Biology subjects

van den Berg, C. P.

Publications and source records attributed to van den Berg, C. P..

5 recordsLinked to original sources

bioRxiv2023

Automated workflows using Quantitative Colour Pattern Analysis (QCPA): A guide to batch processing and downstream data analysis

Animal and plant colouration presents a striking dimension of phenotypic variation, the study of which has driven general advances in ecology, evolution, and animal behaviour. Quantitative Colour Pattern Analysis (QCPA) is a dynamic framework for analysing colour patterns through the eyes of non-human observers. However, its extensive array of user-defined image processing and analysis tools means image analysis is often time-consuming. This hinders the full use of analytical power provided by QCPA and its application to large datasets. Here, we offer a robust and comprehensive batch script, allowing users to automate many QCPA workflows. We further provide a set of useful R scripts for downstream data extraction and analysis. These scripts will empower users to exploit the full analytical power of QCPA and facilitate the development of customised semi-automated workflows. Such quantitatively scaled workflows are crucial for exploring colour pattern space and developing ever-richer frameworks for analysing organismal colouration accounting for the visual perception in animals other than humans. These advances will, in turn, facilitate testing hypotheses on the function and evolution of vision and signals at quantitative and qualitative scales, which are otherwise computationally unfeasible.

animal behavior and cognition↗

bioRxiv2022

Signal detectability and boldness are not the same: the function of defensive colouration in nudibranchs is distant-dependent

Aposematic signals advertise underlying defences in many species. They should be detectable (highly contrasting against the background) and bold (high internal pattern contrast) to enhance predator recognition, learning and memorisation. However, the signalling function of aposematic colour patterns may be distance-dependent: signals may be undetectable from a distance to reduce costs of increased attacks from naive predators but bold when viewed up close. To test this hypothesis, we quantified the chromatic and achromatic detectability and boldness of colour patterns in 13 nudibranch species that varied in the strength of their chemical defences, in terms of unpalatability and toxicity, using Quantitative Colour Pattern Analysis (QCPA) and data on the visual perception of a triggerfish (Rhinecanthus aculeatus). When viewed from larger distances, there were no differences in detectability and boldness between well-defended and undefended species. However, when viewed at close distances, well-defended species were more detectable and bolder than undefended species. The detectability of defended species decreased more significantly with increased viewing distances compared to boldness but remained relatively consistent over viewing distances for undefended species. We provide evidence for distance-dependent signalling in aposematic nudibranchs and highlight the importance of distinguishing between signal detectability and boldness in studies of aposematism.

ecology↗

bioRxiv2022

Colour pattern edge contrast statistics can predict detection speed and success at ecologically relevant viewing distances in triggerfish (Rhinecanthus aculeatus)

Edge detection is important for object detection and recognition. However, we do not know whether edge statistics predict the detection of prey by non-human predators. Understanding the link between image statistics and animal behaviour is crucial and of increasing importance given the growing availability of image analyses and their application across non-human visual systems. Here, we investigated whether Boundary Strength Analysis (BSA), Local Edge Intensity Analysis (LEIA) and the Gabor Ratio (GabRat) could predict the speed and success with which triggerfish (Rhinecanthus aculeatus) detected patterned circular stimuli against a noisy visual background, in both chromatic and achromatic presentations. We found that individual pattern statistics could only explain up to 2% of the variation in detection time, whereas PCA regression analysis considering all edge statistics simultaneously explained up to 6% of the variation. This suggests that other factors explained more behavioural variation than individual edge statistics. Furthermore, different statistics significantly correlated with detection speed depending on treatment, viewing distance, and changes in fish response over time, while highlighting the importance of considering spatial acuity and relevant viewing distances in the study of visual signals. Our results demonstrate the need for broad and unbiased approaches for identifying task-specific predictive relationships between pattern statistics and animal behaviour using image statistics capturing different aspects of colour patterns. We require robust statistical approaches to investigate correlations between ecological effect and the ever-increasing dimensionality and size of datasets in the field of visual ecology, rather than pre-emptively narrowing down the choice of image statistics unless warranted by specific hypotheses. Summary statementCorrelations between edge detecting colour pattern statistics and animal behaviour are complex. Specifically, correlations are unlikely to be explained by single image statistics and depend upon observer distance.

animal behavior and cognition↗

bioRxiv2019

Citizen scientists highlight conservation value of a small subtropical reef, Flinders Reef, southeast Queensland, Australia.

Subtropical reefs are unique ecosystems that require effective management - informed by regular ecological monitoring - to foster resilience to environmental changes. Resources to conduct monitoring are limited, and citizen science can complement data from local management agencies. Here, citizen science efforts document the ecological status of a subtropical reef, Flinders Reef, Moreton Bay Marine Park, Australia. Ecological surveys, following Reef Check Australia and CoralWatch protocols, were conducted by 44 trained volunteers. Ten sites at Flinders Reef were surveyed at 5-10 m depth in autumn and spring. Additionally, underwater photos and depth surveys were integrated with satellite imagery to create a detailed habitat map. Coral cover across sites ranged between 14% and 67%. Branching corals dominated the site with 67% cover and showed 89% dissimilarity in coral community composition compared to other sites. Coral community composition was mostly explained by spatial variation, of which 16% was influenced by wave exposure. Observed reef impacts including physical damage, unknown scars and coral disease were three times lower than studies on more accessible reefs in Moreton Bay Marine Park. Invertebrate abundance was relatively low (6.65 individuals per 100 m2), with the most abundant groups observed being sea urchins (Diadema spp.), gastropods (Drupella spp.) and anemones. Butterflyfish were recorded at every site and were the most abundant fish group surveyed. Findings highlight the healthy condition of Flinders Reef, likely influenced by its offshore location and protection status as a no-take zone. This study demonstrates that increasing the current 500m radius protection zone by a further 500m could double the protected area of coral, offering potential further conservation benefits. The findings resulting from the ecological data analysis and created benthic habitat map, provide an example of how citizen science based projects can assist marine park authorities and the public in ongoing conservation efforts.

ecology↗

bioRxiv2019

Quantitative Colour Pattern Analysis (QCPA): A Comprehensive Framework for the Analysis of Colour Patterns in Nature

O_LITo understand the function of colour signals in nature, we require robust quantitative analytical frameworks to enable us to estimate how animal and plant colour patterns appear against their natural background as viewed by ecologically relevant species. Due to the quantitative limitations of existing methods, colour and pattern are rarely analysed in conjunction with one another, despite a large body of literature and decades of research on the importance of spatiochromatic colour pattern analyses. Furthermore, key physiological limitations of animal visual systems such as spatial acuity, spectral sensitivities, photoreceptor abundances and receptor noise levels are rarely considered together in colour pattern analyses.\nC_LIO_LIHere, we present a novel analytical framework, called the Quantitative Colour Pattern Analysis (QCPA). We have overcome many quantitative and qualitative limitations of existing colour pattern analyses by combining calibrated digital photography and visual modelling. We have integrated and updated existing spatiochromatic colour pattern analyses, including adjacency, visual contrast and boundary strength analysis, to be implemented using calibrated digital photography through the Multispectral Image Analysis and Calibration (MICA) Toolbox.\nC_LIO_LIThis combination of calibrated photography and spatiochromatic colour pattern analyses is enabled by the inclusion of psychophysical colour and luminance discrimination thresholds for image segmentation, which we call Receptor Noise Limited Clustering, used here for the first time. Furthermore, QCPA provides a novel psycho-physiological approach to the modelling of spatial acuity using convolution in the spatial or frequency domains, followed by Receptor Noise Limited Ranked Filtering to eliminate intermediate edge artefacts and recover sharp boundaries following smoothing. We also present a new type of colour pattern analysis, the Local Edge Intensity Analysis (LEIA) as well as a range of novel psycho-physiological approaches to the visualisation of spatiochromatic data.\nC_LIO_LIQCPA combines novel and existing pattern analysis frameworks into what we hope is a unified, user-friendly, free and open source toolbox and introduce a range of novel analytical and data-visualisation approaches. These analyses and tools have been seamlessly integrated into the MICA toolbox providing a dynamic and user-friendly workflow.\nC_LIO_LIQCPA is a framework for the empirical investigation of key theories underlying the design, function and evolution of colour patterns in nature. We believe that it is compatible with, but more thorough than, other existing colour pattern analyses.\nC_LI

animal behavior and cognition↗