A novel body coloration phenotype in Anolis sagrei:Implications for physiology, fitness, and predation

<div><p>In animals, color signals that convey information about quality are often associated with costs linked to the expression of coloration and may therefore be honest signals of sender quality. Honest indicators are often seen in sexual signals that are used by males to advertise quality to females. Carotenoid and pterin pigments are responsible for yellow, orange, and red coloration in a variety of taxa, but can also serve important roles as antioxidants by reducing free radicals in the body. In this study, we test the effects of a novel full-bodied orange color phenotype of the brown anole, <i>Anolis sagrei</i>, on mate choice, physiology, and survival. We found no evidence that lizards expressing the orange phenotype were preferred by females. Additionally, they did not differ in immune function, running endurance, or maximum sprint speed from lizards that did not express the novel phenotype. Pigment extractions revealed that orange body coloration resulted from pterin pigments and not carotenoids. Visual models suggest that the orange phenotype is less conspicuous to bird predators than the brown phenotype and may provide an adaptive explanation for the persistence of this trait. Given its small, yet positive effect on fitness, we expect the orange color phenotype to increase in frequency in subsequent decades.</p></div

What Have Long-Term Field Studies Taught Us About Population Dynamics?

Long-term studies have been crucial to the advancement of population biology, especially our understanding of population dynamics. We argue that this progress arises from three key characteristics of long-term research. First, long-term data are necessary to observe the heterogeneity that drives most population processes. Second, long-term studies often inherently lead to novel insights. Finally, long-term field studies can serve as model systems for population biology, allowing for theory and methods to be tested under well-characterized conditions. We illustrate these ideas in three long-term field systems that have made outsized contributions to our understanding of population ecology, evolution, and conservation biology. We then highlight three emerging areas to which long-term field studies are well positioned to contribute in the future: ecological forecasting, genomics, and macrosystems ecology. Overcoming the obstacles associated with maintaining long-term studies requires continued emphasis on recognizing the benefits of such studies to ensure that long-term research continues to have a substantial impact on elucidating population biology

Sex-related differences in aging rate are associated with sex chromosome system in amphibians

Sex-related differences in mortality are widespread in the animal kingdom. Although studies have shown that sex determination systems might drive lifespan evolution, sex chromosome influence on aging rates have not been investigated so far, likely due to an apparent lack of demographic data from clades including both XY (with heterogametic males) and ZW (heterogametic females) systems. Taking advantage of a unique collection of capture-recapture datasets in amphibians, a vertebrate group where XY and ZW systems have repeatedly evolved over the past 200 million years, we examined whether sex heterogamy can predict sex differences in aging rates and lifespans. We showed that the strength and direction of sex differences in aging rates (and not lifespan) differ between XY and ZW systems. Sex-specific variation in aging rates was moderate within each system, but aging rates tended to be consistently higher in the heterogametic sex. This led to small but detectable effects of sex chromosome system on sex differences in aging rates in our models. Although preliminary, our results suggest that exposed recessive deleterious mutations on the X/Z chromosome (the "unguarded X/Z effect") or repeat-rich Y/W chromosome (the "toxic Y/W effect") could accelerate aging in the heterogametic sex in some vertebrate clades.Peer reviewe

Metrics reloaded: Pitfalls and recommendations for image analysis validation

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, our large international expert consortium created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool, which also provides a point of access to explore weaknesses, strengths and specific recommendations for the most common validation metrics. The broad applicability of our framework across domains is demonstrated by an instantiation for various biological and medical image analysis use cases

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior authors: Paul F. J\"ager, Lena Maier-Hei

Common Limitations of Image Processing Metrics:A Picture Story

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The current version discusses metrics for image-level classification, semantic segmentation, object detection and instance segmentation. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorshi

Joint estimation of growth and survival from mark–recapture data to improve estimates of senescence in wild populations: Reply

We are grateful for Keevil’s (2020) identification of a mistakenly limited prior in the code we supplied as a supplement to Reinke et al. (2020), describing a new model. Within our paper, we demonstrated use of a hierarchical model using mark–recapture datasets that were also published as supplementary material. The introduction of the model was the focus of our paper and the code was included as a courtesy to those who would like to use the model, with parameters adjusted to suit their needs. This transparency allowed Keevil (2020) to run our model with the provided example datasets, identify the limited prior, and set values of their choosing. We are therefore pleased to see firsthand the benefits of open access in science.This reply is published as Bronikowski, Anne M., Beth A. Reinke, Luke Hoekstra, Fredric J. Janzen, and David AW Miller. "Joint estimation of growth and survival from mark–recapture data to improve estimates of senescence in wild populations: Reply." Ecology (2021): e03571. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes

A Framework for Investigating Rules of Life by Establishing Zones of Influence

The incredible complexity of biological processes across temporal and spatial scales hampers defning common underlying mechanisms driving the patterns of life. However, recent advances in sequencing, big data analysis, machine learning, and molecular dynamics simulation have renewed the hope and urgency of fnding potential hidden rules of life. There currently exists no framework to develop such synoptic investigations. Some efforts aim to identify unifying rules of life across hierarchical levels of time, space, and biological organization, but not all phenomena occur across all the levels of these hierarchies. Instead of identifying the same parameters and rules across levels, we posit that each level of a temporal and spatial scale and each level of biological organization has unique parameters and rules that may or may not predict outcomes in neighboring levels. We defne this neighborhood, or the set of levels, across which a rule functions as the zone of influence. Here, we introduce the zone of influence framework and explain using three examples: (a) randomness in biology, where we use a Poisson process to describe processes from protein dynamics to DNA mutations to gene expressions, (b) island biogeography, and (c) animal coloration. The zone of in?uence framework may enable researchers to identify which levels are worth investigating for a particular phenomenon and reframe the narrative of searching for a unifying rule of life to the investigation of how, when, and where various rules of life operate

Sex-specific innate immunity and ageing in long-lived fresh water turtles (Kinosternon flavescens: Kinosternidae)

Background The progressive deregulation of the immune system with age, termed immunosenescence, has been well studied in mammalian systems, but studies of immune function in long-lived, wild, non-mammalian populations are scarce. In this study we leverage a 38-year mark-recapture study to quantify the relationships among age, sex, survival, reproductive output and the innate immune system in a long-lived reptile, yellow mud turtles (Kinosternon flavescens; Testudines; Kinosternidae). Methods We estimated rates of survival and age-specific mortality by sex based on mark-recapture data for 1530 adult females and 860 adult males over 38 years of captures. We analyzed bactericidal competence (BC), and two immune responses to foreign red blood cells - natural antibody-mediated haemagglutination (NAbs), and complement-mediated haemolysis ability (Lys) - in 200 adults (102 females; 98 males) that ranged from 7 to 58 years of age captured in May 2018 during their emergence from brumation, and for which reproductive output and long-term mark-recapture data were available. Results We found that females are smaller and live longer than males in this population, but the rate of accelerating mortality across adulthood is the same for both sexes. In contrast, males exhibited higher innate immunity than females for all three immune variables we measured. All immune responses also varied inversely with age, indicating immunosenescence. For females that reproduced in the preceding reproductive season, egg mass (and therefore total clutch mass) increased with age,. In addition to immunosenescence of bactericidal competence, females that produced smaller clutches also had lower bactericidal competence. Conclusions Contrary to the general vertebrate pattern of lower immune responses in males than females (possibly reflecting the suppressive effects of androgens), we found higher levels of all three immune variables in males. In addition, contrary to previous work that found no evidence of immunosenescence in painted turtles or red-eared slider turtles, we found a decrease in bactericidal competence, lysis ability, and natural antibodies with age in yellow mud turtles. Background Ageing in many vertebrate systems is characterized by organismal senescence – declining efficiency and performance of physiological and cellular processes [1] leading to declining age-specific survival and fertility with advancing age [2]. Studies of ageing in wild populations of vertebrates have often focused on quantifying age-related changes in fecundity and mortality [3], but less often on physiological mechanisms that may contribute to such demographic ageing (e.g., [4,5,6]). One such candidate physiological mechanism is immune function, which plays a critical role in survival. Reduced immune function has been shown to negatively impact survival and reproduction [6,7,8]. The progressive deregulation of the immune system with age, termed immunosenescence, has been well studied in humans for both innate immunity (whose dysregulation with age can lead to chronic inflammation [9]), and acquired immunity, where the best studied changes are an increase in memory T cells and decrease in naïve T cells with advancing age (but here too, immunosenescence remains enigmatic [10]). However, age-specific changes in the immune system of long-lived, wild, non-mammalian populations are not well described in the literature, and studies focusing on reptile immunosenescence are even more rare (reviewed in [8]).This article is published as Bronikowski, A.M., Hedrick, A.R., Kutz, G.A. et al. Sex-specific innate immunity and ageing in long-lived fresh water turtles (Kinosternon flavescens: Kinosternidae). Immun Ageing 20, 11 (2023). https://doi.org/10.1186/s12979-023-00335-x. Posted with permission.This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data