Search

Abstract Background Floodplains harbor highly biodiverse ecosystems, which have been strongly affected by both past climate change and by recent human activities, resulting in a high prevalence of many endangered species in these habitats. Understanding the history of floodplain species over a wide range of timescales can contribute to effective conservation planning. We reconstructed the population formation history of the Itasenpara bitterling Acheilognathus longipinnis, an endangered floodplain fish species in Japan, over a broad timescale based on phylogenetic analysis, demographic modeling, and historical demographic analysis using mitogenome and whole-genome sequences. A genome sequence was newly assembled as a reference for the resequencing analysis. This bitterling is distributed in three plains separated by high mountain ranges and exhibits ecological characteristics well adapted to floodplain environments. Results Our analyses revealed an unexpected population branching pattern, gene flow, and timing of the differentiation that occurred within a few hundred thousand years, i.e., long after the mountain uplift that was assumed to be the primary geological cause of the population differentiation. The analyses also showed that all local populations experienced a severe decline during the last glacial and post-glacial periods. Conclusions Our results suggest that the floodplain bitterling was able to disperse through unknown routes after mountain uplift and that its populations were strongly influenced by climatic and geographic changes in glacial–interglacial cycles and subsequent human activities, probably related to its floodplain-dependent ecology. The genomic data highlight the unanticipated distribution process of this species and the magnitude of the impact of human activities, with important implications for its conservation.

Abstract Background Developing evolutionary literacy is an important component of post-secondary students’ education and is a primary goal for evolution educators. However, as obstacles exist to students’ acceptance of evolution, more information needs to be obtained about what type of evidence students find compelling (or do not) that supports evolution to explain the diversity of life on Earth. Using the lens of conceptual ecologies, this study aimed to determine what lines of evidence senior university biology students found compelling. We examined six semesters of Pre-Post survey data taken at the beginning and end of the semester from 2014 to 2021 to categorize the types of evidence students claimed to find compelling. Results We identified seven categories of evidence that senior university biology students found compelling: New from Old, Comparative Biology, Structural Homology, Demonstration of Natural Section, Adaptation, Molecular Biology, and Not Convinced. A Chi-Square test of Independence indicated a significant difference in the categories that were most frequently discussed between the Pre- and Post surveys. Demonstration of Natural Selection had the highest percentage of student responses in the Pre-survey, while Molecular Biology ranked the highest in the Post. We parsed out the particular types of evidence nested within the Molecular Biology category to see which students found more compelling in the Post-survey. We also found that participation in a one-semester course decreased the percentage of students who answered Not Convinced from Pre to Post every semester. Conclusions Results from this study can offer suggestions for evolution education, such as including more examples of Molecular Biology evolution, as students found this category most compelling in the Post-survey. These types of examples can be used throughout evolution courses or focused on more deeply to support student understanding.

Abstract This study introduces a participatory science-inspired approach to teaching and curriculum design, involving undergraduate students directly in active research. Using a case study on dinosaur eye size, integrated into a first-year undergraduate course in Geology and Palaeontology at a UK university, this study presents the advantages and disadvantages of this approach for both teachers and learners. As part of the study, 22 undergraduate students were involved in data collection, analysis, and the subsequent publication processes, emphasizing active student participation in research. A subsequent survey demonstrated high student engagement and perceived relevance of this participatory science-style teaching approach. Results indicate that students found the approach appealing, engaging, and beneficial for understanding scientific concepts and methods. The case study shows that a participatory science approach through a course-based research experience can enhance student engagement and learning by providing meaningful, hands-on research experiences. This approach allowed students to apply theoretical knowledge in a realistic context, fostering their understanding of evolutionary theory through active data collection and analysis. However, care should be taken concerning data accuracy and ethical aspects, such as exploitation of labour and the recognition of knowledge creators and participants. Despite these challenges, the benefits of integrating such approaches into higher education curricula can be substantial, offering a valuable model for teaching evolutionary theory and related topics.

Abstract Background Phylogenetics is one of the main methodologies to understand cross-cutting principles of evolution, such as common ancestry and speciation. Phylogenetic trees, however, are reportedly challenging to teach and learn. Furthermore, phylogenetics teaching methods traditionally rely solely on visual information, creating inaccessibility for people with visual impairment. Sensory learning style models advocate for tailoring teaching to individual preferred sensory learning style. However, recent research suggests that optimal learning, independently of preferred learning style, depends on the types of transmitted information and learning tasks. The lack of empirically-supported education into the effectiveness of teaching phylogenetics through alternative sensory modalities potentially hinders learning. The aim of this study was to determine whether phylogenetic trees could be better understood if presented in kinaesthetic or multisensory teaching modalities. Results Participants (N = 52) self-assessed personal learning style and were randomly assigned to: visual, kinaesthetic or multisensory learning conditions. Phylogeny reading performance was better for both kinaesthetic and multisensory teaching conditions, compared to the visual teaching condition. There was no main effect and no interaction effect of personal learning style. Conclusions This study establishes a baseline for further research by suggesting that easy-to-implement kinaesthetic teaching modalities might support phylogenetic tree learning and reading. This has practical implications for evolution education and accessibility for students with visual impairment, underscoring the need to shift from vision-centric teaching paradigms towards evidence-based instructional strategies that accommodate sensory diversity.

Abstract Background Panarthropods, a major group of invertebrate animals comprised of arthropods, onychophorans, and tardigrades, are the only limb-bearing members of Ecdysozoa. The complexity and versatility of panarthropod paired limbs has prompted great interest in their development to better understand the formation of these structures and the genes involved in this process. However, studies of limb patterning and development are overwhelmingly focused on arthropods, followed by select work on onychophorans but almost entirely lacking for tardigrades. This model organism bias is inherently limited and precludes a comparative analysis of how panarthropod legs originated, have evolved, and the likely limb patterning genes present in the earliest panarthropod ancestors. In this study, we investigated tardigrade homologs of seven arthropod distal limb patterning genes (apterous, aristaless, BarH1, clawless, Lim1, rotund, and spineless) to better characterize tardigrade limb development in a comparative context. Results We detected homologs of all seven genes in the eutardigrade Hypsibius exemplaris and heterotardigrade Echiniscoides cf. sigismundi suggesting their conservation in both tardigrade lineages. Hybridization chain reaction experiments in H. exemplaris reveal a regionalized expression pattern for the genes aristaless, BarH1, clawless, rotund and spineless. Conclusion The observed regionalized expression of the distal limb patterning genes in H. exemplaris might reflect the external morphological features of tardigrade legs, such as the distal claws, sensory organs in the proximal region, and specific muscle attachment sites. The comparison between the expression of these limb patterning genes in H. exemplaris relative to other panarthropods suggests their conserved role in the last common panarthropod ancestor, such as establishing the distal limb end and the distribution of sensory structures. Our results support the hypothesis that tardigrade legs are homologous to the distal region of other panarthropod limbs, as suggested by previous work on the expression of leg gap genes in H. exemplaris.

Abstract Understanding the interplay between genetic drift, natural selection, gene flow, and demographic history in driving phenotypic and genomic differentiation of insular populations can help us gain insight into the speciation process. Comparing patterns across different insular taxa subjected to similar selective pressures upon colonizing oceanic islands provides the opportunity to study repeated evolution and identify shared patterns in their genomic landscapes of differentiation. We selected four species of passerine birds (Common Chaffinch Fringilla coelebs/canariensis, Red-billed Chough Pyrrhocorax pyrrhocorax, House Finch Haemorhous mexicanus and Dark-eyed/island Junco Junco hyemalis/insularis) that have both mainland and insular populations. Changes in body size between island and mainland populations were consistent with the island rule. For each species, we sequenced whole genomes from mainland and insular individuals to infer their demographic history, characterize their genomic differentiation, and identify the factors shaping them. We estimated the relative (F st ) and absolute (d xy ) differentiation, nucleotide diversity (π), Tajima’s D, gene density and recombination rate. We also searched for selective sweeps and chromosomal inversions along the genome. All species shared a marked reduction in effective population size (Ne) upon island colonization. We found diverse patterns of differentiated genomic regions relative to the genome average in all four species, suggesting the role of selection in island-mainland differentiation, yet the lack of congruence in the location of these regions indicates that each species evolved differently in insular environments. Our results suggest that the genomic mechanisms involved in the divergence upon island colonization—such as chromosomal inversions, and historical factors like recurrent selection—differ in each species, despite the highly conserved structure of avian genomes and the similar selective factors involved. These differences are likely influenced by factors such as genetic drift, the polygenic nature of fitness traits and the action of case-specific selective pressures.

Abstract The ecological importance of great apes is widely recognised, yet few studies have highlighted the role of protecting great apes’ habitats in mitigating climate change, particularly through carbon sequestration. This study used GIS tools to extract data from various sources, including the International Union for Conservation of Nature database, to examine carbon quantity and great ape abundance in African great ape habitats. Subsequently, we employed a generalised linear model to assess the relationship between locally measured great ape populations abundance and carbon storage across areas with different levels of protection. Our findings showed a positive relationship between the abundance of great apes in their habitats and carbon storage, likely since conservation efforts in great apes habitats may be strengthened with higher great ape populations. The results reveal that gorilla habitats exhibited higher carbon storage than chimpanzee habitats. Specifically, the areas inhabited by gorillas are associated with a mean increase of 27.47 t/ha in carbon storage. Additionally, we observed a positive association between highly protected areas and carbon storage within great ape habitats. Our model indicates that highly protected areas increase the mean carbon stored by 1.13 t/ha compared to medium protected areas, which show a reduction of 15.49 t/ha. This highlights the critical role that protected areas play in both species conservation and carbon sequestration, contributing significantly to climate mitigation efforts. Furthermore, our study underscores the significant contribution of great ape habitats, extending beyond protected areas, to carbon storage, highlighting the potential for synergistic conservation strategies targeting both great apes and carbon sequestration. Protecting great apes is vital for reducing carbon emissions from deforestation and boosting tropical forest carbon sinks. Since nearly 90% of great apes live outside protected areas, targeted conservation in these low-protected areas is also crucial.

Abstract Geographic distribution, as well as evolutionary and biogeographic processes and patterns of marine invertebrate benthic species are strongly shaped by dispersal ability during the life cycle. Remote oceanic islands lie at the brink of complex biotic and abiotic interactions which have significantly influenced the biodiversity patterns we see today. The interaction between geological environmental change and taxon-specific dispersal modes can influence species evolutionary patterns, eventually delimiting species-specific biogeographic regions. In this study, we compare the population genetic patterns of the marine bivalve Cardita calyculata in the northeast Atlantic, discussing the role of Macaronesian islands during past climatic cycles. The genetic structure and diversity patterns were outlined based on SSR-GBAS loci of 165 individuals and on the mitochondrial COI marker of 22 individuals from the Canary Islands, Madeira, Azores and the Mediterranean. The highly structured genetic pattern found among regions and within archipelagos suggests the central role of oceanic islands in promoting the divergence of the species in both the NE Atlantic and the Mediterranean. The high degree of divergence in the COI dataset (> 7%) suggests the existence of potential cryptic speciation that needs to be further explored with a more comprehensive sampling. Such patterns are only congruent with a scenario where C. calyculata populations were maintained during glacial/interglacial cycles, supporting the role of the studied archipelagos as drivers of diversity for marine biota. We stress the importance of developing studies for species with various life history and dispersal modes. In such a way, a more profound understanding of the biogeographic and evolutionary significance of oceanic islands can catalyse directed conservation efforts, especially in the context of the ongoing climate crisis.

Abstract A terrace in a phylogenetic tree space is a region where all trees contain the same set of subtrees, due to certain patterns of missing data among the taxa sampled, resulting in an identical optimality score for a given data set. This was first investigated in the context of phylogenetic tree estimation from sequence alignments using maximum likelihood (ML) and maximum parsimony (MP). It was later extended to the species tree inference problem from a collection of gene trees, where a set of equally optimal species trees was referred to as a “pseudo” species tree terrace which does not consider the topological proximity of the trees in terms of the induced subtrees resulting from certain patterns of missing data. In this study, we mathematically characterize species tree terraces and investigate the mathematical properties and conditions that lead multiple species trees to induce/display an identical set of locus-specific subtrees owing to missing data. We report that species tree terraces are agnostic to gene tree heterogeneity. Therefore, we introduce and characterize a special type of gene tree topology-aware terrace which we call “peak terrace”. Moreover, we empirically investigated various challenges and opportunities related to species tree terraces through extensive empirical studies using simulated and real biological data. We demonstrate the prevalence of species tree terraces and the resulting ambiguity created for tree search algorithms. Remarkably, our findings indicate that the identification of terraces could potentially lead to advances that enhance the accuracy of summary methods and provide reasonably accurate branch support.

Abstract Background This review compiles and synthesises the existing information concerning non-native poeciliid introductions to Africa. The recent upsurge in research on invasive poeciliids has revealed their widespread occurrence in Africa. Results Within the 87 relevant articles, 74% reported on the presence of Gambusia spp., 33% on P. reticulata, 19% on X. hellerii, 11% on X. maculatus, and 5% on other ornamental poeciliids. Overall, poeciliids have been documented as introduced to 25 different countries in Africa. With Gambusia spp. being introduced to 16 countries and P. reticulata to 19 countries. Our results are representative of the current state of research on invasive poeciliids in Africa. There was a concentration of studies in South Africa, with limited research elsewhere. Current distribution data is relatively patchy, although widespread surveys of multiple river systems in Morocco and South Africa, confirmed widespread and abundant established poeciliid populations. The ecological impacts of invasive poeciliids in Africa remain understudied but evidence indicates deleterious effects on native fish, invertebrates, and amphibians, many of which are critically endangered or endemic. Conclusion Current research is limited in reporting from certain countries and ecological impacts. An increased effort to monitor species composition in vulnerable waterbodies, especially in the many African countries where invasive poeciliids are reported, should be completed to reveal further established populations. Future research should prioritise quantifying the ecological impacts of invasive poeciliids in the field and identifying both vulnerable and resistant native ecosystems to guide future management decisions.

Abstract Background Montane ecosystems play crucial roles as global biodiversity hotspots. However, climatic changes and anthropogenic pressure increasingly threaten the stability of montane community dynamics, such as diversity-elevation interactions, creating a challenge in understanding species biogeography and community ecology dynamics in these crucial conservation areas. We examined how varying sampling spatial grains influence small mammal diversity patterns within Kenya’s tallest montane ecosystems. Methods Employing a combination of multidimensional alpha diversity metrics and multisite beta diversity characteristics (species richness, phylogenetic and functional diversity and divergence, and multisite beta diversity) alongside spatial generalized additive multivariate regression analyses, we tested how spatial scaling influences elevational diversity gradient patterns and their associations with environmental and human activity variables. Results The diversity-elevation associations were generally homogeneous across spatial grains; however, idiosyncratic patterns emerged across mountains. The total (taxonomic, phylogenetic, and functional) beta diversity, nestedness, and turnover resultant components monotonically increased or decreased with varying spatial grains. The associations between the diversity patterns and the environmental and human footprint variables increased with spatial grain size but also presented variations across mountains and indices. Species richness and phylogenetic and functional richness indices were more strongly influenced by spatial scale variations than were the divergence and community structure indices in both the diversity distribution patterns and their associations with the environmental and human variables. Conclusions The diversity-elevation and diversity-environment (including human activity pressure) relationships across spatial grains suggest that montane small mammal diversity patterns portray subtle but systematic sensitivity to sampling spatial grain variation and underscore the importance of geographical context in shaping these elevational diversity gradients. For improved effectiveness, conservation efforts should consider these spatial effects and the unique geographical background of individual montane ecosystems.

A survey of large beetles, one centimetre or more in length, on Lord Howe Island, was conducted in August 2022 and the results are discussed. In total, 32 large species were found. This was the first survey made at least one beetle generation after eradication of the rodents in 2019, and there was some evidence of recovery, in particular of the large flightless endemic cerambycid, Xylotoles wollastoni (White, 1856), but also of a leaf beetle, Dematochroma picea (Baly, 1864) and an exotic pest of lawns, Heteronychus arator (Fabricius, 1775). There was also evidence of recovery of Carabidae species after the prolonged dry years of 2016 to 2019.

Abstract In close‐range remote sensing data collected in a forest, occlusion often causes incomplete or sparse point cloud representations of individual trees, impeding accurate 3D reconstruction of tree architecture and estimation of tree height and volume. Recent developments in deep learning (DL) for 3D data have produced approaches for point cloud completion, which could potentially be applied to trees. We explored the potential of a DL approach to fill gaps in dense point clouds representing the main structures of deciduous trees by applying an existing transformer‐based completion model (PoinTr). Complete point clouds are required as training data, but even dense terrestrial laser scanning (TLS) data sets contain gaps caused by occlusion, making it nearly impossible to acquire such data. We therefore investigated the ability of point cloud completion models trained on a range of synthetic data sets to handle occlusion patterns in real‐world point clouds. Despite the limited data set, we successfully fine‐tuned a general pre‐trained completion model to fill gaps within 1 m3 segments of tree point clouds. Fine‐tuning on synthetic tree data improved the model's ability to complete tree objects compared with training on diverse artificial objects. However, the quality of the predictions was influenced by the level of sophistication of the synthetic data. Our results demonstrate that incorporating even limited real‐world TLS data during training can considerably improve completion results but may introduce additional noise in the predictions. 3D point cloud completion with DL has the potential to improve and fill gaps in point clouds of individual trees, facilitating further steps in the processing and analysis of 3D forest data.

Abstract The rapid and repeatable characterization of individual morphology has advanced automated taxonomic classification. The most direct study of evolutionary processes is, however, not from taxonomic description, but rather of the evolution of the traits that comprise individuals and define species. Repeatable signatures of individual morphology are crucial for analysing the response to selection at scale, and thus tracking evolutionary trajectories through time and across species boundaries. Here, we introduce our 3DKMI—an open‐source MATLAB package designed for the study of morphology using three‐dimensional (3D) Krawtchouk moment invariants. The volumetric features derived from the 3D images remain stable under translation, scaling and rotation and, for an image of size 128 × 128 × 128 can be computed in less than 0.1 s. We applied our package as a case study on a collection of 300 X‐ray computed tomography scans of planktonic foraminifera specimens across five species to (1) assess the invariance of the features under different transformations and (2) analyse morphological differences among species based on the extracted characteristics. We show that 3DKMI has the capacity to efficiently and repeatedly characterize the signatures of individual morphology. In the future, we hope that the 3D feature extraction technique 3DKMI will be widely applied to digital collections to advance research in ecology and evolution.

Abstract Close‐kin mark–recapture (CKMR) is a method that allows estimating population census size, among other parameters, through the observed number of pairs that are close‐kin including parent–offspring pairs (POPs) and half‐sibling pairs (HSPs). CKMR models are capable of estimating abundance, fecundity and survival at age using POPs and HSPs from different cohorts. The link between effective population size (Ne) and the number of ‘within‐cohort’ sibling pairs has been noted before but how to actually achieve such an estimate with CKMR has not been previously demonstrated. We show it is possible to use the number of ‘within‐cohort’ sibling pairs along with POPs and ‘different‐cohort’ HSPs to estimate Ne. These can be combined with an estimate of annual variance in number of offspring to estimate the lifetime variance of total reproductive success which can be used to find Ne. We show that the variance in number of offspring produced by adults in a given year is related to the within‐cohort comparisons. Our approach is demonstrated on an individual‐based simulation where we show that the CKMR Ne estimate offers similar results to Ne estimated from methods like linkage disequilibrium. Our methods allow estimating Ne using CKMR while also estimating demographic parameters.

Abstract Widespread fuel accumulation in various strata is increasing the risk of high‐severity, crown‐fires. Knowing the vertical forest structure is a crucial factor for fire management planning. Light detection and ranging (LiDAR) sensors have successfully retrieved the main characteristics of the vertical structure of forests. However, detecting and vertically mapping the various fuel strata that can act as ladder fuels (i.e. fuel arrangements that will bring the fire from the surface to the canopy) is challenging and limits our ability to manage the most hazardous forests. Here we show how using LiDAR data and the LadderFuelsR package, developed in the R platform, can provide an automated tool for analysing the vertical fuel structure of a forest and to calculate crown base height (CBH) at tree‐level, among other parameters. We include a suite of tools integrated into a sequential workflow for: (1) calculating the leaf area density (LAD) profiles of each segmented tree; (2) identifying gaps and the non‐continuous fuel layers present; (3) estimating the vertical distance between fuel layers; and (4) retrieving their base height and depth. Additionally, other functions recalculate previous metrics after considering vertical distances greater than certain threshold and calculates the LAD percentage comprised in each fuel layer removing fuel layers below a specified value. Moreover, it calculates tree's CBH based on three criteria: maximum LAD, and both the largest and the last vertical distance between fuel layers. Additionally, when the LAD profiles showed only one fuel layer with CBH at the minimum base height, it identifies the tree's CBH by performing a segmented linear regression. Finally, a collection of plotting functions is developed to represent all previous metrics. This tool has been tested with different LiDAR sensors and thousands of trees in several Pinus pinaster forest areas in Central Spain, and its accuracy has been evaluated using field‐based tree CBH in Pinus palustris Mills dominated forests in Florida (USA). This tool provides accurate information about the vertical structure of a forest, which can be used for prioritizing treatment areas to reduce fire hazard or identify high crown‐fire risk areas.

Abstract Precipitation channelled down tree stems (stemflow) or into drip points of ‘throughfall’ beneath trees results in spatially concentrated inputs of water and chemicals to the ground. Currently, these flows are poorly characterised due to uncertainties about which branches redirect rainfall to stemflow or throughfall drip points. We introduce a graph theoretic algorithm that ‘prunes’ quantitative structural models of trees (derived from terrestrial LiDAR) to identify branches contributing to stemflow and those contributing to throughfall drip points. To demonstrate the method's utility, we analysed two trees with similar canopy sizes but contrasting canopy architecture and rainfall partitioning behaviours. For both trees, the branch ‘watershed’ area contributing to stemflow (under conditions assumed to represent moderate precipitation intensity) was found to be only half of the total ground area covered by the canopy. The study also revealed significant variations between trees in the number and median contribution areas of modelled throughfall drip points (69 vs. 94 drip points tree−1, with contributing projected areas of 28.6 vs. 7.8 m2 tree−1, respectively). Branch diameter, surface area, volumes and woody area index of components contributing to stemflow and throughfall drip points may play a role in the trees' differing rainfall partitioning behaviours. Our pruning algorithm, enabled by the proliferation of LiDAR observations of canopy structure, promises to enhance studies of canopy hydrology. It offers a novel approach to refine our understanding of how trees interact with rainfall, thereby broadening the utility of existing LiDAR data in environmental research.

Abstract The democratisation of next‐generation sequencing has vastly increased the availability of sequencing data from metabarcoding. However, to effectively prepare these metabarcoding data for subsequent analysis, researchers must consistently apply several different bioinformatic tools—including those which denoise reads, cluster sequences and assign taxonomic identities. This often creates a bioinformatics bottleneck in workflows for non‐specialists due to obstacles around: (a) integrating different tools, (b) the inability to easily modify and rerun bioinformatic pipelines involving non‐scripted (‘point‐and‐click’) elements and (c) the multiple outputs that may be required of a single dataset (e.g. amplicon sequence variants [ASVs] and operational taxonomic units [OTUs]), which often results in users running pipelines multiple times. Here, we introduce SimpleMetaPipeline, an open‐source bioinformatics pipeline implemented in R, which addresses these obstacles. SimpleMetaPipeline integrates the most robust and commonly used existing bioinformatic tools in a single reproducible pipeline, with a streamlined choice of parameters, to generate a sequence data table containing alternative clustering and assignment options. SimpleMetaPipeline accepts demultiplexed paired‐end and single reads from multiple sequencing runs. We describe the pipeline and demonstrate how alternative annotations enable the easy implementation of multi‐algorithm agreement tests to strengthen inferences. SimpleMetaPipeline represents a valuable addition to the existing library of pipelines, providing easy and reproducible bioinformatics, including a range of commonly desired clustering and assignment options, such as OTUs and ASVs.

Abstract The PicoCam system is a multi‐camera photogrammetry rig used for generating high‐resolution 3D models of animals in the field, or preserved specimens in laboratory or museum settings. The digital measurement of 3D models is increasingly useful for studying body shape. However, methods that capture sub‐millimetric detail often do so at the cost of portability and versatility; this system aims to bridge this gap. The PicoCam system employs 3D digital photogrammetry, a process that generates accurate, full‐colour, 3D models from sequences of photographs. By using six cameras and a rotating base, the system is able to capture multiple angles in rapid succession—a key advantage for both 3D‐imaging live specimens and efficiently scanning museum specimens. Through the use of macro lenses and high‐resolution camera sensors, this system can capture sub‐millimetric detail without sacrificing portability. In this study, we 3D imaged the bills of 19 species of hummingbirds using the PicoCam system and measured length, height, width, surface area and volume of their bills. We examined eight species in the field and 11 from the Burke Museum in Seattle. We chose Hummingbird bills as a model system, as their fine‐scale interspecific differences in 3D shape can have significant functional and behavioural implications, and could tell us more about how these traits predict habitat and resource use. The prospect of a common 3D‐imaging method for both museum and field use is compelling when documenting structures' shape within and among species. The PicoCam system is also valuable for quantifying the 3D shape of fine‐scale phenotypes (like hummingbird bills) that benefit from digital measurement, preservation, and improved accessibility. Finally, the PicoCam system allows ‘digital 3D collection’, by which the shape of biological structures in the field can be recorded and stored in a public database without the need to collect a specimen. This opens the door to studies in which multiple 3D image captures of the same individual across different time scales permit 3D shape/colour comparisons (e.g. seasonal, ontogenetic changes).

Abstract Simulation studies are essential tools to assess statistical methods. Functioning as controlled experiments, simulations generate data from known underlying processes. However, unclear or incomplete reporting of simulation studies can impact their interpretability and reproducibility, potentially leading to the misuse of statistical methods. While Morris et al. (2019, Stat Med, 38, p. 2074) recently provided guidance on the planning and conduct of simulation studies for statistical method evaluation, there is currently no comprehensive set of reporting guidelines in ecology and evolutionary biology. Here, we propose 11 reporting items for statistical simulation studies extending on Morris and colleagues' guidance. These items span across three stages: planning, coding and analysis. We also clarify the terminology related to statistical components and the broad purposes of statistical simulation studies. To highlight our proposed reporting items with current practices, we surveyed 100 articles in ecology and evolution journals that included a simulation study evaluating a statistical method. Our survey found room for improvement in more transparent reporting to ensure clear evaluation of statistical methods. Most notably, only a small proportion of articles reported a Monte Carlo uncertainty (17%; 17 out of 98), and 32% (32 out of 100) articles did not provide code. Beyond the proposed reporting items, we discuss the benefits of open science tools to enhance the reproducibility of simulation studies. Specifically, we propose the registration of statistical simulation studies to enhance planning, reporting and collaboration. We aim to instigate discussions to improve the reporting of simulation studies for statistical method research. The reporting items we propose, along with open science tools, serve as a template for developing standards and guidelines for simulation studies evaluating statistical methods. These reporting guidelines will help enhance reproducibility and indirectly encourage more consideration in the design and conduct of these simulation studies.

Abstract Global change is impacting biodiversity across all habitats on earth. New selection pressures from changing climatic conditions and other anthropogenic activities are creating heterogeneous ecological and evolutionary responses across many species' geographic ranges. Yet we currently lack standardised and reproducible tools to effectively predict the resulting patterns in species vulnerability to declines or range changes. We developed an informatic toolbox that integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity, genotype‐environment associations and genomic offset) to estimate population vulnerability. In our toolbox, functions and data structures are coded in a standardised way so that it is applicable to any species or geographic region where appropriate data are available, for example individual or population sampling and genomic datasets (e.g. RAD‐seq, ddRAD‐seq, whole genome sequencing data) representing environmental variation across the species geographic range. To demonstrate multi‐species applicability, we apply our toolbox to three georeferenced genomic datasets for co‐occurring East African spiny reed frogs (Afrixalus fornasini, A. delicatus and A. sylvaticus) to predict their population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced from a previous study using data for two European bat species (Myotis escalerai and M. crypticus). Our framework sets the stage for large scale, multi‐species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity and landscape barriers.

Abstract Effective approaches are needed to conserve the planet's remaining wildlife and wilderness landscapes, especially concerning global biodiversity conservation targets. Here, we present a new software system called EarthRanger: an open‐source platform built to help monitor, research and manage ecosystems. EarthRanger consists of seven main components (Core Server, API, Storage, Gundi, Web App, Mobile App, Ecoscope) that provide functionality for data (i) aggregation & collection, (ii) storage & management, (iii) real‐time and post hoc analysis, (iv) visualisation and (v) dissemination. The mobile application provides field‐based data recording and visualisation tools. EarthRanger may be deployed for single project use or can aggregate across multiple geographies as a centralised hub. EarthRanger can be used to collect standardised tracking data (e.g. from wildlife collars, vehicles and ranger patrols) and configurable event information (e.g. a singular recording with associated user‐defined attribute information such as a wildlife sighting or encounter with a poacher). Since development began in 2015, the platform has (at the time of writing) been deployed at over 500 sites across 70 countries and with myriad configurations and objectives. EarthRanger has improved the ability to monitor data feeds and manage conservation‐related operations in real time. For instance, the deployment of EarthRanger by African Parks has led to the removal of over 50,000 snares, steady population growth of key species of concern and near cessation of poaching. In Liwonde's protected area, enhanced mitigation efforts supported by EarthRanger reduced the number of deaths from wildlife conflict by more than 91%. EarthRanger is also providing a platform to enhance standardisation, aggregation, transfer and long‐term storage of ecological information and promote collaboration between groups conducting protected area management and ecology and biodiversity research.

Abstract Monitoring environmental conditions over time is essential for understanding how species regulate those conditions to satisfy their physiological needs. Variation in ultraviolet (UV) light exposure, for instance, is crucial for numerous taxa, influencing behaviour as well as essential physiological processes like vitamin D3 synthesis. Yet, despite these considerations, no commercially available data loggers exist to record UV exposures over time, preventing inquiry into this important but neglected fitness demand. To overcome this challenge, I designed the first UV data logger, custom built on the open‐source Arduino platform. This device logs UV exposures (in voltage or converted to UV index) and date‐time information for each UV reading, at user‐defined intervals. The integration of a low‐power timer into the assembly, and its weather‐resistant housing, enables long‐term use (at least several months). The cost of one device (including housing) is under £45/$55 USD. Calibration and performance tests reveal that this device is reliable under various weather conditions and produces accurate UV readings under both artificial lighting and sunlight. Both the device and its customised housing can be easily replicated and expanded upon (e.g. inclusion of additional sensors). Overall, this device represents a crucial first step in our ability to better characterise UV exposure patterns in habitats for physiological ecology studies. Exposure to UV light is adaptive for many types of organisms, both in the wild and in captivity (e.g. zoos and private hobbyists), and so I expect a broad array of scientific and public users alike to benefit from using this device.

Abstract Reconstructing past ecological population dynamics and demographic events is crucial for understanding the dynamics of ecological processes, evaluating the impact of environmental changes and making informed conservation decisions. In forest ecosystems, retrodiction (i.e. the backward projection of ecological populations) plays a pivotal role in understanding historical forest carbon levels and the factors that have influenced their variation over time, because forest demography is a major determinant of the amount of carbon stored in forest ecosystems. The persistent lack of quantitative methods has been a significant obstacle in retrodicting forest demography, especially in applications of a broad geographical scale. While there is a wealth of models for predicting future forest conditions, models that can project these conditions backward in time are scarce. This study presents reverse matrix model (RMM), an innovative retrodiction modelling approach grounded in the principles of transition matrix models. RMM is designed to deduce past demographic characteristics of ecological populations using current data, making it one of the first models capable of projecting the fine‐scale dynamics of forest demography into the past. We assessed the retrodictive performance of RMM by fitting it to a dataset of a disturbed tropical rainforest in French Guiana in 2001–2023, then comparing the retrodictions to observations back to 1983 when the disturbance occurred. We further empirically evaluated the viability of retrodiction over a defined duration by inverting the density‐dependent matrix model by Lin et al. (1996), which predicts the dynamics of northern hardwoods in the United States. The case studies demonstrate significant potential for RMM application in various domains of forestry and conservation, including ecosystem management and conservation planning, global change impact assessment and biodiversity monitoring.

Abstract Estimating and monitoring plant population size is fundamental for ecological research, as well as conservation and restoration programs. High‐resolution imagery has potential to facilitate such estimation and monitoring. However, remotely sensed estimates typically have higher uncertainty than field measurements, risking biased inference on population status. We present a model that accounts for false negative (missed plants) and false positive (misclassified or double‐counted plants) error in counts from high‐resolution imagery via integration with ground data. We apply it to estimate the abundance of a foundational shrub species in post‐wildfire landscapes in the western United States. In these landscapes, plant recruitment is crucial for ecological recovery but locally patchy, motivating the use of spatially extensive measurements from unoccupied aerial systems (UAS). Integrating >16 ha of UAS imagery with >700 georeferenced field plots, we fit our model to generate insights into the prevalence and drivers of observation errors associated with classification algorithms used to distinguish individual plants, relationships between abundance and landscape context, and to generate spatially explicit maps of shrub abundance. Raw counts of plant abundance in high‐resolution imagery resulted in substantial false negative and false positive observation errors. The probability of detecting (p) adult plants (≥0.25 m tall) varied between sites within 0.52

Abstract Spatial modelling approaches to aid land‐use decisions which benefit both wildlife and humans are often limited to the comparison of pre‐determined landscape scenarios, which may not reflect the true optimum landscape for any end‐user. Furthermore, the needs of wildlife are often under‐represented when considered alongside human financial interests in these approaches. We develop a method of addressing these gaps using a case‐study of wild bees in the UK, an important group whose declines may adversely affect both human economies and surrounding ecosystems. By combining the genetic algorithm NSGA‐II with a process‐based pollinator model which simulates bee foraging and population dynamics, Poll4pop, we ‘evolve’ a typical UK agricultural landscape to identify optimum land cover configurations for three different guilds of wild bee. These configurations are compared to those resulting from optimisations for farm income alone, as well as optimisations that seek a compromise between bee populations and farm income objectives. We find that the land cover proportions in landscapes optimised for each bee guild reflect their nesting habitat preferences rather than foraging preferences, highlighting a limiting resource within the study landscape. The spatially explicit nature of these optimised landscapes illustrates how improvement for a given target species may be limited by differences between their movement range and the scale of the units being improved. Land cover composition and configuration differ significantly in landscapes optimised for farm income and bee population growth simultaneously and illustrate how human agents are required to compromise much more when the multifaceted nature of biodiversity is recognised and represented by multiple objectives within an optimisation framework. Our methods provide a way to quantify the extent to which real‐life landscapes promote or compromise objectives for different landscape end‐users. Our investigation suggests that optimisation set‐up (decision‐unit scales, traditional choice of a single biodiversity metric) can bias outcomes towards human‐centric solutions. It also demonstrates the importance of representing the individual requirements of different actors with different landscape‐level needs when using genetic algorithms to support biodiversity‐inclusive decision‐making in multi‐functional landscapes.

Abstract In this paper, we explain how to obtain sets of descriptors of the spatial variation, which we call “predictive Moran's eigenvector maps” (pMEM), that can be used to make spatially explicit predictions for any environmental variables, biotic or abiotic. It unites features of a method called “Moran's eigenvector maps” (MEM) and those of spatial interpolation, and produces sets of descriptors that can be used with any other modelling method, such as regressions, support vector machines, regression trees, artificial neural networks and so on. The pMEM are the predictive eigenvectors produced by using a distance‐weighting function (DWF) in the construction of MEM. Seven types of pMEM, each associated with one of seven different DWFs, were defined and studied. We performed a simulation study to determine the power of different types of pMEM eigenfunctions at making accurate predictions for spatially structured variables. We exemplified the application of the method to the prediction of the spatial distribution of 35 Oribatid mites living in a peat moss (Sphagnum) mat on the shore of a Laurentian lake. We also provide an R language package called pMEM to make calculations easily available to end users. The results indicate that anyone of the pMEMs obtained from the different DWFs could be the best suited one to predict spatial variability in a given data set. Their application to the prediction of mite distributions highlights the capability of pMEMs for predicting distributions, and for providing spatially explicit estimates of environmental variables that are useful for predicting distributions.

Abstract Automated radio telemetry systems are one of the most widely applicable methods for tracking wildlife at fine spatiotemporal scales. A growing trend is for these systems to apply large networks of receivers to detect radio signal strength (RSS) from radio‐tagged individuals. Analytical methods to derive position estimates using RSS localisation, however, are relatively underdeveloped in the field of wildlife tracking. Here, we apply approaches from indoor positioning systems to develop a new method, radio fingerprinting, for localising radio‐tagged animals in structurally complex, outdoor environments. This method characterises the RSS patterns at known locations to generate a radio map of the study area, which is then used to predict the location of new RSS patterns. We conducted field tests to evaluate the localisation accuracy of radio fingerprinting relative to multilateration, a commonly used method for RSS localisation. To do so, we established an experimental receiver network covering multiple habitat types and compared the localisation accuracy of radio fingerprinting to multilateration. Additionally, we evaluated how a variety of features characteristic of typical tracking data sets affected the accuracy of both methods. While both methods had a similar median error under ideal conditions (~30 m), radio fingerprint localisation method offered several advantages over multilateration. Multilateration localisation estimates were highly affected by missed detections from the nearest receiver to the test point, which occurred in 30% of cases. In these cases, the median error was 103 m, over a 3.5‐fold increase. Distance to the nearest receiver also biased multilateration estimates with error increasing as the distance increased. Additionally, errors from multilateration estimates were higher in more densely vegetated areas. In contrast, fingerprinting position estimates were largely robust to each of these scenarios. Automated radio telemetry enables the fine‐scale, continuous tracking of range‐resident animals. We present radio fingerprinting as a localisation method in outdoor environments where standard localisation methods are error‐prone due to habitat heterogeneity and missed detections. This approach can be applied to any automated radio telemetry hardware and to any study system where a radio map can be generated.

Abstract Occupancy models were originally developed to better understand species distribution while accounting for imperfect detection. Because species distribution is not only shaped by habitat quality but also by the ability of individuals to reach suitable habitats, spatial dynamic occupancy models have been proposed to extend the original framework by defining that site colonisation was a function of the Euclidean distance to occupied sites. However, not all sites in the landscape are equally accessible due to the presence of barriers, that of corridors, etc. To account for connectivity between sites, the Euclidean distance has recently been replaced by a least‐cost path distance, which explicitly accounts for landscape resistance, but assumes that individuals will follow the optimal route. To relax this assumption, we first developed a new spatial occupancy model that incorporates commute‐time distance derived from circuit theory to model accessibility across sites. This distance has the advantage of modelling movement as a random walk and accounting for the fact that colonisation could be achieved from multiple paths. Our approach allows for the explicit estimation of landscape connectivity from detection/non‐detection data and a direct measure of connectivity uncertainty. We implemented the model in the Bayesian framework using the nimble R package, which allows useful R connectivity functions to be called from within the model. Second, we carried out a simulation study to assess the performance of our model by considering four scenarios depicting an increasing level of landscape resistance. Third, to illustrate our new approach, we studied the recolonisation of two carnivores in France. We quantified the degree to which rivers facilitate Eurasian otter (Lutra lutra) colonisation and highways impede Eurasian lynx (Lynx lynx) colonisation. Overall, spatial occupancy models provide a flexible framework to accommodate any distance metric designed to align with species dispersal ecology.

Abstract Modern methods for quantifying, predicting and mapping species distributions have played a crucial part in biodiversity conservation. Occupancy models have become a popular choice for analysing species occurrence data due to their ability to separate out the observational error induced by imperfect detection of a species, and the sources of bias affecting the occupancy process. However, the spatial and temporal variation in occupancy that is not accounted for by environmental covariates is often ignored or modelled through simple spatial structures as the computational costs of fitting explicit spatio‐temporal models is too high. In this work, we demonstrate how Integrated Nested Laplace Approximation (INLA) may be used to fit complex spatio‐temporal occupancy models and how the R‐INLA package can provide a user‐friendly interface to make such complex models available to users. We show how occupancy models, provided some simplification on the detection process is assumed, can be framed as latent Gaussian models and, as such, benefit from the powerful INLA framework. A large selection of complex modelling features, and random effect models, including spatio‐temporal models, have already been implemented in R‐INLA. These also become available for occupancy models, providing the user with an efficient, reliable and flexible toolbox. We illustrate how INLA provides a flexible and computationally efficient framework for developing and fitting complex occupancy models using two complex case studies. Through these, we show how different spatio‐temporal models that include spatial‐varying trends, smooth terms and spatio‐temporal random effects can be fitted to aggregated detection/non‐detection data. At the cost of limiting the complexity of the detection model structure, INLA can incorporate a range of rather complex structures in the ecological process of interest and hence, extend the functionality of occupancy models. The limitations of occupancy models in terms of scalability for large spatio‐temporal data sets remain a challenge and an active area of research. INLA‐based occupancy models provide an alternative inferential and computational framework to fit complex spatio‐temporal occupancy models. The need for new and more flexible computationally efficient approaches to fit such models makes INLA an attractive option for addressing complex ecological problems, and a promising area of research.

Abstract The survival of animals is impacted by landscapes of spatially varying mortality factors including habitat type, predation risk or harvest risk, among others. Characterization of these spatial mortality processes is important for managing animal populations and their habitats, yet this information has proved challenging to capture. Advances in telemetry now make it possible to monitor tagged individuals' locations through time for a wide range of taxa, providing opportunity to assess movement and mortality simultaneously through spatial time‐to‐event data. Existing time‐to‐event modelling frameworks have largely ignored spatially varying mortality processes or have treated an animal's location as fixed at a regional level. Here we present a general spatial survival model for analysing time‐to‐event data arising from animal telemetry. Our model has a flexible Cox regression form and can estimate the effects of conventional non‐spatial risk factors (size, seasonality, etc.), spatial covariates (e.g. habitat type) and spatial variation in risk not explained by covariates on mortality. We show how to fit our model using Bayesian methods and demonstrate applications of our model with several simulated examples and two animal telemetry case studies. Our model produced consistent and unbiased parameter estimates throughout simulations with a variety of spatial and non‐spatial hazards. In the first case study, data from 147 tagged caribou in British Columbia, Canada, revealed a spatially heterogeneous mortality landscape with caribou survival varying by elevation, likely in response to space use by predators. Our second case study involved a dataset of 390 acoustically tagged Atlantic cod in a southern Norwegian fjord where a marine protected area (MPA) was established during the study. We found that the MPA led to a shift from mostly fishing mortality to mostly natural mortality within the fjord and that these risks had markedly different spatial hazard patterns. Our spatial time‐to‐event model can make use of data from a variety of widely used telemetry technologies to characterize landscapes of mortality risks for different taxa. Our work provides new opportunities to inform the spatial ecology and management of fish and wildlife populations.

Abstract Background Great apes are a global conservation concern, with anthropogenic pressures threatening their survival. Genetic analysis can be used to assess the effects of reduced population sizes and the effectiveness of conservation measures. In humans, autosomal short tandem repeats (aSTRs) are widely used in population genetics and for forensic individual identification and kinship testing. Traditionally, genotyping is length-based via capillary electrophoresis (CE), but there is an increasing move to direct analysis by massively parallel sequencing (MPS). An example is the ForenSeq DNA Signature Prep Kit, which amplifies multiple loci including 27 aSTRs, prior to sequencing via Illumina technology. Here we assess the applicability of this human-based kit in African great apes. We ask whether cross-species genotyping of the orthologs of these loci can provide both individual and (sub)species identification. Results The ForenSeq kit was used to amplify and sequence aSTRs in 52 individuals (14 chimpanzees; 4 bonobos; 16 western lowland, 6 eastern lowland, and 12 mountain gorillas). The orthologs of 24/27 human aSTRs amplified across species, and a core set of thirteen loci could be genotyped in all individuals. Genotypes were individually and (sub)species identifying. Both allelic diversity and the power to discriminate (sub)species were greater when considering STR sequences rather than allele lengths. Comparing human and African great-ape STR sequences with an orangutan outgroup showed general conservation of repeat types and allele size ranges. Variation in repeat array structures and a weak relationship with the known phylogeny suggests stochastic origins of mutations giving rise to diverse imperfect repeat arrays. Interruptions within long repeat arrays in African great apes do not appear to reduce allelic diversity. Conclusions Orthologs of most human aSTRs in the ForenSeq DNA Signature Prep Kit can be analysed in African great apes. Primer redesign would reduce observed variability in amplification across some loci. MPS of the orthologs of human loci provides better resolution for both individual and (sub)species identification in great apes than standard CE-based approaches, and has the further advantage that there is no need to limit the number and size ranges of analysed loci.

Abstract Fish early-stages constitute useful indicators of the states of marine ecosystems, as well as important fishery resources. Given the spectacular phenotypic changes during ontogeny, and the paucity of diagnostic morphological characters at the species level, the identification of fish early-stages is a challenging task. DNA barcoding, the use of the mitochondrial gene of the cytochrome c oxidase subunit I (COI) as an internal species tag, opened new perspectives for the identifications of both larval fish and fish eggs. However, the accuracy of the identifications assisted by DNA barcoding are dependent of the completeness of the DNA barcode reference libraries used to assigned unknown sequences to known species. Here, we built a DNA barcode reference library for 113 species of larval fish and 85 species of fish eggs involving the production of 741 newly generated DNA barcodes from South China Sea (63 localities). Together with 514 DNA barcodes mined from Genbank for 116 species from the South China Sea regions, a reference library including 1255 DNA barcodes for 308 species (248 locations) was assembled. The present study emphasizes the importance of integrating DNA barcoding to large scale inventories of early stages, as DNA-based species delimitation analyses delimited 305 molecular operational taxonomic units (MOTUs) and multiple cases of discordance with morphological identifications were detected. Cryptic diversity is detected with 14 species displaying two MOTUs and a total of 23 species were lumped into 11 MOTUs due to low interspecific divergence and/or mixed lineages.

Abstract The Western honey bee (Apis mellifera) subspecies exhibit local adaptive traits that evolved in response to the different environments that characterize their native distribution ranges. An important trait is the cuticular hydrocarbon (CHC) profile, which helps to prevent desiccation and mediate communication. We compared the CHC profiles of six European subspecies (A. m. mellifera, A. m. carnica, A. m. ligustica, A. m. macedonica, A. m. iberiensis, and A. m. ruttneri) and investigated potential factors shaping their composition. We did not find evidence of adaptation of the CHC profiles of the subspecies to the climatic conditions in their distribution range. Subspecies-specific differences in CHC composition might be explained by phylogenetic constraints or genetic drift. The CHC profiles of foragers were more subspecies-specific than those of nurse bees, while the latter showed more variation in their CHC profiles, likely due to the lower desiccation stress exerted by the controlled environment inside the hive. The strongest profile differences appeared between nurse bees and foragers among all subspecies, suggesting an adaptation to social task and a role in communication. Foragers also showed an increase in the relative amount of alkanes in their profiles compared to nurses, indicating adaptation to climatic conditions.

Abstract In order to clarify the chloroplast genomes and structural features of ten Ilex species and provide insights into the phylogeny and genome evolution of the genus Ilex, we conducted a comparative analysis of chloroplast genomes using bioinformatics methods. The chloroplast genomes of ten Ilex species were obtained, and their structural features and variations were compared. The results indicated that all chloroplast genomes in the genus Ilex exhibit a double-stranded circular structure, with sizes ranging from 157,356 to 158,018 bp, showing minimal differences in size. The chloroplast genomes of the ten Ilex species have a relatively conservative gene count, with a total of 134 to 135 genes, including 88 or 89 protein-coding genes, and a conserved number of 8 rRNA genes. Each chloroplast genome contains 3 to 123 SSR (Simple Sequence Repeat) sites, predominantly composed of mononucleotide and trinucleotide repeats, with no detection of pentanucleotide or hexanucleotide repeats. The variation in dispersed repeat sequences among Ilex species is minimal, with a total repeat sequence number ranging from 1 to 14, concentrated in the length range of 30 to 42 base pairs. The expansion and contraction of chloroplast genome boundaries among Ilex species are relatively stable, with only minor variations observed in individual species. Variations in non-coding regions are more pronounced than those in coding regions, with the variability in the Large Single Copy region (LSC) being the highest, while the variability in the Inverted Repeat region A (IRa) is the lowest. The divergence time among Ilex species was estimated using the MCMC-tree module, revealing the evolutionary relationships among these species, their common ancestors, and their differentiation throughout the evolutionary process. The research findings provide a valuable reference for the systematic study and molecular marker development of Ilex plants.

Abstract Background Sanniang Bay (SNB) and Dafeng River (DFR), located in the northern Beibu Gulf, is well-known as one of the eight habitats for humpback dolphins in China. This region is representative of typical estuarine and bay ecosystems and produce complex hydrodynamic seawater conditions. Moreover, anthropogenic pressure, such as eutrophication and large-scale infrastructure projects, have caused ongoing habitat deterioration and loss. It is urgent to know the phytoplankton community and their relationships with environmental factors in this region. Results In this study, we assessed the diversity and assembly mechanisms of phytoplankton communities, as well as their relationship with the physicochemical characteristics of seawater in SNB and DFR region using 18 S rDNA metabarcoding analysis. The results showed that seasonal changes markedly impacted the alpha diversity of the phytoplankton community. From March to July, with the average temperature increasing from 25.2℃ to 28.1℃,the Shannon or Species Richness were negatively correlated with temperature. During hot season (in Sep, average temperature 32.1℃), phytoplankton diversity was negatively correlated with nutrients (NH4 +, NO3 −, PO4 3−, TN). Additionally, during the rainy season, the Bray-Curtis similarity of the phytoplankton community was significantly lower than during the dry season. In March, the distance among the sampling sites was most strongly and positively correlated with the Bray-Curtis dissimilarity. Stochastic processes, specifically dispersal limitation and ecological drift, are the primary drivers of community assembly, while deterministic assembly processes (mainly heterogeneous selection) contribute a relatively minor portion (

Abstract Background Heelwalkers possess a highly modified tarsal attachment system. All extant species lift the distalmost tarsomere permanently off the substrate and primarily use their euplantulae for locomotion. The combination of a smooth adhesive pad (arolium) on the pretarsus and fibrillary attachment pads on the euplantulae offers valuable insights for translational approaches, but its infra-order diversity remains unexplored. Results We explored the morphology of the tarsal attachment apparatus of Mantophasmatodea based on a representative taxon sampling spanning a large fraction of species of this group and compared morphological differences in the specialized morphology of this system across species and sexes. Our scanning electron microscope investigation of the tarsi of 11 species (52% of all described extant species) revealed an overall very consistent ground pattern and almost no specific adaptations. There are only minor, but mostly clade-specific differences in the shape of the adhesive setae on the tarsal euplantulae and in the morphology and density of the acanthae on the pretarsal arolium. Both features differ primarily between Austrophasmatidae in comparison to the remaining Mantophasmatodea taxa. Conclusion We conclude that the strong specialization of the mantophasmatodean tarsal attachment sufficiently copes with the diversity of substrates the insects are exposed to.

Abstract Background Evolution continues to be one of the most difficult biological topics to teach, warranting innovative pedagogical tools and assessment strategies for enhancing evolutionary instruction. A major advance in measuring the evolution knowledge of undergraduate students came with the development of the Conceptual Assessment of Natural Selections (CANS). In this study, we use the CANS to measure knowledge and learning of natural selection in a large (N > 6000) sample of undergraduate students to expand upon prior validity testing of this instrument and advance knowledge of student evolutionary reasoning. We apply the Rasch measurement framework to examine if the CANS productively measures the intended construct and investigate the patterns of knowledge and learning about evolution among students with different backgrounds and demographic characteristics. Results While a unidimensional Rasch model demonstrated acceptable reliabilities and fit for most of the CANS items, some items showed problematic fit statistics and were resistant to instruction. The instrument items also did not span the full range of student abilities, which suggests relatively low measurement precision. Our large sample also allowed rigorous tests of multidimensionality, revealing the presence of multiple dimensions or constructs, some of which may not be intentional. These results generated specific item-level recommendations for improving this instrument. Using Rasch measures to examine learning patterns, we found that pre-test evolution knowledge was low but that there were high learning gains by the end of the course. However, some concept categories were found to be more difficult than others, suggesting the need for more attention to these areas by instructors. We also identified pre-test disparities in evolutionary knowledge by socially defined race and biological sex, yet students from all groups achieved comparable learning gains at the end of the course. Conclusion The CANS holds great potential to generate critical insights about student evolutionary reasoning and provide information about which instructional approaches most effectively mitigate the notable knowledge disparities among students. We leverage the findings of this study to propose tangible ways in which this instrument may be improved in order to better achieve both of these goals.

Abstract Background Early embryogenesis is characterized by dramatic cell proliferation and movement. In most insects, early embryogenesis includes a phase called the uniform blastoderm, during which cells evenly cover the entirety of the egg. However, the embryo of the German cockroach, Blattella germanica, like those of many insects within the super order Polyneoptera, does not have a uniform blastoderm; instead, its first cells condense rapidly at the site of a future germband. We investigated early development in this species in order to understand how early gene expression is or is not conserved in these insect embryos with distinct early cell behaviors. Results We present a detailed time series of nuclear division and distribution from fertilization through germband formation and report patterns of expression for the early patterning genes hunchback, caudal, and twist in order to understand early polarization and mesoderm formation. We show a detailed time course of the spatial expression of two genes involved in the segmentation cascade, hedgehog and even-skipped, and demonstrate two distinct dynamics of the segmentation process. Conclusions Despite dramatic differences in cell distribution between the blastoderms of many Polyneopteran insects and those of more well-studied developmental models, expression patterns of early patterning genes are mostly similar. Genes associated with axis determination in other insects are activated relatively late and are probably not maternally deposited. The two phases of segmentation—simultaneous and sequential—might indicate a broadly conserved mode of morphological differentiation. The developmental time course we present here should be of value for further investigation into the causes of this distinct blastoderm type.

Abstract Background With the advances in high-throughput sequencing and bioinformatic pipelines, mitochondrial genomes have become increasingly popular for phylogenetic analyses across different clades of invertebrates. Despite the vast rise in available mitogenomic datasets of molluscs, one class of aplacophoran molluscs – Solenogastres (or Neomeniomorpha) – is still neglected. Results Here, we present six new mitochondrial genomes from five families of Solenogastres (Amphimeniidae, Gymnomeniidae, Proneomeniidae, Pruvotinidae, Simrothiellidae), including the first complete mitogenomes, thereby now representing three of the four traditional orders. Solenogaster mitogenomes are variable in size (ranging from approximately 15,000 bp to over 17,000 bp). The gene order of the 13 protein coding genes and two rRNA genes is conserved in three blocks, but considerable variation occurs in the order of the 22 tRNA genes. Based on phylogenetic analyses and reconstruction of ancestral mitochondrial genomes of Aculifera, the position of (1) trnD gene between atp8 and atp6, (2) trnT and P genes between atp6 and nad5, and (3) trnL1 gene between G and E, resulting in a ‘MCYWQGL1E’-block of tRNA genes, are all three considered synapomorphies for Solenogastres. The tRNA gene block ‘KARNI’ present in Polyplacophora and several conchiferan taxa is dissolved in Solenogastres. Conclusion Our study shows that mitogenomes are suitable to resolve the phylogenetic relationships among Aculifera and within Solenogastres, thus presenting a cost and time efficient compromise to approach evolutionary history in these clades.

Abstract Background Isolating phylogenetic signal from morphological data is crucial for accurately merging fossils into the tree of life and for calibrating molecular dating. However, subjective character definition is a major limitation which can introduce biases that mislead phylogenetic inferences and divergence time estimation. The use of quantitative data, e.g., geometric morphometric (GMM; shape) data can allow for more objective integration of morphological data into phylogenetic inference. This systematic review describes the current state of the field in using continuous morphometric data (e.g., GMM data) for phylogenetic reconstruction and assesses the efficacy of these data compared to discrete characters using the PRISMA-EcoEvo v1.0. reporting guideline, and offers some pathways for approaching this task with GMM data. A comprehensive search string yielded 11,123 phylogenetic studies published in English up to Oct 2023 in the Web of Science database. Title and abstract screening removed 10,975 articles, and full-text screening was performed for 132 articles. Of these, a total of twelve articles met final inclusion criteria and were used for downstream analyses. Results Phylogenetic performance was compared between approaches that employed continuous morphometric and discrete morphological data. Overall, the reconstructed phylogenies did not show increased resolution or accuracy (i.e., benchmarked against molecular phylogenies) as continuous data alone or combined with discrete morphological datasets. Conclusions An exhaustive search of the literature for existing empirical continuous data resulted in a total of twelve articles for final inclusion following title/abstract, and full-text screening. Our study was performed under a rigorous framework for systematic reviews, which showed that the lack of available comparisons between discrete and continuous data hinders our understanding of the performance of continuous data. Our study demonstrates the problem surrounding the efficacy of continuous data as remaining relatively intractable despite an exhaustive search, due in part to the difficulty in obtaining relevant comparisons from the literature. Thus, we implore researchers to address this issue with studies that collect discrete and continuous data sets with directly comparable properties (i.e., describing shape, or size).

Abstract Background Few animal populations have been studied under the framework of the OCBIL theory, which addresses the ecology and evolution of biodiversity on old climatically buffered infertile landscapes. Available genetic data challenge the low connectivity and high genetic differentiation predicted for isolated tepui-summit vertebrate communities, suggesting potential dispersal among summits. However, the OCBIL theory posits reduced dispersibility, enhanced resilience to habitat fragmentation and inbreeding due to small populations. We tested these hypotheses by conducting the first analytic evaluation of the spatial ecology and population biology of a tepui-summit vertebrate at multiple spatial scales. Results We used harmonic radar tracking (100 individuals/448 points of contact) and capture-mark-recapture data (596 individuals captured/52 recaptured) to reveal the temporal niche, microhabitat use, population size, and dispersal abilities of the tepui-summit endemic toad Oreophrynella quelchii on Roraima-tepui. Abundance was determined using a closed population model incorporating sources of variation in capture probability. We tested the relative influence of biotic and abiotic variables on distances moved through model selection. Our data indicate that the population size of O. quelchii is remarkably large (ca. 12 million individuals), with strong seasonal demographic fluctuations. Ecology and observed limited spatial movements challenge the likelihood of active dispersal among tepui tops in this species. Our results are counter to those predicted by the available genetic data but support two hypotheses of the OCBIL theory: reduced dispersibility and enhanced resilience. However, they do not support the expectation of a small refugial population size. Conclusion We postulate that the insular, hostile tepui-summit environment tends to produce robust demographic populations, likely to buffer stochastic adverse environmental effects, rather than diversity, as observed in much younger post-Pleistocene Neotropical landscapes. Our results draw attention to the value of faunal studies using an OCBIL framework to better understand the ecology and evolution of this unique biota worldwide.

Abstract Background White forsythia (Abeliophyllum distichum) is an endangered Korean Peninsula endemic that has been subjected to recent population genomics studies using SNPs via RAD sequencing. Here, we primarily employed the often underutilized haplotype information from RAD loci to further describe the species’ previously uninvestigated haplotype-based genomic variation and structure, and genetic-geographic characteristics and gene flow patterns among its five earlier identified genetic groups. We also inferred the time of past events that may have impacted the effective population size of these groups, as well as the species’ potential future distribution amidst the warming climate and anthropogenic threats. Results Our findings emphasized the recognition of the species’ regional patterns of genetic structure, and the role of topography and its associated gene flow patterns as some of the possible factors that may have influenced the species’ present-day fragmented population distribution. The inferred bottleneck events during the Anthropocene, some of which aligned with the time of historical catastrophic events on the Peninsula (e.g., the Korean War), were revealed to have contributed to the generally low effective population size of its five lineages, particularly those with marginal distributional range. Future distribution under both optimistic and pessimistic climatic scenarios suggests unlikely suitable habitats for these populations to expand from their current range limits, at least in the next 80 years. Conclusions The small effective population size and landscape-driven limited gene flow among white forsythia populations will remain a big challenge for the conservation management of the species’ already fragmented population distribution. To help mitigate these impacts, the merging of various research approaches and the use of genomic data to their full potential is recommended to provide the optimized knowledge-based tools for the conservation of this endangered species, and other similar plants under pressure.

Abstract Invasive species such as Xanthium strumarium L., can disrupt ecosystems, reduce crop yields, and degrade pastures, leading to economic losses and jeopardizing food security and biodiversity. To address the challenges posed by invasive species such as X. strumarium, this study uses species distribution modeling (SDM) to map its potential distribution in Pakistan and assess how it might respond to climate change. This addresses the urgent need for proactive conservation and management strategies amidst escalating ecological threats. SDM forecasts a species’ potential dispersion across various geographies in both space and time by correlating known species occurrences to environmental variables. SDMs have the potential to help address the challenges posed by invasive species by predicting the future habitat suitability of species distributions and identifying the environmental factors influencing these distributions. Our study shows that seasonal temperature dependence, mean temperature of wettest quarter and total nitrogen content of soil are important climatic factors influencing habitat suitability of X. strumarium. The potential habitat of this invasive species is likely to expand beyond the areas it currently colonizes, with a notable presence in the Punjab and Khyber Pakhtunkhwa regions. These areas are particularly vulnerable due to threats to agriculture and biodiversity. Under current conditions, an estimated 21% of Pakistan’s land area is infested by X. strumarium, mainly in upper Punjab, central Punjab and Khyber Pakhtunkhwa. The range is expected to expand in most regions except Sindh. The central and northeastern parts of the country are proving to be particularly suitable habitats for X. strumarium. Effective strategies are crucial to contain the spread of X. strumarium. The MaxEnt modeling approach generates invasion risk maps by identifying potential risk zones based on a species’ climate adaptability. These maps can aid in early detection, allowing authorities to prioritize surveillance and management strategies for controlling the spread of invasive species in suitable habitats. However, further research is recommended to understand the adaptability of species to unexplored environments.

Abstract Some snakes emit hissing calls which are imitated by birds to deter potential predators. However, the effect of these snake and bird hisses on anuran risk recognition is not yet explored. Here we hypothesize that these hisses may advertise dangers to frogs and evoke their anti-predator responses. We used little torrent frogs (Amolops torrentis) as subjects and conducted sound playbacks to test their anti-predator behaviors. We found that little torrent frogs changed their calling behaviors during sympatric snake hiss playbacks, but showed no response to white noise and allopatric snake hiss playbacks. They did not respond to sympatric avian hiss that has low acoustic similarity with snake sounds. However, they decreased calling activity in response to sympatric avian hiss that has high acoustic similarity with snakes. As compared to other treatments, more individuals ceased calling during the playbacks of the highly similar bird hiss. These results suggest that frogs may recognize risks from snake and snake-like hissing calls and perform anti-predator responses.

Abstract Avida-ED is a model system that lets students explore evolution and the nature of science by observing and manipulating the evolutionary dynamics of digital organisms. Over 5 years, we ran eight 2.5-day in-person professional development workshops for 105 primarily college biology instructors to introduce them to Avida-ED and digital evolution and to help them to plan implementations. In this paper, based upon 60-min interviews with 46 of the attendees, we describe what they found to be of value in the workshop itself and the implementations of Avida-ED that they subsequently carried out. The Active LENS workshops were universally valued by the interviewees as a professional development experience; they valued the overall experience of the workshops, their organization and content, and the instructor support materials. Of the 46 teachers that we interviewed, 41 implemented Avida-ED in their classrooms, in 66 separate implementations. We characterized these with respect to the nature of the implementation and its duration, and examined the data in relation to course type, course level, and stated learning goals of the instructors. The most common use was to have students learn evolutionary concepts by observing them in action. A smaller fraction used it to provide a complete research experience.

Abstract Background Previous studies have reported that periderm (the outer ectodermal layer) in zebrafish partially expands into the mouth and pharyngeal pouches, but does not reach the medial endoderm, where the pharyngeal teeth develop. Instead, periderm-like cells, arising independently from the outer periderm, cover prospective tooth-forming epithelia and are crucial for tooth germ initiation. Here we test the hypothesis that restricted expansion of periderm is a teleost-specific character possibly related to the derived way of early embryonic development. To this end, we performed lineage tracing of the periderm in a non-teleost actinopterygian species possessing pharyngeal teeth, the sterlet sturgeon (Acipenser ruthenus), and a sarcopterygian species lacking pharyngeal teeth, the axolotl (Ambystoma mexicanum). Results In sturgeon, a stratified ectoderm is firmly established at the end of gastrulation, with minimally a basal ectodermal layer and a surface layer that can be homologized to a periderm. Periderm expands to a limited extent into the mouth and remains restricted to the distal parts of the pouches. It does not reach the medial pharyngeal endoderm, where pharyngeal teeth are located. Thus, periderm in sturgeon covers prospective odontogenic epithelium in the jaw region (oral teeth) but not in the pharyngeal region. In axolotl, like in sturgeon, periderm expansion in the oropharynx is restricted to the distal parts of the opening pouches. Oral teeth in axolotl develop long before mouth opening and possible expansion of the periderm into the mouth cavity. Conclusions Restricted periderm expansion into the oropharynx appears to be an ancestral feature for osteichthyans, as it is found in sturgeon, zebrafish and axolotl. Periderm behavior does not correlate with presence or absence of oral or pharyngeal teeth, whose induction may depend on ‘ectodermalized’ endoderm. It is proposed that periderm assists in lumenization of the pouches to create an open gill slit. Comparison of basal and advanced actinopterygians with sarcopterygians (axolotl) shows that different trajectories of embryonic development converge on similar dynamics of the periderm: a restricted expansion into the mouth and prospective gill slits.

Abstract Large language models (LLMs) are a type of artificial intelligence (AI) that can perform various natural language processing tasks. The adoption of LLMs has become increasingly prominent in scientific writing and analyses because of the availability of free applications such as ChatGPT. This increased use of LLMs not only raises concerns about academic integrity but also presents opportunities for the research community. Here we focus on the opportunities for using LLMs for coding in ecology and evolution. We discuss how LLMs can be used to generate, explain, comment, translate, debug, optimise and test code. We also highlight the importance of writing effective prompts and carefully evaluating the outputs of LLMs. In addition, we draft a possible road map for using such models inclusively and with integrity. LLMs can accelerate the coding process, especially for unfamiliar tasks, and free up time for higher level tasks and creative thinking while increasing efficiency and creative output. LLMs also enhance inclusion by accommodating individuals without coding skills, with limited access to education in coding, or for whom English is not their primary written or spoken language. However, code generated by LLMs is of variable quality and has issues related to mathematics, logic, non‐reproducibility and intellectual property; it can also include mistakes and approximations, especially in novel methods. We highlight the benefits of using LLMs to teach and learn coding, and advocate for guiding students in the appropriate use of AI tools for coding. Despite the ability to assign many coding tasks to LLMs, we also reaffirm the continued importance of teaching coding skills for interpreting LLM‐generated code and to develop critical thinking skills. As editors of MEE, we support—to a limited extent—the transparent, accountable and acknowledged use of LLMs and other AI tools in publications. If LLMs or comparable AI tools (excluding commonly used aids like spell‐checkers, Grammarly and Writefull) are used to produce the work described in a manuscript, there must be a clear statement to that effect in its Methods section, and the corresponding or senior author must take responsibility for any code (or text) generated by the AI platform.

Abstract Historically, most insect chronoecological research has used direct observations, cameras or infrared beam‐based monitors to quantify movement across timed intervals. Although some alternative DIY systems are cheaper than the current standard locomotor activity monitor, these options remain complicated to build and/or computationally intensive. We developed the imaging Locomotor Activity Monitor (iLAM), an affordable (~$75 USD/unit) system for activity quantification. The iLAM utilizes a Raspberry Pi Zero W computer and night‐vision camera inside a flight cage to photograph a population of insects at user‐defined intervals. Open‐source, modular R‐scripts process the images and output a file containing the number, size, coordinate location and timestamp of all movements (blobs) identified between consecutive images. Output can be analysed directly or converted into the standard TriKinetics DAM format. We demonstrated the flexibility and power of the iLAM system by comparing diel and circadian activity of different insect species (fireflies: Photinus marginellus, P. greeni, P. obscurellus), ecotypes (moths: Ostrinia nubilalis) and sexes (moths: O. nubilalis). Data captured by only six iLAMs ($450) identified that peak activity of O. nubilalis females (AZT: 19.2 h) occurs significantly earlier than males (22.0 h). Additionally, male moths from a univoltine population exhibited a significantly shorter endogenous period length (AZT: 21.3 h) than males from a bivoltine genetic background (22.7 h). The iLAM will serve as a valuable tool for researchers seeking to measure locomotor activity across diverse species, sexes and populations in constant and changing environments.

Abstract Archival DNA samples collected and analysed for a range of research and applied questions have accumulated in the laboratories of universities, government agencies and commercial service providers for decades. These DNA archives represent a valuable, yet largely un‐tapped repository of genomic information. With lowering costs of, and increasing access to, high‐throughput sequencing, we predict an increase in retrospective research to explore the wealth of information that resides in these archival samples. However, for this to occur, we need confidence in the integrity of the DNA samples, often stored under suboptimal conditions and their fitness of purpose for downstream genomic analysis. Here, we borrow from a well‐established concept in ancient DNA to evaluate sample integrity, defined as loss of information content in recovered amplicons, of frozen DNA samples and based on the ratio of ⍺‐diversity of short‐ and long‐read 16S rRNA gene sequences. The 16S rRNA variable region of 87 stored DNA samples, extracted from soil, collected from western and southern agricultural regions of Australia between 2001 and 2021 were sequenced using both PacBio full length reads (V1–V9, 1.5 kbp) and Illumina short‐reads (V3–V4, 200–450 bp). When ⍺‐diversity ratios were calculated between the long and short reads to assess DNA degradation, the ratio of ⍺‐diversity did not decrease in older samples versus younger samples. We suggest this as a novel method to confirm integrity of DNA before embarking on large‐scale diversity profiling projects using archival DNA.