Traditional Sampling Methods Research Articles

Towards eDNA informed biodiversity studies – Comparing water derived molecular taxa with traditional survey methods

Managing natural resources in a sustainable manner requires understanding the complexity of ecosystems and the species that are associated with the different parts of the ecosystem. Much of this knowledge is derived from traditional sampling methods (e.g., different types of trawls). The analysis of environmental DNA (eDNA) can provide increased knowledge, complementary to the traditional methods. In the present pilot study, we sampled eDNA from two geographical areas, north and west of Svalbard (NWS) and in the southwestern Barents Sea (SWBS). The combination of trawling, visual identification of mammals and eDNA collection facilitated a robust analysis of fish and marine mammal diversity and species composition. Through 12S MiFish metabarcoding of the eDNA samples, we found that incorporating eDNA data provided an additional level of information on both the diversity of fish and marine mammals in the study areas. By adding eDNA data to the trawl data, we found that richness increased from 32 to 49 fish taxa. Significant differences in diversity and composition of the fish communities were detected by eDNA between the two study areas. Considering degradation and dilution factors it is postulated that the results represent resident species to the Barents Sea and that long -transported DNA from other areas are less likely.

Bridging the gap: The integration of eDNA techniques and traditional sampling in fish diversity analysis

IntroductionBiodiversity loss poses a significant environmental challenge, particularly in aquatic ecosystems. The advent of environmental DNA (eDNA) sampling technology offers a promising tool for monitoring biological communities with purported high efficiency. Yet, its efficacy compared to traditional sampling methods remains underexplored, especially in fish diversity research.MethodsThis study conducted a comparative analysis of fish diversity and distribution across 29 sampling points within the rivers of the Changqing Nature Reserve, Central China, employing both eDNA techniques and traditional sampling methods.ResultsA total of 46 unique fish species were identified through this comprehensive approach. eDNA sampling detected 34 species, surpassing the 22 species identified by traditional methods. Interestingly, 10 species were detected by both methods, while traditional methods exclusively identified 12 species not detected by eDNA, and eDNA uniquely identified an additional 24 species. Despite eDNA's broader species detection range, traditional sampling methods typically yielded higher Shannon diversity index values. Both β-diversity indices (Bray-Curtis and Jaccard) and multivariate analyses (NMDS and PCoA) were applied, revealing no significant statistical differences in biodiversity measurement between the two sampling methods.DiscussionThe findings suggest that while eDNA sampling excels in identifying a wider range of species, it does not significantly outperform traditional methods in overall biodiversity assessment. By integrating both methodologies, this study demonstrates a more comprehensive and precise assessment of riverine biodiversity, underscoring the benefits of a synergistic approach for enhancing species detection and understanding distribution patterns. The combined methodology notably improves alpha diversity evaluations, particularly regarding Shannon diversity and Berger-Parker dominance. This integrated approach advocates for the amalgamation of data from both eDNA and conventional methods, fostering a robust and accurate biodiversity appraisal.

A review of non-invasive samples and tools in kala-azar diagnosis and test of cure

The recurrence of visceral leishmaniasis (VL), also called kala-azar (KA), in endemic regions of tropical countries like India, is primarily attributed to asymptomatic VL, post-kala azar dermal leishmaniasis (PKDL), and human immunodeficiency virus (HIV) co-infection. To effectively manage VL cases and elimination targets, an early and rapid diagnosis as well as accurate field surveillance is highly essential. The traditional sampling methods like bone marrow (BM), spleen, and lymph node (LN) tissue aspirations are invasive, painful, tedious, and prone to nosocomial infections, require skilled persons and hospital facilities, and are not feasible in rural areas. Therefore, there is an urgent requirement for the adoption of a patient-friendly, non-invasive, non-hospitalized sampling procedure that ensures an effective VL diagnosis. This review aims to meticulously evaluate the most recent scientific research that focuses on the precision, feasibility, and applicability of non-invasive sampling (NIS) and techniques for the diagnosis and test of cure of VL, particularly in resource-limited settings. Apart from that, the non-invasive techniques (NIT) that have shown promising results while monitoring VL treatment response and relapse are also reviewed. The limitations associated with NIT and possible improvements in this regard are discussed as well to improve the diagnosis and management of VL.

Arterial Pulse Wave Velocity Signal Reconstruction Using Low Sampling Rates.

Pulse Wave Velocity (PWV) analysis is valuable for assessing arterial stiffness and cardiovascular health and potentially for estimating blood pressure cufflessly. However, conventional PWV analysis from two transducers spaced closely poses challenges in data management, battery life, and developing the device for continuous real-time applications together along an artery, which typically need data to be recorded at high sampling rates. Specifically, although a pulse signal consists of low-frequency components when used for applications such as determining heart rate, the pulse transit time for transducers near each other along an artery takes place in the millisecond range, typically needing a high sampling rate. To overcome this issue, in this study, we present a novel approach that leverages the Nyquist-Shannon sampling theorem and reconstruction techniques for signals produced by bioimpedance transducers closely spaced along a radial artery. Specifically, we recorded bioimpedance artery pulse signals at a low sampling rate, reducing the data size and subsequently algorithmically reconstructing these signals at a higher sampling rate. We were able to retain vital transit time information and achieved enhanced precision that is comparable to the traditional high-rate sampling method. Our research demonstrates the viability of the algorithmic method for enabling PWV analysis from low-sampling-rate data, overcoming the constraints of conventional approaches. This technique has the potential to contribute to the development of cardiovascular health monitoring and diagnosis using closely spaced wearable devices for real-time and low-resource PWV assessment, enhancing patient care and cardiovascular disease management.

Research on a Two-stage Plane Adaptive Sampling Algorithm for Near-field Scanning Acceleration

As one of the most useful methods in electromagnetic interference (EMI) diagnosis, near-field (NF) scanning is widely used in electromagnetic compatibility (EMC) evaluation of complex devices under test (DUTs). In this paper, a two-stage plane adaptive sampling algorithm is proposed to reduce the acquisition time in the process of NF scanning and to make reconstruction of the radiation source more efficient. The sampling method is based on the region self-growth algorithm and the Voronoi subdivision principle, significantly reducing the number of NF samples in the stage of solving the radiation source model through uniform and non-uniform two-stage sampling. Two experiments were conducted to verify the correctness and effectiveness by comparing with the traditional uniform sampling method.

Monitoring the threatened Harttiella (Siluriformes, Loricariidae) with environmental DNA: A comparison between metabarcoding and targeted digital PCR

Abstract Environmental DNA has emerged as an efficient alternative to traditional sampling methods. A standard multispecies or a targeted single‐species approach can be used for analysing environmental DNA samples. The costs, benefits, and drawbacks associated with these two approaches are quite different. Here, a comparison between standard multispecies metabarcoding and targeted species assay using digital PCR (dPCR) for two threatened Harttiella species occurring in French Guiana (Harttiella lucifer and H. nsp. “Makwali”) was performed. Samples were collected in 11 sites of the upper Maroni River drainage basin and located in the Galbao mountain range, known to host the targeted species. The “Teleo” primer was used for the metabarcoding approach. To implement a new dPCR assay, specific primers and probes for the two targeted Harttiella species were developed. This targeted dPCR assay detected Harttiella in seven sites. All of these sites were also positive for metabarcoding detection, and the habitat characteristics were favourable for the species. This study demonstrated that both targeted (dPCR) and multispecies (metabarcoding) approaches can be used for the monitoring of the threatened H. lucifer and H. nsp. “Makwali” species. From a conservation point of view, we recommend to use the metabarcoding approach to update the spatial distribution of the species, while the dPCR method can be used for a temporal follow‐up of known Harttiella populations.

Improving wild bee monitoring, sampling methods, and conservation

Bees are the most important group of insect pollinators, but their populations are declining. To gain a better understanding of wild bee responses to different stressors (e.g. land-use change) and conservation measures, regional and national monitoring schemes are currently being established in Germany, which is used here as a model region, and in many other countries. We offer perspectives on how to best design future bee monitoring programs with a focus on evaluating the implementation of conservation measures. We discuss different traditional and novel sampling methods, their efficacy depending on research questions and the life-history traits of target species, and how greater standardization of wild bee sampling and monitoring methods can make data more comparable, contributing to the identification of general trends and mechanisms driving bee populations. Furthermore, the potential impact of bee sampling itself on bee populations is discussed.

MsDC-DEQ-Net: Deep Equilibrium Model (DEQ) with Multiscale Dilated Convolution for Image Compressive Sensing (CS)

Compressive sensing (CS) is a technique that enables the recovery of sparse signals using fewer measurements than traditional sampling methods. To address the computational challenges of CS reconstruction, our objective is to develop an interpretable and concise neural network model for reconstructing natural images using CS. We achieve this by mapping one step of the iterative shrinkage thresholding algorithm (ISTA) to a deep network block, representing one iteration of ISTA. To enhance learning ability and incorporate structural diversity, we integrate aggregated residual transformations (ResNeXt) and squeeze-and-excitation mechanisms into the ISTA block. This block serves as a deep equilibrium layer connected to a semi-tensor product network for convenient sampling and providing an initial reconstruction. The resulting model, called MsDC-DEQ-Net, exhibits competitive performance compared to state-of-the-art network-based methods. It significantly reduces storage requirements compared to deep unrolling methods, using only one iteration block instead of multiple iterations. Unlike deep unrolling models, MsDC-DEQ-Net can be iteratively used, gradually improving reconstruction accuracy while considering computation tradeoffs. Additionally, the model benefits from multiscale dilated convolutions, further enhancing performance.

The Application of a Mobile Unmanned Device for Monitoring Water and Sediment Pollution in the Port of Gdynia

Pollution in the Port of Gdynia can encompass various types of substances and contaminants that affect the quality of water and sediment in this region. Ships entering and leaving the port can release pollutants such as oil, fuel, waste, and chemicals into the water. Controlling and monitoring these pollutants is a crucial part of environmental stewardship. In recent years, uncrewed units have been increasingly in use for in situ water and sediment sampling. Boat-based water sampling crews face significant safety risks at sea. Eliminating the need for a boat-based sampling crew, uncrewed units allow sampling from locations that are difficult to access by traditional sampling methods. To validate the HydroDron-1 method, water samples and bottom sediments were collected from five basins in the Port of Gdynia using the HydroDron-1 method and accredited sampling methods. The values of measured parameters were similar for both methods. Using the HydroDron-1 method at the Port of Gdynia has the potential to improve safety while reducing sampling costs and increasing data collection. The project was implemented as part of the POLNOR 2019 Call program, announced by the National Center for Research and Development (NCRD): “Marine port surveillance and observation system using mobile unmanned research units” NOR/POLNOR/MPSS/0037/2019.

Soil electrical conductivity as a proxy for enhanced weathering in soils

To effectively monitor and verify carbon dioxide removal through enhanced weathering (EW), this study investigates the use of soil electrical conductivity (EC) and volumetric water content (θ) as proxies for alkalinity and dissolved inorganic carbon (DIC) in soil water. EC-θ sensors offer a cost-effective and straightforward alternative to traditional soil and water sampling methods. In a lab experiment, three different substrates were treated with NaHCO3 solutions to increase the alkalinity of the soil water and analyze the response. The combination of EC and θ to track the increase in carbonate alkalinity due to EW, and therefore CO2 consumption, is applicable for low cation exchange capacity (CEC) soil-substrates like the used quartz sand. However, the presence of organic material and pH-dependent CEC complicates the detection of clear weathering signals in soils. In organic-rich and clay-rich soils, only a high alkalinity addition has created a clear EC signal that could be distinguished from a non-alkaline baseline with purified water. Cation exchange experiments revealed that the used soil buffered alkalinity input and thereby might consume freshly generated alkalinity, initially mitigating CO2 uptake effects from EW application. Effective CEC changes with pH and pH buffering capacity by other pathways need to be considered when quantifying the CO2 sequestration potential by EW in soils. This should be estimated before the application of EW and should be part of the monitoring reporting and verification (MRV) strategy. Once the soil-effective CEC is raised, the weathering process might work differently in the long term.

A decade-long journey shed light on chemical composition and field determination of acid mine drainage in Brazil.

Regular monitoring of Acid Mine Drainage (AMD) is essential for understanding its extent and impact on water resources. Traditional manual sampling methods have limitations, such as limited representativeness and delayed lab analysis. High-frequency monitoring offers an alternative, enabling real-time analysis of AMD fluctuations and determination of constituents in the field. This study assessed a decade-long environmental monitoring database from watersheds impacted by coal mining in Brazil to analyze the relationships between physical properties and constituents from different water sources affected by AMD. Samples were grouped into four categories based on location and contamination levels. Results revealed that water samples from the two groups not affected by AMD exhibited near-neutral pH, low metal and sulfate concentrations, and a large portion of samples below the quantification limit for Mn and Al. In contrast, samples from groups affected by AMD displayed high metal and sulfate concentrations and acidic pH, with the highest contamination observed in the underground mine discharges group (AMD UMD). Spearman correlation analyzes between field (pH and electrical conductivity (EC)) and lab (SO42-, Fe, Mn, and Al) parameters showed no significant correlations in non-AMD-affected groups, but significant correlations in AMD-affected groups, particularly the Streams group. A regression model between sulfate and EC was identified as the best predictor for AMD, enabling continuous, low-cost monitoring of contaminated streams and providing insight into previously unobserved AMD processes, such as variations in contamination during storm events and river flushing.

EDNA metabarcoding reveals riverine fish community structure and climate associations in northeastern Canada

AbstractClimate change is a critical threat to northern freshwater ecosystems, yet many remote areas are data deficient in terms of biodiversity information. Generating community composition data through collection of environmental DNA (eDNA) is less labor‐intensive than traditional sampling methods and is being increasingly used in areas that have been historically difficult to sample such as northern freshwater habitats. Here, we employed eDNA metabarcoding using three mitochondrial markers at 174 coastal river sites, sampled over three years (2019–2021) across a broad region in northeastern North America, Newfoundland and Labrador. We characterized current riverine fish community composition, compared it to traditional sampling records, and quantified the influence of climate on variation in fish community composition. The analysis detected 33 fish species across the region (1–13 per location), including three non‐native species, as well as several new possible range expansions. Variance partitioning with redundancy analysis indicated ~56% of the variation in community composition could be explained by spatial and climate factors (~21% and ~7%, respectively, with an additional ~28% shared). A temporal comparison across a subset of locations with both eDNA and historical records (1965–1985) revealed that more species were detected on average with eDNA sampling, and that sampling method explained a small portion of the variation (~4%) in comparison with space (~10%) and climate (~7%). Ultimately, this work is the most complete survey of freshwater and diadromous fishes present in Newfoundland and Labrador to date, highlights new detections of non‐native species including previously unknown diversity for the region, and provides future direction for the application of eDNA analysis in northern riverine habitats.

Discovery of Prevalent Ciliophora, Discoba, and Copepoda Protists in Deep Sea Water by In Situ Nucleotide Extraction

Deep-sea eukaryotic microorganisms play a vital role in degrading organic matter and geochemically cycling elements in the deep ocean. However, the impact of sampling methods on detection of these microorganisms under high hydrostatic pressure remains uncertain. In this study, we compared a traditional water sampling method using a Niskin bottle, an in situ microbial filtration and fixation method (ISMIFF), and a multiple in situ nucleic acid collection (MISNAC) method to exhibit differences in the community structures that were collected at ~590–3100 m in the South China Sea (SCS). The classification and biodiversity indices of 18S rDNA Illumina sequencing reads from the V9 variation region revealed higher diversity for MISNAC DNA absorption column samples compared to others. Importantly, the relative abundance of Ciliophora (19.49%), Copepoda (23.31%), and Diplonemea (10.67%) was higher in MISNAC adsorption column samples, while Retaria (48.86%) were dominant in the MISNAC membrane samples. This indicates that MISNAC columns might collect more DNA in situ for the naked protists, while Retaria with a carbonate shell were more likely retained on the membrane. In conclusion, MISNAC is an effective method for DNA collection of deep-sea eukaryotic microorganisms and provides valuable materials for studying deep-sea microbial ecosystems.

Investigative Approaches for Pollutants in Water: Aligning with Water Framework Directive Maximum Allowable Concentrations

In the wake of rapid advancements in the pharmaceutical, food, and agricultural industries, the environment faces an increasing influx of diverse compounds, both intentionally and unintentionally released. These compounds fall into two categories: persistent and emerging pollutants. Persistent pollutants, characterized by their resistance to degradation and potential to accumulate in the environment, pose serious ecological threats. The Water Framework Directive (WFD) plays a pivotal role in monitoring and regulating these substances. This review discusses various contemporary analytical approaches to determine problematic substances, including benzo(a)pyrene, cypermethrin, dichlorvos, heptachlor, and heptachlor epoxide, aligning with the priorities outlined in the 2013 WFD classification. This review focuses on diverse water sampling methods, sample preparation techniques, and analytical methods, encompassing chromatographic, spectroscopic, and electrochemical approaches, with the primary goal of achieving the requirement laid on analytical methods used for the determination of maximum allowable concentrations defined in the WFD. Chromatographic methods, utilizing diverse mass spectrometers, have achieved detection limits as low as 10−6 μg/L, while modern electroanalytical techniques reach levels as low as 10−13 μg/L, reflecting an ongoing collective effort to enhance monitoring and safeguard the health of aquatic ecosystems. From sampling methods, large-volume sampling and passive sampling devices have been shown to be a cost-effective and modern solution, addressing limitations in traditional sampling methods, even if both of them face important pros and cons in terms of quantitative analysis.

Estimating truncation effects of quantum bosonic systems using sampling algorithms

To simulate bosons on a qubit- or qudit-based quantum computer, one has to regularize the theory by truncating infinite-dimensional local Hilbert spaces to finite dimensions. In the search for practical quantum applications, it is important to know how big the truncation errors can be. In general, it is not easy to estimate errors unless we have a good quantum computer. In this paper, we show that traditional sampling methods on classical devices, specifically Markov Chain Monte Carlo, can address this issue for a rather generic class of bosonic systems with a reasonable amount of computational resources available today. As a demonstration, we apply this idea to the scalar field theory on a two-dimensional lattice, with a size that goes beyond what is achievable using exact diagonalization methods. This method can be used to estimate the resources needed for realistic quantum simulations of bosonic theories, and also, to check the validity of the results of the corresponding quantum simulations.

Environmental DNA metabarcoding of water samples as a tool for monitoring Iberian freshwater fish composition.

Environmental DNA (eDNA) metabarcoding has been increasingly used to monitor the community assemblages of a wide variety of organisms. Here, we test the efficacy of eDNA metabarcoding to assess the composition of Iberian freshwater fishes, one of the most endangered groups of vertebrates in Spain. For this purpose, we sampled 12 sampling sites throughout one of Spain's largest basins, the Duero, which is home to approximately 70% of the genera and 30% of the primary freshwater fish in Spain. We sampled these sampling sites in the summer by using electrofishing, a traditional sampling method, and eDNA metabarcoding of river water samples using the mitochondrial 12S rRNA gene (12S) as a marker. We also resampled four of these sampling sites in autumn by eDNA. We compared the results obtained through eDNA metabarcoding with those of electrofishing surveys (ones conducted for the present study and past ones) and assessed the suitability of 12S as an eDNA metabarcoding marker for this group of freshwater fishes. We found that the 12S fragment, analysed for 25 Iberian species, showed sufficient taxonomic resolution to be useful for eDNA approaches, and even showed population-level differences in the studied populations across the tissue samples for Achondrostoma arcasii. In most cases, a greater number of species was detected through eDNA metabarcoding than through electrofishing. Based on our results, eDNA metabarcoding is a powerful tool to study the freshwater fish composition in the Iberian Peninsula and to unmask cryptic diversity. However, we highlight the need to generate a local genetic database for 12S gene for such studies and to interpret the results with caution when studying only mitochondrial DNA. Finally, our survey shows that the high detection sensitivity of eDNA metabarcoding and the non-invasiveness of this method allows it to act as a detection system for species of low abundance, such as early invasive species or species in population decline, two key aspects of conservation management of Spanish freshwater fishes.

Echolocation call characterization of insectivorous bats from caves and karst areas in southern Luzon Island, Philippines

Bats are excellent bioindicators and are increasingly used to assess ecosystem health and monitor changes in the environment. Due to increased awareness of the potential transmission of pathogens from bats to humans and recognizing the limitations of traditional bat sampling methods, the use of of non-invasive sampling techniques such as bat recorders were recommended for field-based monitoring studies. In the Philippines, however, bat bioacoustics is still a growing field, and the scarcity of acoustic data hinders the use of echolocation calls to conduct accurate inventories and population monitoring of echolocating bats. Here, we recorded and characterized echolocation calls of insectivorous bats from caves and karst areas located in southern Luzon Island, Philippines. In addition, we compared our results with other studies performed within and outside the country to identify possible regional and local variation in acoustic characters for some species. A total of 441 echolocation calls were recorded from six bat families: Hipposideridae (five species), Rhinolophidae (five species), Vespertilionidae (three species), Miniopteridae (two species), Megadermatidae (one species), and Emballonuridae (one species). Discriminant function analyses (DFA) with leave-one-out cross validation correctly classified bats emitting calls dominated with a constant frequency (CF) component (rhinolophids and hipposiderids) with >97% success and those producing frequency modulated (FM) calls (Miniopteridae and Vespertilionidae) with 88.9% success. We report echolocation calls for Philippine population of two species (Megaderma spasma and Hipposideros lekaguli) for the first time. Moreover, we present geographical variations in call frequencies for some species by comparing previously reported acoustic data elsewhere across the species’ range. This underscores the importance of establishing a readily accessible and comprehensive local reference library of echolocation calls which would serve as a valuable resource for examining taxonomic identities of echolocating bats, particularly those whose calls exhibit biogeographic variations.

Assessment of the partial saddle point approximation in field-theoretic polymer simulations.

Field-theoretic simulations are numerical treatments of polymer field theory models that go beyond the mean-field self-consistent field theory level and have successfully captured a range of mesoscopic phenomena. Inherent in molecularly-based field theories is a "signproblem" associated with complex-valued Hamiltonian functionals. One route to field-theoretic simulations utilizes the complex Langevin (CL) method to importance sample complex-valued field configurations to bypass the signproblem. Although CL is exact in principle, it can be difficult to stabilize in strongly fluctuating systems. An alternate approach for blends or block copolymers with two segment species is to make a "partial saddle point approximation" (PSPA) in which the stiff pressure-like field is constrained to its mean-field value, eliminating the signproblem in the remaining field theory, allowing for traditional (real) sampling methods. The consequences of the PSPA are relatively unknown, and direct comparisons between the two methods are limited. Here, we quantitatively compare thermodynamic observables, order-disorder transitions, and periodic domain sizes predicted by the two approaches for a weakly compressible model of AB diblock copolymers. Using Gaussian fluctuation analysis, we validate our simulation observations, finding that the PSPA incorrectly captures trends in fluctuation corrections to certain thermodynamic observables, microdomain spacing, and location of order-disorder transitions. For incompressible models with contact interactions, we find similar discrepancies between the predictions of CL and PSPA, but these can be minimized by regularization procedures such as Morse calibration. These findings mandate caution in applying the PSPA to broader classes of soft-matter models and systems.

Estimating the effectiveness of using wildlife cameras versus visual-encounter surveys to detect herpetofauna

Context Efficient monitoring of herpetofauna can prove challenging to agencies and NGOs responsible for their management. Wildlife cameras have been proposed as a method to monitor herpetofauna; however, estimates of detection rates and factors affecting detection by cameras are generally lacking and therefore limiting their application. Aims We determined the effect of body size and temperature differential on the detection of snakes and frogs by passive infrared (PIR) wildlife cameras. We hypothesised that detection would differ among models and be positively correlated with body size and surface-temperature differential between the animal and substrate. We then conducted a field study to compare the detection of herpetofauna by a traditional method with PIR cameras. Methods We tested 10 cameras of seven models on five snakes and one camera on six frogs. Photographs were downloaded to determine the detection rate of each species by each camera. We then chose a camera model to compare two herpetofauna survey methods, namely, drift fences equipped with cameras and visual-encounter surveys. Surveys were conducted monthly over 12 months in Irwin County, GA, USA. Key results The highest mean detection rates of snakes were 0.65 (s.e. = 0.33), 0.50 (s.e. = 0.34), and 0.49 (s.e. = 0.34) for the Browning Dark Ops, Reconyx Hyperfire 2, and Mossy Oak Covert Scouting Camera respectively. The detectability of larger snakes was greater than that of smaller snakes and increased as the absolute temperature differences between the snake and the substrate increased. The detectability of frogs was influenced by absolute temperature differential alone. PIR cameras generated five times more observations, documented more herpetofauna species, and were seven times more efficient than traditional surveys. Conclusions The effectiveness of PIR cameras to detect herpetofauna varies among models and depends on the likelihood that the animal will have a body temperature significantly different from the temperature of the substrate. PIR cameras generated observations far more efficiently than traditional sampling methods. Implications PIR wildlife cameras may be most effective at detecting larger, diurnal herpetofauna and least effective at detecting smaller, nocturnal species. Wildlife cameras have the potential to efficiently monitor some herpetofauna, providing a means to better evaluate management objectives.

Unveiling temporal variation in dissolved organic matter (DOM) with high-frequency spectroscopic measurements in a shallow eutrophic lake

ABSTRACT Dissolved organic matter (DOM) plays an important role in biogeochemistry of lake ecosystems. Studies measuring DOM at short intervals in lakes are rare, and thus its short-term dynamics are largely unknown. We investigated DOM temporal variation in large, shallow, eutrophic Lake Võrtsjärv (Estonia) during one growing season (May–Sep 2016) using a field-deployable in situ spectrometer to measure absorbance spectra (wavelength range 200–708 nm) at a 2 h interval coupled with monthly discrete water sampling. Collected spectra were analyzed together with some in-lake variables, lake metabolic rates, and meteorological and hydrological data using boosted regression tree (BRT) and random forest (RF) models. Different spectral parameters were used to assess total and allochthonous DOM quantity and relative share of autochthonous DOM. All parameters (i.e., DOM quantity and quality) varied on a large scale. For example, dissolved organic carbon (DOC) concentrations ranged from 12.0 to 17.3 mg L−1. High levels of DOM were mainly of allochthonous origin, and a strong relationship with inflow indicated the same. The relative share of autochthonous DOM increased with rising air temperature as primary production rose in warm water; however, we found no direct relationships with gross primary production. RF and BRT models explained up to 38% and 63% of DOM temporal variability, respectively. Our results showed that monthly water samples did not capture large variation in DOM. Therefore, high-frequency measurements using in situ spectrometry improve temporal representativeness of DOM monitoring in lakes compared to traditional sampling methods.