Animal stoichiometry influences critical processes from organismal physiology to biogeochemical cycles. However, it remains uncertain whether animal stoichiometry follows predictable scaling relationships with body mass and whether adaptation to terrestrial or aquatic environments constrains elemental allocation. We tested both interspecific and intraspecific body-mass scaling relationships for nitrogen (N), phosphorus (P), and N:P content using a subset of the StoichLife database, which includes 9,933 individual animals across 1,543 species spanning 10 orders of magnitude in body mass from terrestrial, freshwater, and marine realms. Our results show that body mass predicts intraspecific stoichiometric variation, accounting for 42-45% of the variation in 27% of vertebrate and 35% of invertebrate species. However, body mass was less effective at explaining interspecific variation, with taxonomic identity emerging as a more significant factor. Differences between aquatic and terrestrial organisms were observed only in invertebrate interspecific %N, suggesting that realm has a relatively minor influence on elemental allocation. Our study, based on the most comprehensive animal stoichiometry database to date, revealed that while body mass is a good predictor of intraspecific elemental content, it is less effective for interspecific patterns. This highlights the importance of evolutionary history and taxonomic identity over general scaling laws in explaining stoichiometric variation.

Large pre-trained models (LPMs) have the capabilities to understand natural language, code, and diverse data including images; e.g., large language models (LLMs), code-generative models, and large vision models (LVMs) as well as combined as multi-modal models. We outlines the main applications of LPMs and multi-modal LPMs for ecology and biodiversity conservation. These applications include generating ecological data, generating code, providing insights into public opinion and sentiment. We highlighted the significant potential of LPMs and the potential use of Ecology-specialized LPMs for ecology and biodiversity conservation. They offer unprecedented opportunities for analyzing diverse data, extracting meaningful insights, and informing conservation decisions.

Large Language Models (LLMs) have revolutionized the field of natural language processing. These models can analyze vast amounts of data, extract meaningful insights, and provide a basis for informed conservation decisions. This paper identifies the main applications of LLMs for ecology and biodiversity conservation: generation of ecological data, prediction using coding by LLMs, providing insights into public opinion and sentiment, and the potential application of Ecology-specialized LLMs.We discuss the potential challenges and limitations associated with the use of LLMs, such as biases in LLM-generated code and data, and the need for careful evaluation and interpretation of LLM-generated results.

Ectothermic species have body temperatures that reflect their environment to varying degrees. Environmental temperature drives all cellular and physiological functions, including metabolism, development, growth, migration, and reproduction. Extreme temperatures are occurring more frequently with climate change, and understanding the thermal tolerance and adaptive traits of species is critical.We hypothesized that 1) geographic location of stream ecosystems, such as elevation and latitude, influence the habitable water temperature of lotic (stream) invertebrates because the thermal habitat of species directly influences their life cycle and consequently fitness and 2) species functional traits (e.g., voltinism and feeding behavior) are influenced by habitable temperature. Here, we tested these hypotheses across diverse taxa and geographic regions using a dataset for stream invertebrates traits across North America. We showed that maximum water temperature in habitats and thermal breadth were significantly lower and narrower across streams ranging in elevation, from 0 to 3000 m, suggesting that invertebrate taxa across various elevations are less tolerant of warmer water temperature. Also, we identified thermal sensitivity differences among species traits, especially functional feeding group traits, as these are related to habitat selection in stream ecosystems. Our synthesis suggests that elevation and species traits can help predict thermal breadth and thermal tolerance for different species under a changing climate.

Environmental DNA measurement has been widely applied in organism biomonitoring. Different DNA extraction methods may cause changes in yield and stability, resulting in an inaccurate estimation of eDNA, especially when quantitative measurements are performed. This study focused on the DNA extraction method and compared its yield and stability for stream fish and spiked DNA samples. Samples were collected periodically over a year from river and lake water systems and eDNA was spiked into them. The samples were extracted and compared using three methods: using Buffer-AL for initial lysis with the DNeasy Blood and Tissue Kit (Qiagen); using Buffer-ATL for initial lysis and the microfluidic-channel method (BC method). The method using Buffer-ATL in the DNeasy Blood and Tissue Kit showed better stability and a higher yield than the Buffer-AL method. In addition, the BC method, despite being comparatively simple, performed the extraction stably and with relatively high yields. We showed that differences in DNA extraction methods based on the long-term evaluation of eDNA measurements with various methods may cause alterations in DNA yield and stability.

Pritam Banerjee1, 2, Kathryn A. Stewart3, Caterina M. Antognazza4, Ingrid V. Bunholi5, Kristy Deiner6, Matthew A. Barnes7, Santanu Saha8, Héloïse Verdier9, Hideyuki Doi10, Jyoti Prakash Maity2, Michael W.Y. Chan1, Chien Yen Chen2*1Department of Biomedical Sciences, Graduate Institute of Molecular Biology, National Chung Cheng University, 168 University Road, Ming-Shung, Chiayi County 62102, Taiwan2Department of Earth and Environmental Sciences, National Chung Cheng University, 168 University Road, Ming-Shung, Chiayi County 62102, Taiwan.3 Institute of Environmental Science, Leiden University, 2333 CC Leiden, The Netherlands4 Department of Theoretical and Applied Science, University of Insubria, Via J.H. Dunant, 3, 21100, Varese, Italy5 Department of Biology, Indiana State University, Terre Haute, IN 47809, USA6 Department of Environmental Systems Science, ETH Zurich, Universitätstrasse 16, CH-8092 Zurich, Switzerland7 Department of Natural Resources Management, Texas Tech University, Lubbock, TX USA8Post Graduate Department of Botany, Bidhannagar College, Salt Lake City, Kolkata 700064, India9Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, UMR 5023 LEHNA, Villeurbanne, France10Graduate School of Information Science, University of Hyogo, 7-1-28 Minatojima-minamimachi, Chuo-ku, Kobe, 650-0047, JapanAbstract Plant-animal interactions (PAI) represent major channels of energy transfer through ecosystems, where both positive and antagonistic interactions simultaneously contribute to ecosystem functioning. Monitoring PAI therefore increases understanding of environmental health, integrity and functioning, and studying complex interactions through accurate, cost-effective sampling can aid in the management of detrimental anthropogenic impacts. Environmental DNA (eDNA)-based monitoring represents an increasingly common, non-destructive approach for biomonitoring, which could help to elucidate PAI. Here, we focused our foundation to discuss the potential of eDNA in studying PAI on the literature existing from 2009 to 2021 using a freely accessible web search tool. The search was conducted by using key words involving eDNA and PAI, including both species-specific and metabarcoding approaches, recovering 43 studies. We summarise advantages and current limitations of such approaches, and we offer research priorities that will potentially improve future eDNA-based methods for PAI analysis. Our review has demonstrated that numerous studies exist using eDNA to identify PAI (e.g., pollination, herbivory, mutualistic, parasitic relationships), and although eDNA-based PAI studies remain in their infancy, to date they have identified higher taxonomic diversity in several direct comparisons to DNA-based gut/bulk sampling and conventional survey methods. Research into the influencing factors of eDNA detection involved in PAI (e.g., origin and types, methodological standardization, database limitations, validation with conventional surveys, and existing ecological models) will benefit the growth of this application. Thus, implementation of eDNA methods to study PAI can particularly benefit environmental biomonitoring surveys that are imperative for biodiversity health assessments.

The environmental DNA (eDNA) method, which is widely applied for biomonitoring, is limited to laboratory analysis and processing. In this study, we developed a filtration/extraction component using a microfluidic channel, Biryu-Chip (BC), and a filtration/extraction method, BC method, to minimize the volume of the sample necessary for DNA extraction and subsequent PCR amplification. We tested the performance of the BC method and compared it with the Sterivex filtration/extraction method using aquarium and river water samples. We observed that using the BC method, the same concentration of the extracted DNA was obtained with 1/20–1/40 of the filtration volume of the Sterivex method, suggesting that the BC method can be widely used for eDNA measurement. In addition, we could perform on-site measurements of eDNA within 30 min using a mobile PCR device. Using the BC method, filtration and extraction could be performed easily and quickly. The PCR results obtained by the BC method were similar to those obtained by the Sterivex method. The BC method required fewer steps and therefore, the risk of DNA contamination could be reduced. When combined with a mobile PCR, the BC method can be applied to easily detect eDNA within 30 min from a few 10 mL of the water sample, even on-site.

In a recent paper, “Environmental DNA: What’s behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring”, Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. Not only is this terminology based on categories that are often difficult to assign and uninformative, but it ignores what is in our opinion the most important distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived.

The biomass ratio of herbivores to producers reflects the structure of a community. Four primary factors have been proposed to affect this ratio, including production rate, defense traits, and nutrient contents of producers as well as predation by carnivores. However, the relative importance of these factors across natural communities is elusive, in part because of the lack of a framework for quantitatively comparing their effect sizes. Here, we develop a framework based on Lotka-Volterra equations for examining the relative importance among these factors in determining the biomass ratio. We further utilize it to analyze plankton communities in experimental ponds with different carnivore (fish) abundance and light input. We found that all four factors contributed significantly to the biomass ratio, but carnivore abundance had the largest effect size, followed by the stoichiometric nutrient content. The present framework is useful for quantifying relative roles of these factors shaping terrestrial and aquatic communities.

Phenotypic variation among individuals and species is a fundamental principle of natural selection. In this review, we focus on numerous experiments involving the model species Daphnia (Crustacea) and categorize the factors, especially secondary ones, affecting intraspecific variations in inducible defense. Primary factors, such as predator type and density, determine the degree to which inducible defense expresses and increases or decreases. Secondary factors, on the other hand, act together with primary factors to inducible defense, or without primary factors on inducible defense. The secondary factors increase intra-species variation in inducible defense, and thus the level of adaptation of organisms varies within species. Future research will explore the potential for new secondary factors, as well as the relative importance between factors needs to be clarified.

Analysis of biodiversity in natural environments based on environmental DNA (eDNA) has been applied to a wide range of ecosystems and species. The combination of high-throughput sequencing technologies and eDNA analysis is a powerful tool that enables comprehensive non-invasive monitoring of species present in the environment. Quantitative data of the eDNA from each species is essential for understanding species abundance but until recently required individual assays targeting each species. Recently developed quantitative sequencing (qSeq) allows simultaneous phylogenetic identification and quantification of individual species by counting random tags added to the 5′ end of the target sequence during the first DNA synthesis. Here, we applied qSeq to eDNA analysis to test its effectiveness in biodiversity monitoring. The eDNA extracted from aquaria with five fish species (Hemigrammocypris neglectus, Candidia temminckii, Oryzias latipes, Rhinogobius flumineus, and Misgurnus anguillicaudatus) across 4 days was quantified by microfluidic digital PCR using a TaqMan probe and qSeq. The eDNA abundance quantified by qSeq was consistent with dPCR for each fish species at each sampling time. However, the relative abundances of sequences obtained from high throughput sequencing did not follow the same trend as the quantitative analyses, probably due to different PCR amplification efficiencies for each species. The correlation coefficients between qSeq and dPCR were 1.052, 1.074, and 1.114 for H. neglectus, O. latipes, and M. anguillicaudatus, respectively, indicating that qSeq accurately quantifies fish eDNA. The application of qSeq to eDNA of other species will provide comprehensive quantitative data that could deepen our knowledge of natural ecosystems.