Frontiers in Ecology and Evolution

Environmental DNA (eDNA) has emerged as a promising tool for estimating fish abundance, yet linking eDNA concentration to true density remains a significant challenge in seasonal systems, where the signal is strongly influenced by temperature. We investigated whether eDNA can serve as an abundance index for three-spined stickleback (Gasterosteus aculeatus) in four coastal bays of the Baltic Sea (5.7-20.5{degrees}C, April-July 2023), by pairing eDNA sampling with two trap types of contrasting catchability. Light traps capture fish by phototactic attraction during darkness, so their catchability is driven primarily by night duration rather than temperature, while benthic traps respond to temperature through the same activity-driven mechanism as eDNA production. The temperature sensitivity of eDNA estimated from field data was far higher than physiological expectation (Q10 = 12.4, against a maximum metabolic rate benchmark of Q10 = 3.5), indicating that the field temperature signal reflects ecological change in addition to metabolism. We then compared how well three eDNA predictors tracked a combined trap-based abundance index: uncorrected eDNA, eDNA corrected with the temperature response constrained to the laboratory metabolic rate (a first-principles correction), and eDNA corrected with the response estimated from the field data. Uncorrected and first-principles-corrected eDNA were both strong predictors of abundance (standardised slopes of 0.45 and 0.43), whereas the field-corrected predictor was not (0.08). Uncorrected and first-principles-corrected eDNA performed comparably because temperature and abundance increased together over the season; the first-principles correction is nonetheless preferable, as it remains reliable when this covariation is unknown a priori. We conclude that estimating a temperature correction from field data should be avoided in seasonal eDNA monitoring, because it removes the abundance signal together with the temperature effect and assumes a stability in abundance that cannot be verified without independent reference data.

Oxygen limitation is a widespread environmental constraint that shapes physiological and evolutionary responses across ecosystems. A central unresolved question is whether tolerance to hypoxia reflects generalized stress responses or coordinated regulatory strategies shaped by long-term environmental exposure. Here, we use comparative transcriptomic analyses to examine gene expression responses to low oxygen in two aquifer-dwelling stoneflies (Isocapnia sp. and Paraperla frontalis) and one benthic species (Sweltsa sp.) under controlled conditions. Time-series analysis in Isocapnia sp. revealed a multi-phase transcriptional response involving early regulatory activation, metabolic reorganization, and late-stage cellular stabilization. Across aquifer taxa, hypoxia was associated with downregulation of energy-demanding processes and upregulation of pathways related to oxidative stress mitigation, metabolite transport, and protein folding, consistent with coordinated cellular adjustment to oxygen limitation. In contrast, the river benthic species exhibited transcriptional profiles dominated by neural signaling, ion channel activity, and structural remodeling, which are patterns consistent with acute physiological stress rather than coordinated regulation. Despite these differences, all taxa showed modulation of ion transport and calcium signaling pathways, suggesting conserved mechanisms of hypoxia sensing. Together, these results indicate that transcriptional responses to hypoxia differ systematically with habitat and are consistent with the evolution of distinct regulatory strategies in chronically hypoxic environments. Significant statementOxygen limitation is a common environmental challenge that affects organisms across aquatic and terrestrial ecosystems, yet the mechanisms by which species cope with low oxygen remain incompletely understood. A key question is whether tolerance to hypoxia reflects common stress responses or the evolution of coordinated metabolic regulatory strategies under chronic exposure. By comparing gene expression responses in closely related aquatic insects from oxygen-variable underground aquifers and oxygen-rich river habitats, we show that species that evolved under persistent hypoxia exhibit transcriptional patterns consistent with energy conservation and cellular stabilization, whereas those experiencing hypoxia as a transient stress display signature of physiological disruption. These findings highlight fundamental differences between evolutionarily adaptive and acute stress-driven responses to environmental change and provide insight into how organisms may respond to increasing hypoxia under global change.

OverviewThis dataset originates from a preliminary respirometry study on carabid beetles from the Elbe Estuary (Northern Germany), encompassing species from freshwater and saltmarsh habitats along a salinity gradient. The study was designed to establish and validate a workflow for measuring oxygen consumption, including chamber setup, sensor recording, drift correction, and calculation of absolute and mass-specific metabolic rates. Oxygen consumption was measured for five species (Carabus auratus, Carabus granulatus, Limodromus assimilis, Poecilus versicolor and Pterostichus niger) using sealed glass vials connected to an optical oxygen system. The dataset provides individual-level measurements and serves primarily as a methodological reference for future respirometry studies on ground-dwelling arthropods. The O2 consumption rates of carabid beetles showed interspecific differences and followed metabolic scaling theory, revealing an inverse relationship between body mass and mass-specific metabolic rates across species (Figure 3). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/720111v1_fig3.gif" ALT="Figure 3"> View larger version (17K): org.highwire.dtl.DTLVardef@f41f27org.highwire.dtl.DTLVardef@12939eeorg.highwire.dtl.DTLVardef@19a4630org.highwire.dtl.DTLVardef@17611ba_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 3:C_FLOATNO Oxygen consumption rates of Carabid species per (a) animal in [ml O2 h-1] and as (b) mass-specific consumption rate [ml O2 h-1 g-1]. Points represent mean oxygen consumption per individual (C. auratus: n = 2; L. assimilis: n = 6; P. versicolor: n = 7; P. niger: n = 6). C_FIG

Migrating bats alternate between stopover periods and directed flights. When departing from a stopover site, bats select the night, the specific time within the night, and the flight direction to resume migration. Despite their ecological importance, the factors shaping these stopover departure decisions remain poorly understood. To identify the intrinsic and environmental factors driving departure decisions and movement patterns, we tagged Nathusius pipistrelles Pipistrellus nathusii at three coastal locations in the Netherlands and tracked 178 individuals during autumn migration, using the MOTUS Wildlife Tracking System. We examined movement patterns and analysed departure probability in relation to a set of individual and environmental covariates in a Bayesian capture-recapture model in state-space formulation. Additionally, we modelled within-night variation in departure timing. Seasonal patterns were strongly influenced by reproductive behaviour, with decreased migration probability during the mating period. Regardless of their seasonal timing, bats departed under moderate tailwinds and dry conditions, optimizing energy efficiency, while avoiding crosswinds and cloud cover, enhancing navigational safety. Most individuals departed shortly after sunset, whereas headwinds delayed nocturnal departure. Movement patterns were diverse, including migration towards lower latitudes, coastal barrier movements, and long-distance roundtrips, suggesting the use of multiple movement strategies. Our study demonstrates that migration patterns in bats emerge from the interaction between intrinsic factors and external conditions, and highlights the importance of both energy efficiency and safety in shaping stopover departure decisions. The presence of multiple movement strategies complicates predictions of spatiotemporal occurrence, emphasising the need to account for behavioural variability in conservation planning, for example in the context of wind energy developments.

Environmental DNA (eDNA) has the potential to be a powerful tool in blue carbon science for characterizing and quantifying the contribution of marine macrophytes; but its complex, dynamic relationship with bulk biomass is poorly understood. Here, we used eDNA to examine the degradation dynamics of sugar kelp (Saccharina latissima) in muddy, anaerobic marine sediment. This involved three 16-week incubations; with additions of lyophilized sugar kelp alone, a mix of lyophilized marine macrophytes including sugar kelp, and sugar kelp holdfasts buried in sediment. We used species-specific digital polymerase chain reaction assays for mitochondrial, chloroplast and nuclear markers, and metabarcoding for the 16S and 18S ribosomal RNA genes. In the former two incubations, all sugar kelp eDNA markers showed rapid log exponential declines (up to 98-99%) to asymptotes greater than the unamended controls, even as part of a more complex mix of macrophytes. In contrast, for the buried kelp holdfasts, sugar kelp eDNA increased to an asymptote (by up to [~]15X), which may be reflective of the different nature of added biomass. Overall, we demonstrate substantial preservation of environmental DNA and total organic carbon under anaerobic conditions, and the potential to use environmental DNA to quantify biomass in a blue carbon context.

Conservation biology increasingly relies on ecological forecasting, yet the biodiversity components most urgently targeted by conservation, such as rare species, local assemblages, and hotspot-defined communities, are often those whose dynamics are least predictable. Understanding how predictability varies across biodiversity is therefore essential for aligning management tools with their targets. This study tests whether predictability varies along three axes, how diversity is measured, the spatial scale of observation, and the temporal forecast horizon (which together govern the effective signal-to-noise ratio of ecological dynamics), and uses these patterns to inform conservation strategies. Using long-term monitoring data from seven estuaries along the Texas Gulf Coast, forecasting performance was evaluated for Hill diversity (q = 0, 1, 2) and population-level abundance of eight dominant taxa at local (bay) and regional (coastwide) scales across near-term (1-month) and long-term (12-month) horizons. Multiple time-series model classes were assessed within a rolling-origin cross-validation framework, with performance measured as improvement in root mean square error over a seasonal naive baseline. Forecasting performance increased consistently with Hill number order, reflecting reduced stochastic variation as dominant species are emphasized. The effects of spatial aggregation differed between systems. Aggregation generally improved performance for littoral assemblages but provided limited or no benefit for demersal assemblages, consistent with differences in how predictive signals are distributed across space. Forecast skill declined from 1-to 12-month horizons, with slower decay for dominance-weighted diversity and demersal assemblages than for rare-species-weighted richness and littoral assemblages. Environmental covariates provided limited near-term gains but became an increasingly important source of predictive information at longer horizons for a subset of demersal and crustacean targets. These results define a predictability landscape structured by diversity measurement, spatial scale, and forecast horizon. Three conservation domains, stochastic, transitional, and structured, emerge from this framework, each associated with distinct predictability regimes and management strategies. Aligning conservation approaches with the predictability properties of their targets provides a principled basis for determining when forecast-based management is informative and when precautionary approaches are more appropriate.

Animal COI (mitochondrial cytochrome oxidase I) metabarcoding of environmental DNA (eDNA) is increasingly used to assess biodiversity in complex substrates such as soil. However, due to read-length constraints of second-generation sequencing platforms, mini-barcodes have been used instead of the full barcode region. Long-read sequencing technologies now enable the recovery of full-length barcode sequences, and are more commonly applied for studying microbes, but their use for metabarcoding the full-length standard COI barcoding region in animals remains limited. In this study, we compared three COI amplicon sets -- 313 bp, 660 bp, and 1,256 bp -- amplified from soil eDNA samples and sequenced using Illumina and PacBio platforms to evaluate their overall concurrence, the effectiveness of identifying nuclear mitochondrial DNA segments (NUMTs) and chimeras, as well as their respective taxonomic resolution. The long-read datasets exhibited a higher identification rate of NUMTs and true chimeras, suggesting that longer sequences improve the detection of noise in COI metabarcoding data, thereby reducing the occurrence of spurious taxa. Taxonomy assignment confidence was similar between the 313 bp and 660 bp datasets, whereas extending the amplicon beyond the standard COI barcode region (1,256 bp) reduced confidence, likely because longer reads extend into regions poorly represented in barcode reference databases. Despite substantially lower sequencing depth in the 660 bp dataset, per-sample OTU richness did not differ significantly from that recovered with the Illumina 313 bp amplicon set. Similarly, the relationships between samples were strongly correlated across the detected OTU communities, indicating consistent ecological interpretations between short and long amplicons. We conclude that the standard ~658 bp COI barcode is an optimal marker for soil animal metabarcoding from eDNA, balancing target recovery, artifact detection, taxonomic assignment and ecological interpretability. As COI eDNA metabarcoding becomes increasingly used in biodiversity assessment and is increasingly adopted in large-scale monitoring initiatives, this study provides methodological guidance for improving the robustness of soil animal community biomonitoring.

The release of tens of millions of common pheasants (Phasianus colchicus) across the UK for shooting may pose an ecological risk to native species and sensitive habitats, particularly if the birds move into protected areas (PAs) such as Special Areas of Conservation (SAC), Special Protection Areas (SPA), and Sites of Special Scientific Interest (SSSI). The extent of this ecological risk depends on the abundance of pheasants in these sensitive sites, especially if they are attracted there after the shooting season when game management efforts to retain the birds cease. We used relative pheasant abundance measures derived from British Trust for Ornithology bird atlas data from 3793 2km tetrads across four English counties (Berkshire, Cornwall, Devon, and Hertfordshire) to determine if pheasants preferentially disperse into or reside in areas with greater PA coverage. We analysed relative abundance in both the winter shooting season and the breeding season using a Bayesian occupancy-abundance model, controlling for habitat type and diversity. Our results showed a strong influence of habitat on pheasant abundance, consistent with known habitat preferences. However, we found no evidence of a relationship between relative pheasant abundance and the proportion of ecologically relevant PA coverage in a tetrad. This lack of a relationship was consistent across all four counties and across both the winter and breeding seasons. Our finding suggests that common pheasants do not preferentially disperse into or reside in protected areas compared to surrounding, unprotected land, suggesting that the ecological impacts caused by released pheasants are no more likely to occur in protected areas than in non-protected areas.

Mitochondrial loci were for long considered as markers of choice to reconstruct phylogenies. The development of high-throughput sequencing over the past two decades fostered the sequencing of mitogenomes, allowing further macroevolutionary questions to be tested. Several biological traits of birds (e.g. body mass, migration distances) have been related to mitochondrial substitution rates. Environmental parameters in ectothermics vertebrates, and potentially in endotherms, have been further suggested to impact substitution rates for specific taxa or loci. Yet, the relative importance of biological traits versus bioclimatic variables is unknown because the former were not systematically controlled for in studies that underlined the effect of the bioclimatic variables. To assess the importance of bioclimatic variables on selection regimes, we analysed the thirteen mitochondrial protein-coding genes for 176 Piciformes (toucans, honeyguides, woodpeckers), a clade with homogeneous life-history traits that can be found in diverse bioclimatic environments. Our analyses highlighted a negative relationship between temperature annual range and the non synonymous to synonymous substitutions ratio. The higher purifying selection in temperate environments may be a result of the strong constraints on maintaining an optimal metabolism in broader climatic variations. Our results further highlight that care should be taken when applying general mitochondrial clocks to estimate divergence times among avian lineages distributed in different climatic conditions.

Capelin (Mallotus villosus), a key forage fish in the Northwest Atlantic, links zooplankton to predators including commercial fishes, seabirds, and marine mammals, yet its life-cycle movements in the Gulf of St. Lawrence (GSL) remain poorly understood. Between 2022 and 2024, otoliths from 927 individuals collected during and after spawning were analysed by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). Building on previous work on regional structuring, seven trace elements (Li, B, Mg, K, Zn, Sr, Ba) were used to discriminate three regions. Early-life regional signatures were inferred through an edge-to-core approach, assigning otolith core chemistry to one of these regions using quadratic discriminant analysis. The core was treated as an integrated early-life signal (late-larval to early juvenile period) rather than a strictly natal signature. Spatial variation in core chemistry was consistent across cohorts, mirroring the stability documented on the otolith edge. Results revealed widespread dispersal alongside partial regional residency: individuals with northeastern early-life signatures showed the strongest correspondence between early-life and capture regions, whereas other regions were more connected. Fish sampled during spawning were more often reassigned to their inferred early-life region than post-spawning fish, a regional-scale homing-like pattern consistent with regional spawning fidelity. This coexistence of dispersive and resident strategies likely generates a portfolio effect buffering the population against environmental variability and localised reproductive failures.

The release and management of pheasants (Phasianus colchicus) in the UK for recreational shooting exerts a range of effects on the ecosystem into which they are released. We studied possible effect of nutrient deposition on epiphytic tree flora at 20 pheasant release sites distributed through England (18) and Wales (2) during winter and spring 2023/24. Sites were all Ancient Semi-natural Woodlands (ASNWs) and had substantial (600-8000 pheasants) in a single release pen. We measured N-sensitive and N-tolerant indicator bryophyte and lichen species on tree trunks near to the pen and then in plots along a transect 100m, 250m, 500m and 1km+ away from the pen. To achieve a gradient of pheasant use, the transects were located in the opposite direction to the game managed / shooting area. We recorded 1.9 times more coverage of N-tolerant lichens and bryophytes combined on selected tree species at the pen-edge compared to the control plots. The relationship showed a decline from the pen edge to 250m away but then stabilised. We also detected higher levels of coverage of N-sensitive tree flora at 100m and 250 m compared to the penedge plot. These measures were also higher at these mid distances compared to the 500m and 1000m plots. We suggest far plots were nearer wood edges and were affected by ambient inputs of aerial N from farmland and other external sources. The overall interpretation is that concentrations of pheasants in and around release pens for several months from late summer until early winter in ASNWs does affect the balance of N-sensitive and tolerant tree flora up to potentially 250m and this is a consideration when locating release pens in and near to sensitive woods.

The effect of predator behaviours on the evolution of colour pattern has been extensively studied in chemically defended prey but much less so in evasive prey, although similar selection regimes might be at play. Most previous work on the recognition and learning of colour patterns by predators has relied on experiments with few model predator species, preventing a proper assessment of how natural predator communities shape the evolution of prey signals. Here, we investigate predation on evasive iridescent blue Morpho helenor butterflies by wild avian communities in a tropical forest, using artificial butterflies exposed to natural bird assemblages attracted to insect-light traps in the field. We presented five prey types: evasive (local and exotic Morpho), cryptic, palatable-control and unpalatable-control. We recorded attacks from 43 different bird species, and compared attack latency, attack order and predation exerted by different birds on different prey types. Most birds avoided evasive and defended prey, but attack responses differed depending on their levels of specialization towards insect prey. Avoidance of conspicuous coloured prey was more prevalent in specialist flight-feeding, invertivorous birds, whereas more opportunistic treehunter and frugivorous guilds had weaker discrimination. Exotic and local evasive iridescent blue Morphos experienced similar predation rates, suggesting a generalization of iridescent blue signals associated with evasiveness by most birds. Finally, contrasting selection on ventral vs. dorsal patterns was detected in M. helenor, where cryptic ventral surfaces were exposed to attack by ground-foraging birds, whereas conspicuous iridescent blue coloration displayed during flight is associated with reduced attack rates. By revealing potential differences in the responses of specialist and generalist predators, this study highlights the importance of accounting for diversity of predator traits and behaviours when investigating the evolution of aposematism, mimicry, and other anti-predator adaptations.

We investigated the influence of small-scale topographic and associated microclimatic drivers on the elevational patterns of functional alpha and beta diversity in ant communities of eastern Himalayas. Ants were sampled along three elevational transects spanning [~]1000-2000 m on two nearby mountain slopes, but differing in aspect, inclination and summit height. Ant genera were quantified at the quadrat level, yielding an abundance of 3090 genus-quadrats (from 22577 individuals in 1215 quadrats), almost evenly split between the two mountain slopes. Each ant was assigned to guilds along functional axes of thermal niche, trophic position and competitive abilities. Comparative analyses of functional diversity profiles along the two mountain slopes revealed no differences in the composite multi-guild alpha and beta diversity but significant differences amongst individual guild profiles. Seven of the eleven functional guilds showed strong elevational trends along the steeper north-facing slope, compared to only two of eleven on the shallower south-facing slope. These results indicate that similar functional space can be maintained despite taxonomic turnover within guilds or shifts in their relative abundances highlighting the influence of fine-scale topographic variation on community assembly. Alternatively, these findings demonstrate that the pattern of multivariate functional diversity across elevation does not necessarily provide an understanding of changing composition of the communities therein.

Globally, nocturnal lightscapes are now determined by both moonlight and light pollution, or artificial light at night (ALAN). Organisms respond both to changes in moonlight across lunar cycles and to alterations in light conditions due to artificial light. The interaction of natural and artificial light is a critical aspect to incorporate into our understanding of how crepuscular and nocturnal ecology is altered in anthropogenically-modified landscapes. In this manuscript we review the rapidly expanding body of research on ecological impacts of ALAN to (1) assess patterns of lunar data inclusion and (2) summarize documented interactions of moonlight and ALAN. Three-fourths (72%) of 379 papers reviewed did not incorporate moonlight into their statistical analyses and experimental design. Only 12% directly investigated interaction effects of moonlight and ALAN. However, 70% of these studies reported an interactive effect. Considering this stark contrast, as a precursor to our literature review, we present an overview of moonlight and the lunar cycle for biologists. The overarching trend emerging from the literature is that biological impacts of ALAN decrease with increasing moonlight, although the opposite is true in some cases. After summarizing the literature, we present general hypotheses regarding the interaction of the lunar cycle and ALAN. These hypotheses consider the different forms of ALAN encountered by organisms (i.e. skyglow and light sources) and account for the influence of cloud cover. Finally, we suggest best practices for incorporating moonlight into future research on biological impacts of ALAN.

Among eukaryotes, insects are by far the most diverse organisms on Earth, yet their global decline threatens ecosystem stability. Understanding local and regional biodiversity patterns is critical for conservation planning, ecosystem management, and predicting responses to environmental change, but traditional surveys for assessing insect diversity (e.g., manual collection, morphological identification, and counting) are highly labor-intensive, time-consuming, and often require rare or simply unavailable dedicated taxonomic expertise. DNA metabarcoding offers an efficient, high-resolution alternative to assess insect communities. Here, we report on the first insect metabarcoding survey on Crete that spans two years of sample collection between 2021 and 2023 from a small area in Southern Central Crete in the context of a citizen science project. A total of 29 samples yielded 10,865 Exact Sequence Variants (ESVs), 10,516 of which were assigned to insects, covering 988 species, 900 genera, and 227 families across 14 orders. A comparison with the existing observation records reveals 406 potential newly-observed species and an estimated 690 unclassified species, indicating substantial cryptic diversity. Our results demonstrate that even small-scale sampling can unravel substantial insect diversity and highlight critical gaps in barcode reference databases. Our study demonstrates how DNA metabarcoding can accelerate biodiversity discovery and monitoring in understudied regions.

O_LIMonitoring and limiting the spread of invasive species on islands requires efficient detection and population estimation methods. However, elusive species can be difficult to monitor using traditional methods, making autonomous approaches such as camera trapping and acoustic monitoring increasingly valuable. C_LIO_LIOn the island of Okinawa, Japan, the small Indian mongoose ( Urva auropunctata) threatens many native species since its introduction in 1910. Listed among the worlds worst invasive species, effective monitoring of U. auropunctata in Okinawa is critical. The Okinawa Environmental Observation Network (OKEON) uses camera traps to detect U. auropunctata, but success depends on precise placement. Though OKEON also includes a high-resolution acoustic monitoring programme, no audio classification model currently exists for U. auropunctata. Developing such a model could improve substantially our capacity to detect and manage the species. C_LIO_LIUsing sparse U. auropunctata vocalisations collected from camera trap videos, we built a lightweight Convolutional Neural Network distilled from a more complex model for classifying contact calls and alarm calls of U. auropunctata. Our distilled model performed similarly to the full model at detecting vocalisations from training data, but was considerably faster. C_LIO_LIWe applied the distilled classifier to [~]486 hrs of audio collected over eight years from southern Okinawa, where we successfully detected U. auropunctata a handful of times in each year of recording. In spite of strong model performance on test data, our model did not transfer well to unseen data, perhaps owing to the rarity of U. auropunctata calls and consequent small training dataset size, limiting its utility for ecological monitoring. C_LIO_LIPractical implication. The use of sparse audio data from camera trap videos to train an acoustic classifier had limited utility to detect the rarely vocalising U. auropunctata from passive acoustic monitoring data. We provide several recommendations for enhancing classifier performance to provide robust actionable insights into the distribution and spread of U. auropunctata, and aid targeted conservation efforts for Okinawas threatened biodiversity. C_LI

Thermal extremes are among the most immediate environmental challenges faced by animals. Coping with these conditions across life is complex because growth changes body size, heat exchange and thermoregulatory demands. Consequently, adaptive responses in young, small individuals may be maladaptive, or require adjustment, later in life. However, in endotherms we know very little about how thermoregulatory responses to hot and cold temperatures change during development, or about the molecular mechanisms regulating responses. We examined the molecular responses to acute heat (40{degrees}C), cold (12{degrees}C) and control (23{degrees}C) conditions in 1- and 8-week-old ostrich chicks (Struthio camelus), a rapidly growing species exposed to strong daily and seasonal temperature variation. We found that in 1-week-old chicks, 32% of temperature-related genes were involved in both heat and cold responses, indicating that responses to opposing temperatures involve overlapping molecular pathways. However, the response of 75% of these genes changed during development. For example, some genes that increased with heat when young decreased with heat later in development, and vice versa. Such opposing selection pressures may maintain genetic variation in thermoregulatory pathways. Consistent with this prediction, comparisons between ostrich subspecies adapted to different thermal environments revealed patterns of genomic variation compatible with balancing selection in differentially expressed genes. Our results show that hot and cold temperatures trigger overlapping molecular responses that change during development, which shape genetic variation in the thermoregulatory system.

Terrestrial environmental DNA (eDNA) approaches are rapidly expanding, yet robust, field-ready substrates for detecting insect DNA remain limited in forest ecosystems. Tree sap is a localized microhabitat that attracts diverse insects and may provide a useful substrate for surface eDNA sampling, but its potential for insect monitoring has rarely been evaluated. Here, we present a pilot proof-of-concept study testing naturally exuding tree sap and sap-mimicking traps as terrestrial eDNA substrates. We collected swab samples from sap and trap surfaces at two forest sites in Japan (Fujisawa and Minamisanriku) and performed metabarcoding using COI and an arthropod-focused 16S marker (gInsect). Reads were processed into amplicon sequence variants and assigned by BLAST top hits against NCBI nt, with high-confidence detections defined at identity [≥]98%. Across sites, sap and trap swabs yielded multiple high-confidence insect detections spanning several orders, including sap-associated stag beetles (Dorcus spp.). Overlap with contemporaneous conventional monitoring was limited, suggesting that sap-surface eDNA and conventional surveys capture partly different components of sap-associated insect assemblages. In a targeted 2024 spot survey, actively fermenting sap yielded multiple insect eDNA detections, whereas inactive, non-fermented sap yielded no high-confidence insect detections. Although limited by small sample size and the absence of dedicated process controls, these findings support the feasibility of tree sap as a localized terrestrial eDNA substrate and provide a basis for future replicated studies of sap-associated insect monitoring.

Explainable machine learning (ML) methods are gaining increasing attention in environmental and ecological research for their ability to reveal relationships between environmental drivers and population dynamics. However, there remain questions on the reliability of these tools, especially given recent research shows that these explanations can be highly sensitive to model architecture. In ecology, it is typical to use a single ML model, and a comparative evaluation of sensitivity of explainability for different ML approaches is overlooked. In this paper, we develop a novel framework that quantifies explanation consistency between multiple ML model architectures. This framework provides a discrepancy measure for each model prediction, with high discrepancy indicating substantive explanation disagreement across models and low discrepancy indicating strong consensus in explanations across models. We then demonstrate that low explanation discrepancy aligns well with ground truth mechanism. Furthermore, high explanation discrepancy provide a mechanism to identify areas for model refinement and further investigation by domain experts. We do this by using a simulation study based on synthetic coral cover data that incorporate spatio-temporal variability driven by known disturbance effects. Our method provides a quantitative approach to assess the sensitivity of explainable ML in the absence of ground truth. As a result, this enhances the utility of ML approaches in conservation and ecological management. While we focus primarily on ecological modelling for coral reefs, our methods are generally applicable to other ecological and environmental modelling settings.

Efficiently finding rare species is a perennial challenge in conservation science. The orange-bellied parrot Neophema chrysogaster is a rare mobile bird that is difficult to locate using traditional field survey techniques with human observers. We harnessed recent advances in bioacoustic technology to create a survey framework that integrates passive acoustic surveys and semi-automated detection to increase monitoring capacity for the orange-bellied parrot. We developed a custom BirdNET classifier for the orange-bellied parrot and compared efficacy of acoustic and field surveys using an occupancy framework. We deployed autonomous recording units across the orange-bellied parrots breeding range in southwest Tasmania and concurrently undertook between three and six repeated point-count surveys at the same 48 sites using human observers. Our custom BirdNET classifier had high accuracy and discrimination abilities. Validation of model scores across a week (5,712 hours of audio) required 60 hours reviewing time and yielded a 95% confidence of a correct BirdNET prediction at scores over 0.998. Occupancy analysis showed that the detection probability of acoustic surveys (p = 0.80) was more than eleven times greater than field surveys by skilled ecologists familiar with the species (p = 0.07). We provide a template for how to implement monitoring of the orange-bellied parrot and recommendations for how our methods can be improved to optimise the classifier to account for other species and locations.