Temporal Replication Research Articles

Optimizations for time and effort in long-term monitoring: a case study using a multidecadal terrestrial salamander monitoring program

Long-term monitoring programs can identify environmental trends or reveal limitations to protocols, as long as their results are analysed appropriately. While monitoring programs are not necessarily hypothesis-driven, their data are important for conservation and can guide improvements to monitoring programs. Here, we present a case study using dynamic occupancy models to guide the optimization of time and effort in a long-term terrestrial salamander monitoring program. To ensure a detailed analysis, we analysed the available long-term data to first identify estimates of occupancy and detection parameters for the salamanders. Using these estimates, we created simulations to identify the optimal number of years for monitoring and the optimal allocation of spatial and temporal survey replicates. Our data support previous claims that monitoring programs should be allowed to run for at least a decade. We also found that in order to obtain accurate estimates of species occupancy, programs should consider appropriate partitioning of monitoring effort across spatial and temporal scales. We show how analyses of long-term monitoring datasets are valuable not only for trend detection but also for the development of templates to guide the design and optimization of similar programs.

Testing performance of large-scale surveys in determining trends for the critically endangered Great Indian Bustard Ardeotis nigriceps

Great Indian Bustard (GIB) is listed as Critically Endangered, with less than 250 individuals surviving in three fragmented populations. The species is under tremendous threat due to various anthropogenic pressures. Effective management and conservation of GIB requires a proper monitoring protocol, which we propose using an occupancy framework approach to detect changes in the species’ population. We used occupancy estimates from various landscape level surveys and simulated scenarios to evaluate the effectiveness of the proposed protocol. Our result showed there is >70% chance of detecting 100% change in the occupancy with 100 sampling sites and 10 temporal replicates. While with double sampling sites, the same change can be detected with 4–6 temporal replicates. In absence of a robust population estimation method, we argue for the use of occupancy as a surrogate to detect change in population as it provides better insights for rare elusive species such as GIB. Our proposed methodological framework is more precise than previous methods, which will help in evaluating efficacy of management interventions proposed and the implementation of species recovery plans.

Commensal bacterial sharing does not predict host social associations in kangaroos.

Social network analysis has been postulated as a tool to study potential pathogen transmission in wildlife but is resource-intensive to quantify. Networks based on bacterial genotypes have been proposed as a cost-effective method for estimating social or transmission network based on the assumption that individuals in close contact will share commensal bacteria. However, the use of network analysis to study wild populations requires critical evaluation of the assumptions and parameters these models are founded on. We test (a) whether networks of commensal bacterial sharing are related to hosts' social associations and hence could act as a proxy for estimating transmission networks, (b) how the parameters chosen to define host associations and delineate bacterial genotypes impact inference and (c) whether these relationships change across time. We use stochastic simulations to evaluate how uncertainty in parameter choice affects network structure. We focused on a well-studied population of eastern grey kangaroos (Macropus giganteus), from Sundown National Park, Australia. Using natural markings, each individual was identified and its associations with other kangaroos recorded through direct field observations over 2years to construct social networks. Faecal samples were collected, Escherichia coli was cultured and genotyped using BOX-PCR, and bacterial networks were constructed. Two individuals were connected in the bacterial network if they shared at least one E.coli genotype. We determined the capacity of bacterial networks to predict the observed social network structure in each year. We found little support for a relationship between social association and dyadic commensal bacterial similarity. Thresholds to determine host associations and similarity cut-off values used to define E.coli genotypes had important ramifications for inferring links between individuals. In fact, we found that inferences can show opposite patterns based on the chosen thresholds. Moreover, no similarity in overall bacterial network structure was detected between years. Although empirical disease transmission data are often unavailable in wildlife populations, both bacterial networks and social networks have limitations in representing the mode of transmission of a pathogen. Our results suggest that caution is needed when designing such studies and interpreting results.

The effects of spatial and temporal replicate sampling on eDNA metabarcoding.

BackgroundThe heterogeneous nature of environmental DNA (eDNA) and its effects on species detection and community composition estimates has been highlighted in several studies in the past decades. Mostly in the context of spatial distribution over large areas, in fewer occasions looking at spatial distribution within a single body of water. Temporal variation of eDNA, similarly, has mostly been studied as seasonality, observing changes over large periods of time, and often only for small groups of organisms such as fish and amphibians.MethodsWe analyzed and compared small-scale spatial and temporal variation by sampling eDNA from two small, isolated dune lakes for 20 consecutive weeks. Metabarcoding was performed on the samples using generic COI primers. Molecular operational taxonomic unit (MOTUs) were used to assess dissimilarities between spatial and temporal replicates.ResultsOur results show large differences between samples taken within one lake at one point in time, but also expose the large differences between temporal replicates, even those taken only 1 week apart. Furthermore, between-site dissimilarities showed a linear correlation with time frame, indicating that between-site differences will be inflated when samples are taken over a period of time. We also assessed the effects of PCR replicates and processing strategies on general patterns of dissimilarity between samples. While more inclusive PCR replicate strategies lead to higher richness estimations, dissimilarity patterns between samples did not significantly change.ConclusionsWe conclude that the dissimilarity of temporal replicates at a 1 week interval is comparable to that of spatial replicate samples. It increases, however, for larger time intervals, which suggests that population turnover effects can be stronger than community heterogeneity. Spatial replicates alone may not be enough for optimal recovery of taxonomic diversity, and cross-comparisons of different locations are susceptible to inflated dissimilarities when performed over larger time intervals. Many of the observed MOTUs could be classified as either phyto- or zooplankton, two groups that have gained traction in recent years as potential novel bio-indicator species. Our results, however, indicate that these groups might be susceptible to large community shifts in relatively short periods of time, highlighting the need to take temporal variations into consideration when assessing their usability as water quality indicators.

Inter‐annual monitoring improves diversity estimation of tropical butterfly assemblages

AbstractMonitoring programs for diverse tropical butterfly assemblages are scarce, and temporal diversity patterns in these assemblages are poorly understood. We adopted an additive partitioning approach to determine how temporal butterfly species richness was structured at the levels of days, months, and years in five tropical/subtropical sites across three continents covering up to 9 years of monitoring. We found that observed butterfly richness was not uniformly distributed across temporal extents. Butterfly species composition differed across months and years, potentially accounting for the fact that temporal butterfly species richness contributed a high proportion to total species richness. We further examined how species richness of common and uncommon species (> and <0.5% of total abundance, respectively) were structured across temporal extents. The results showed that the common species relative contribution to total species richness was higher at lower‐temporal levels, whereas uncommon species contributed more at higher‐temporal resolutions. This suggests that long‐term sampling will be more effective in capturing patterns of rare species and the total species pool while lower‐temporal level sampling (e.g., daily or weekly) may be more useful in examining common species demographic patterns. We therefore encourage careful consideration of temporal replication at different extents in developing butterfly monitoring schemes. Long‐term monitoring is essential for improvement in the resolution of species estimation and diversity patterns for tropical ecosystems.Abstract in Chinese is available with online material.

Passive acoustic monitoring as a potential tool to survey animal and ecosystem processes in freshwater environments

Abstract Biodiversity in freshwater habitats is decreasing faster than in any other type of environment, mostly as a result of human activities. Monitoring these losses can help guide mitigation efforts. In most studies, sampling strategies predominantly rely on collecting animal and vegetal specimens. Although these techniques produce valuable data, they are invasive, time‐consuming and typically permit only limited spatial and temporal replication. There is need for the development of complementary methods. As observed in other ecosystems, freshwater environments host animals that emit sounds, either to communicate or as a by‐product of their activity. The main freshwater soniferous groups are amphibians, fish, and macroinvertebrates (mainly Coleoptera and Hemiptera, but also some Decapoda, Odonata, and Trichoptera). Biophysical processes such as flow or sediment transport also produce sounds, as well as human activities within aquatic ecosystems. Such animals and processes can be recorded, remotely and autonomously, and provide information on local diversity and ecosystem health. Passive acoustic monitoring (PAM) is an emerging method already deployed in terrestrial environments that uses sounds to survey environments. Key advantages of PAM are its non‐invasive nature, as well as its ability to record autonomously and over long timescales. All these research topics are the main aims of ecoacoustics, a new scientific discipline investigating the ecological role of sounds. In this paper, we review the sources of sounds present in freshwater environments. We then underline areas of research in which PAM may be helpful emphasising the role of PAM for the development of ecoacoustics. Finally, we present methods used to record and analyse sounds in those environments. Passive acoustics represents a potentially revolutionary development in freshwater ecology, enabling continuous monitoring of dynamic bio‐physical processes to inform conservation practitioners and managers.

Assessing arrays of multiple trail cameras to detect North American mammals.

Motion triggered camera traps are an increasingly popular tool for wildlife research and can be used to survey for multiple species simultaneously. As with all survey techniques, it is crucial to conduct camera trapping research following study designs that include adequate spatial and temporal replication, and sufficient probability of detecting species presence. The use and configuration of multiple camera traps within a single survey site are understudied considerations that could have a substantial impact on detection probability. Our objective was to test the role that camera number (one, two or three units), and spacing along a linear transect (100 m or 150 m), have on the probability of detecting a species given it is present. From January to March, 2017 we collected data on six mammal species in Maine, USA: coyote (Canis latrans), fisher (Pekania pennanti), American marten (Martes americana), short-tailed weasel (Mustela erminea), snowshoe hare (Lepus americanus), and American red squirrel (Tamiasciurus hudsonicus). We used multi-scale occupancy modelling to compare pooled detection histories of different configuration of five cameras deployed at the same survey site (n = 32), and how the configuration would influence the probability of detecting a species given it was available at the site. Across all six species, we found substantial increases in probability of detection as the number of cameras increased from one to two (22 to 400 percent increase), regardless of the spacing between cameras. For most species the magnitude of the increase was less substantial when adding a third camera (4 to 85 percent increase), with coyote and snowshoe hare showing a pronounced effect. The influence of survey station features also varied by species. We suggest that using pooled data from two or three cameras at a survey site is a cost effective approach to increase detection success over a single camera.

Time-lapsing biodiversity: An open source method for measuring diversity changes by remote sensing

Understanding biodiversity changes in time is crucial to promptly provide management practices against diversity loss. This is overall true when considering global scales, since human-induced global change is expected to make significant changes on the Earth's biota. Biodiversity management and planning is mainly based on field observations related to community diversity, considering different taxa. However, such methods are time and cost demanding and do not allow in most cases to get temporal replicates. In this view, remote sensing can provide a wide data coverage in a short period of time. Recently, the use of Rao's Q diversity as a measure of spectral diversity has been proposed in order to explicitly take into account differences in a neighbourhood considering abundance and relative distance among pixels. The aim of this paper was to extend such a measure over the temporal dimension and to present an innovative approach to calculate remotely sensed temporal diversity. We demonstrated that temporal beta-diversity (spectral turnover) can be calculated pixel-wise in terms of both slope and coefficient of variation and further plotted over the whole matrix / image. From an ecological and operational point of view, for prioritisation practices in biodiversity protection, temporal variability could be beneficial in order to plan more efficient conservation practices starting from spectral diversity hotspots in space and time. In this paper, we delivered a highly reproducible approach to calculate spatio-temporal diversity in a robust and straightforward manner. Since it is based on open source code, we expect that our method will be further used by several researchers and landscape managers.

Chronic phosphorus enrichment and elevated pH suppresses Quercus spp. leaf litter decomposition in a temperate forest

The potential of excessive nitrogen (N) suppressing litter decay in is widely recognized. The role of phosphorus (P) in plant litter decay is less understood and is generally assumed to have a weak influence in decomposition outside tropical or wetland ecosystems. Based on the “microbial mining” hypothesis that suggests the availability of limiting nutrients is the driving mechanism of decay, P could have a strong influence on carbon (C) cycling in low-P ecosystems. The objective of this study was to determine if increasing P availability will influence the decomposition of leaf litter in a low-P temperate forested ecosystem. If the availability of a limiting nutrient is a driving mechanism mediating decay, then increasing the availability of P in a low-P environment should inhibit decay. The experiment was held in a low-P mixed mesophytic forest in the unglaciated Alleghany Plateau (USA). Since 2009, P availability has been increased either directly by phosphate fertilizer and/or indirectly by raising soil pH. Starting in 2012 and for three consecutive years, Quercus spp. leaf litter bags were deployed and harvested at least every year for three years for temporal replication. After three years, elevating pH and/or P litter mass loss was ∼52% and significantly (P < 0.001) lower than the control at 73% mass loss. The mean residence time (MRT; k yr−1) for the control was 2.1 years, but elevating P with pH increased MRT to 5.3 years. Results support the “microbial phosphorus mining” hypothesis that P has the potential to inhibit decay for Quercus spp. leaf litter in temperate forests and potentially increase soil C.

Butterfly diversity and effect of temperature and humidity gradients on butterfly assemblages in a sub-tropical urban landscape

The butterfly assemblages of urban ecosystems of Delhi were studied for a period of one year to investigate their diversity. The objective of the study was to understand the dynamics of the butterfly assemblages with respect to changing temperature and humidity levels. We tested the hypothesis that the diversity of butterflies would differ significantly across sampling period owing to pronounced temperature and relative humidity differences throughout the year. The Pollard walk method was used for butterfly survey. Twelve months of intensive sampling at four study sites with 24 temporal replicates per site yielded 14,913 individuals belonging to 75 species. Butterfly community showed a biannual peak of species richness and abundance. The maximum diversity was recorded in the pre-monsoon period between the months of April and May unlike most other studies from India which have reported April–May as the months of lowest diversity. The lowest diversity was observed during winter. Previous studies have shown that tropical insect communities have higher diversity during high precipitation periods. In this study, we found an additional peak of diversity during the pre-monsoon in addition to the post-monsoon months. The study quantitatively assessed community assemblages between ecosystems across a temperature gradient evaluating potential conservation role of natural areas and parks in urban landscapes.

Control of Eukaryotic DNA Replication Initiation-Mechanisms to Ensure Smooth Transitions.

DNA replication differs from most other processes in biology in that any error will irreversibly change the nature of the cellular progeny. DNA replication initiation, therefore, is exquisitely controlled. Deregulation of this control can result in over-replication characterized by repeated initiation events at the same replication origin. Over-replication induces DNA damage and causes genomic instability. The principal mechanism counteracting over-replication in eukaryotes is a division of replication initiation into two steps—licensing and firing—which are temporally separated and occur at distinct cell cycle phases. Here, we review this temporal replication control with a specific focus on mechanisms ensuring the faultless transition between licensing and firing phases.

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community.

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.

AMMI and GGE Biplot Analysis of Linseed (Linum usitatissimum L) Genotypes in Central and South-Eastern Highlands of Ethiopia

Twelve linseed genotypes were evaluated in 13 environments during the main cropping season in central highlands of Ethiopia. The objective of the study was to determine the magnitude and pattern of G × E interaction and yield stability in linseed genotypes. The study was conducted using randomized complete block design with 3 replications. Genotype × environment interaction and yield stability were estimated using the additive main effects and multiplicative interaction and site regression genotype plus genotype × environment interaction biplot. Pooled analysis of variance for seed yield showed significant (p ≤ 0.001) differences among the genotypes, environments and G × E interaction effects. This indicated that the genotypes differentially responded to the changes in the test environments or the test environments differentially discriminated the genotypes or both. Environment effect was responsible for the greatest part of the variation, followed by G × E interaction and genotype effects, indicating spatial and temporal replications of linseed yield trials. The first three multiplicative component terms of AMMI were found to be significant. The first two multiplicative component terms sum of squares, with their cumulative degrees of freedom of 44, explained 62.9% of the interaction sum of squares. No single variety showed superior performance in all environments but CI-1525 demonstrated top ranking at six of the thirteen environments. The application of AMMI and GGE biplots facilitated the visual comparison and identification of superior genotypes, thereby supporting decisions on variety selection and recommendation in different environments

Mathematical analysis of a tumour-immune interaction model: A moving boundary problem

A spatio-temporal mathematical model, in the form of a moving boundary problem, to explain cancer dormancy is developed. Analysis of the model is carried out for both temporal and spatio-temporal cases. Stability analysis and numerical simulations of the temporal model replicate experimental observations of immune-induced tumour dormancy. Travelling wave solutions of the spatio-temporal model are determined using the hyperbolic tangent method and minimum wave speeds of invasion are calculated. Travelling wave analysis depicts that cell invasion dynamics are mainly driven by their motion and growth rates. A stability analysis of the spatio-temporal model shows a possibility of dynamical stabilization of the tumour-free steady state. Simulation results reveal that the tumour swells to a dormant level.

Estimates of benthic invertebrate community variability and its environmental determinants differ between snapshot and trajectory designs

Long-term data sets are essential for biodiversity research and monitoring. Researchers use 2 major approaches in the study of temporal variability of biological communities: 1) the trajectory approach (monitoring sites across several consecutive years) and 2) the snapshot approach (comparing sites among few sampling events several years apart). We used data on benthic macroinvertebrate communities in 23 near-pristine forested streams to compare these 2 approaches for different study periods ranging from 3 to 14 y. We asked whether the level of temporal turnover and the identity of the best explanatory variables underlying it were comparable across studies based on differing approaches, study periods, or total duration. The 2 approaches yielded partly different stories about the level of community variability and its environmental correlates. With the snapshot approach, variation in community similarity and factors explaining it reflected short-term (e.g., year-specific) conditions, which could be misinterpreted as long-term trends, the difference being most evident for periods that began or ended in an extreme drought year. Our results imply that snapshot studies may lead to ambiguous conclusions, whereas the trajectory approach yielded more consistent results. Trajectory data of differing length showed minor differences, apart from studies with the shortest durations. Overall, our results suggest that time sequences of ∼6 y of trajectory data (i.e., 6 generations for most benthic invertebrates in boreal streams) may be needed for the among-year similarity of macroinvertebrate communities in near-pristine streams to stabilize. If temporal replication is limited (snapshots/very short time sequences) the outcome depends strongly on the particular years included in a comparison. Based on our results, we advise caution when basing conclusions on a comparison of a few (e.g., just 2) occasions several years apart or on very short time sequences.

The potential for citizen science to produce reliable and useful information in ecology

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference (design based, model based), and scientific paradigms (confirmatory, exploratory). We distinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass‐participation internet‐based projects with opportunistic data collection lacking sampling design, and examined overarching objectives, design, analysis, volunteer training, and performance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high‐quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state‐of‐the‐art analytical methods, and well‐supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.

Small dynamic mountainous rivers in Taiwan exhibit large sedimentary geochemical and provenance heterogeneity over multi-spatial scales

Taiwan rivers are characterized by extremely rapid mass wasting and sediment transfer due to active tectonics and frequent typhoons. Various methods have been applied to constrain processes affecting their sediment source-to-sink routing. In most cases, the sediment at the outlet is considered to be a representative average of the whole upstream basin due to the short sediment routes (<200 km). However, this assumption may be inappropriate because huge compositional heterogeneity can exist even within such small dynamic river systems. To reveal their intra-station and basin-wide geochemical heterogeneity, we collected sediment samples along the Zhuoshui and Liwu Rivers in Taiwan. Multiple samples deposited in different locations or with different grain-sizes were collected at each station, and the <63 μm fractions were measured for their elemental and Sr–Nd isotopic compositions. Elemental ratios and dimension-reducing technique were firstly applied to discriminate the sediment provenances. They show that the large elemental heterogeneity exists between samples at the same station and also between stations along each river, explainable by variable sediment mixing and local lithological heterogeneity. When combining our Sr–Nd isotopic data with literature data from Taiwan rivers, five discrete clusters of river sediments can be distinguished, reflecting the inter-catchment heterogeneity of sediment provenance in Taiwan Island. We also applied a Sr–Nd isotopic mixing model coupled with Monte-Carlo simulations to quantify the provenance heterogeneity in both rivers. The sediment contribution of the Western Foothills/Tailuko Belt to the Zhuoshui/Liwu downstream can vary by a factor of ∼2 between sediment samples that were considered as spatial or temporal replicates. Combined with field in-situ observations, we propose that fast-changing sediment transport modes cause the provenance heterogeneity in small dynamic mountainous rivers attacked by frequent heavy storms or typhoons. Sediments transported during different events and with different provenances can be preserved at each station, which leads to the intra-station and basin-wide geochemical heterogeneity. This study shows that “small” dynamic mountainous rivers can exhibit “large” geochemical and provenance heterogeneity over multi-spatial scales, and thus the common assumption that “let nature do the averaging” should be treated cautiously in this kind of river. Therefore, we propose several effective sediment sampling approaches on small mountainous rivers for reference. Future studies relying on detrital sediments, e.g. applying cosmogenic nuclides or Li isotopes, should also be aware of the heterogeneous nature in small mountainous rivers, because fast-changing provenances can simultaneously bias the weathering and erosion signals and lead to unrepresentative results.

Exploring population responses to environmental change when there is never enough data: a factor analytic approach

Abstract Temporal variability in the environment drives variation in vital rates, with consequences for population dynamics and life‐history evolution. Integral projection models (IPMs) are data‐driven structured population models widely used to study population dynamics and life‐history evolution in temporally variable environments. However, many datasets have insufficient temporal replication for the environmental drivers of vital rates to be identified with confidence, limiting their use for evaluating population level responses to environmental change. Parameter selection, where the kernel is constructed at each time step by randomly selecting the time‐varying parameters from their joint probability distribution, is one approach to including stochasticity in IPMs. We consider a factor analytic (FA) approach for modelling the covariance matrix of time‐varying parameters, whereby latent variable(s) describe the covariance among vital rate parameters. This decreases the number of parameters to estimate and, where the covariance is positive, the latent variable can be interpreted as a measure of environmental quality. We demonstrate this using simulation studies and two case studies. The simulation studies suggest the FA approach provides similarly accurate estimates of stochastic population growth rate to estimating an unstructured covariance matrix. We demonstrate how the latent parameter can be perturbed to show how selection on reproductive delays in the monocarp Carduus nutans changes under different environmental conditions. We develop a demographic model of the fire dependent herb Eryngium cuneifolium to show how a putative driver of the variation in environmental quality can be incorporated with the addition of a single parameter. Using perturbation analyses we determine optimal management strategies for this species. This approach estimates fewer parameters than previous approaches and allows novel eco‐evolutionary insights. Predictions on population dynamics and life‐history evolution under different environmental conditions can be made without necessarily identifying causal factors. Putative environmental drivers can be incorporated with relatively few parameters, allowing for predictions on how populations will respond to changes in the environment.

Underwater ecoacoustics as a monitoring tool in freshwater environments

Biodiversity in freshwater habitats is decreasing faster than in any other environment, mostly due to human activities. Monitoring these losses can help guide mitigation efforts. In most comparative or focal studies, sampling strategies predominantly rely on collecting animal and vegetal specimens. Although these techniques have produced valuable data, they are invasive, time-consuming, and typically have limited spatial and temporal replication. There is therefore a need for the development of complementary methods. As with other ecosystems and landscapes, freshwater environments host animals producing sounds, either to communicate or as a byproduct of their life activity. Animals and processes can be recorded, remotely, by unattended equipment and provide global information on local diversity and ecosystem health. We review practical examples of progress in experimentally addressing six main challenges that freshwater ecoacoustic monitoring faces: (1) associating each sound to its emitter, (2) estimating intra-specific sound variations, (3) evaluating diurnal variation, (4) modeling sound propagation, (5) deriving links between ecological condition and sounds, and (6) developing a repository for freshwater sounds. Passive acoustics represents a potentially revolutionary development in freshwater ecology, enabling dynamic monitoring of biophysical processes to inform conservation practitioners and managers.

Hand searching versus pitfall trapping: how to assess biodiversity of ground beetles (Coleoptera: Carabidae) in high altitude equatorial Andes?

The use of ground beetles (Coleoptera: Carabidae) as bioindicators of environmental change depends on the reliability and the effectiveness of the sampling methods. Those that have been tested in the temperate zone and in tropical forests still await experimentation in tropical high-altitude environments. For the first time, pitfall trapping and hand searching have been compared in Ecuadorian paramo above 4000 m a.s.l., in terms of practical effectiveness. The study was performed on six volcanoes and was based on the comparison of 28 sampling sessions (pitfall trapping and hand searching) performed along two different elevational belts [lower superparamo (LSP) and upper superparamo (USP)]. Analyses of sampling sessions showed that detected species richness is slightly higher with hand searching than with pitfall trapping, regardless of the elevation. Additionally, hand searching is more time-effective than pitfall trapping. The performance of the sampling method slightly varies when species assemblage composition is analysed in relation to elevational belts. In the LSP, hand searching and pitfall trapping should be simultaneously used to obtain exhaustive inventories of carabid biodiversity, since different species are likely to be collected by each method. In the USP, hand searching and pitfall trapping efficiency is very similar, but hand searching allows to collect a slightly larger number of species. Lastly, the sample-based rarefaction curves showed that four temporal replicates are mandatory to obtain a robust dataset and an exhaustive inventory of the true species richness and species assemblages composition. Our findings suggest a combined use of hand searching and pitfall trapping in the LSP, while both methods can be used alone for surveying carabids in the USP. Furthermore, hand searching is recommended if the aim is to obtain an inventory of species diversity, whereas pitfall trapping seems more convenient for fine grain ecological and comparative studies.