecosystems. Here, we compare findings from previous work on predator decline against areas with recent native mammalian carnivore loss. Specifically, we investigate top-down control on utilization of experimentally placed carcasses by two mesoscavengers—the invasive feral cat and native forest raven. Ravens profited most from carnivore loss, scavenging for five times longer in the absence of native mammalian carnivores. Cats scavenged on half of all carcasses in the region without dominant native carnivores. This was eight times more than in areas where other carnivores were at high densities. All carcasses persisted longer than the three-week monitoring period in the absence of native mammalian carnivores, while in areas with high carnivore abundance, all carcasses were fully consumed. Our results reveal that top-carnivore loss lifies impacts associated with carnivore decline—increased carcass persistence and carrion access for smaller scavengers. This suggests that even at low densities, native mammalian carnivores can fulfil their ecological functions, demonstrating the significance of global carnivore conservation and supporting management approaches, such as trophic rewilding.
No related grants have been discovered for Luke Yates.