Gauging megadiversity with optimized and standardized sampling protocols: A case for tropical forest spiders

Characterizing and monitoring biodiversity and assessing its drivers require accurate and comparable data on species assemblages, which, in turn, should rely on efficient and standardized field collection. Unfortunately, protocols that follow such criteria remain scarce and it is unclear whether they can be applied to megadiverse communities, whose study can be particularly challenging. Here, we develop and evaluate the first optimized and standardized sampling protocol for megadiverse communities, using tropical forest spiders as a model taxon. We designed the protocol COBRA‐TF (Conservation Oriented Biodiversity Rapid Assessment for Tropical Forests) using a large dataset of semiquantitative field data from different continents. This protocol combines samples of different collecting methods to obtain as many species as possible with minimum effort (optimized) and widest applicability and comparability (standardized). We ran sampling simulations to assess the efficiency of COBRA‐TF (optimized, non‐site‐specific) and its reliability for estimating taxonomic, phylogenetic, and functional diversity, and community structure by comparing it with (1) commonly used expert‐based ad hoc protocols (nonoptimized, site‐specific) and (2) optimal protocols (optimized, site‐specific). We then tested the performance and feasibility of COBRA‐TF in the field. COBRA‐TF yielded similar results as ad hoc protocols for species (observed and estimated) and family richness, phylogenetic and functional diversity, and species abundance distribution. Optimal protocols detected more species than COBRA‐TF. Data from the field test showed high sampling completeness and yielded low numbers of singletons and doubletons. Optimized and standardized protocols can be as effective in sampling and studying megadiverse communities as traditional sampling, while allowing data comparison. Although our target taxa are spiders, COBRA‐TF can be modified to apply to any highly diverse taxon and habitat as long as multiple collecting techniques exist and the unit effort per sample is comparable. Protocols such as COBRA‐TF facilitate studying megadiverse communities and therefore may become essential tools for monitoring community changes in space and time, assessing the effects of disturbances and selecting conservation areas.     

Application of detectability in the use of indicator species: A case study with birds

The use of indicator species is popular in ecological monitoring and management. In recent years, new methods to improve the quality and application of indicator data have been proposed and developed. Here we propose the use of detection probability in the selection and application of indicator species. We evaluated environmental and observer factors believed to affect detection of potential species. Observer effects were the most evident factor and may necessitate the greatest consideration in the use of indicator species. Our results call attention to the fact that raw counts are far from accurate and that the use of detection probability can and should be incorporated into sampling protocols, species selection, and the allocation of effort for projects that use indicator species as part of monitoring and management programs.     

Changes in bird populations as criteria of environmental changes

Järvinen, O. and Väisänen, R. A. 1979. Changes in bird populations as criteria of environmental changes. – Holarct. Ecol. 2: 75-80.
Birds are a powerful tool of environmental monitoring, on account of their ecological diversity. Because of this, bird populations seem best suited for monitoring biological, possibly non-linear effects of specified environmental changes, such as habitat modification, and for "general monitoring" aimed at detecting unexpected environmental changes as they occur. Because many population changes have multiple causes, monitoring specific environmental changes is most rewarding if birds are grouped by e.g. habitat, major strategy (e.g. resident vs. migrant species), or feeding guild. A blueprint for a Nordic monitoring system based on breeding land birds is presented. Local trends may be atypical, and representative coverage of the major habitats in large areas should thus be ensured. As annual population fluctuations usually give little information in environmental monitoring, long-term projects are necessary. The line transect method seems applicable to many monitoring purposes, as it is rapid, inexpensive, relatively accurate, and suitable for sampling the northern terrestrial biota of the Holarctic region, probably including the temperate deciduous forests.     

环境DNA技术在贻贝入侵监测中的应用挑战

沼蛤(Limnoperna fortunei)和斑马贻贝(Dreissena polymorpha)是淡水系统中常见的入侵贻贝物种,对其种群规模的持续监测是入侵贻贝防治管控中的关键环节。随着分子生物学技术的发展,入侵物种监测中逐渐尝试利用环境DNA(eDNA)技术实现快速、灵敏检测。然而,在入侵物种引入-定植-扩散过程的监测中,eDNA技术的灵敏度及定量效果受到诸多因素的影响,给实际应用带来挑战。系统梳理了国内外学者利用eDNA技术监测沼蛤、斑马贻贝等入侵物种的研究进展;分析了eDNA技术的采样方案、引物设计、定量分析、质量保证、原位便携仪器设计等影响监测效率与准确率的关键环节;进一步探讨了eDNA技术在贻贝入侵监测中的优势和局限性,以及未来的改进方向。     

A probabilistic model for designing and assessing the performance of eDNA sampling protocols

Environmental DNA (eDNA) sampling, the detection of species‐specific genetic material in water samples, is an emerging tool for monitoring aquatic invasive species. Optimizing eDNA sampling protocols can be challenging because there is imperfect understanding of how each step of the protocol influences its sensitivity. This paper develops a probabilistic model that characterizes each step of an eDNA sampling protocol to evaluate the protocol's overall detection sensitivity for one sample. The model is then applied to analyse how changes over time made to the eDNA sampling protocol to detect bighead (BH) and silver carp (SC) eDNA have influenced its sensitivity, and hence interpretation of the results. The model shows that changes to the protocol have caused the sensitivity of the protocol to fluctuate. A more efficient extraction method in 2013, new species‐specific markers with a qPCR assay in 2014, and a more efficient capture method in 2015 have improved the sensitivity, while switching to a larger elution volume in 2013 and a smaller sample volume in 2015 have reduced the sensitivity. Overall, the sensitivity of the current protocol is higher for BH eDNA detection and SC eDNA detection compared to the original protocol used from 2009 to 2012. The paper shows how this model of eDNA sampling can be used to evaluate the effect of proposed changes in an eDNA sampling and analysis protocol on the sensitivity of that protocol to help researchers optimize their design.     

Estimating linear temporal trends from aggregated environmental monitoring data

Trend estimates are often used as part of environmental monitoring programs. These trends inform managers (e.g., are desired species increasing or undesired species decreasing?). Data collected from environmental monitoring programs is often aggregated (i.e., averaged), which confounds sampling and process variation. State-space models allow sampling variation and process variations to be separated. We used simulated time-series to compare linear trend estimations from three state-space models, a simple linear regression model, and an auto-regressive model. We also compared the performance of these five models to estimate trends from a long term monitoring program. We specifically estimated trends for two species of fish and four species of aquatic vegetation from the Upper Mississippi River system. We found that the simple linear regression had the best performance of all the given models because it was best able to recover parameters and had consistent numerical convergence. Conversely, the simple linear regression did the worst job estimating populations in a given year. The state-space models did not estimate trends well, but estimated population sizes best when the models converged. We found that a simple linear regression performed better than more complex autoregression and state-space models when used to analyze aggregated environmental monitoring data.     

Demographic modeling and monitoring cycle in a long-lived endangered shrub

Demographic monitoring is a well established tool for conservation managers. But, monitoring programs typically do not offer methods to explore the relationship between projected population trends and the probability of trend detection. Moreover, conservation biologists need to evaluate and incorporate the effect of variability and habitat perturbation on the efficiency of monitoring programs.We studied population demography of an endangered shrub endemic to East Central Spain, Vella pseudocytisus subsp. paui in order to understand its present demographic performance, how it is affected by increasing variability and perturbation and how these two factors are related to monitoring and monitoring thresholds.Using Lefkovich demographic matrices on six years of data, we produced 19 different population projections, and we compared these modeled projections against observed projection. We designated three conceptually important detection thresholds: an early warning; an unequivocal signal; and, a quasi-extinction threshold. Based on calculated detection times of all models for every threshold, we produced an averaged monitoring cycle (minimum visit frequency) to provide managers with a tool to design a consistent monitoring program for this plant.Our results indicate a relatively stable current population along with large detection times for critical threshold changes of modeled populations when considering small management changes (low population variability and low perturbation intensity). In contrast, model combinations incorporating high population variance and high perturbation produce disproportionally short times to detection of a significant population trend. In terms of designing studies to maximise results while minimising monitoring effort, designing a monitoring program capable of providing an early warning system of potential population failure requires more effort than detecting an unequivocal signal of decline.Finally, we propose two alternatives when calculating monitoring cycle (MC) values. One of them implies demographic MC if population perturbation and variation are high. For that, an optimal monitoring cycle is estimated based on a range of possible scenarios for population trends. Alternatively, we propose environmental MC, when low values of perturbation and variation are expected.     

PCR for bioaerosol monitoring: sensitivity and environmental interference.

The PCR technique has potential for use in detection of low concentrations of airborne microorganisms. In this study, the sensitivity of PCR and its susceptibility to environmental interference were assessed with Escherichia coli DH1 as the target organism. Air samples, containing environmental bioaerosols, were collected with AGI-30 samplers and seeded with E. coli DH1 cells. Parallel studies were performed with cells seeded into the sampler prior to collection of air samples to determine the effects of environmental inhibition and sampling stress on the PCR assay. Baseline studies were also performed without environmental challenge or sampling stress to compare two protocols for cell lysis, solid phase and freeze-thaw. Amplification of a plasmid target sequence resulted in a detection limit of a single bacterial cell by the freeze-thaw and solid-phase methods within 5 and 9 h, respectively. With a genomic target, the sensitivity of the solid-phase method was 10-fold lower than that of freeze-thaw. Samples which contained 10(3) to 10(4) CFU of environmental organisms per m3 inhibited amplification; however, a 1/10 dilution of these samples resulted in successful amplifications. No difference in sensitivity of the PCR assay was obtained as a result of sampling stress, although a 10-fold decrease in culturability was observed. A field validation of the protocol with genomic primers demonstrated the presence of airborne E. coli and/or Shigella spp. in outdoor samples. This study indicates that the PCR method for detection of airborne microorganisms is rapid and sensitive and can be used as an alternative method for air quality monitoring.     

The international program on plant bioassays and the report of the follow-up study after the hands-on workshop in China.

Among the seven plant bioassays reviewed by the US Environmental Protection Agency (EPA) Gene-Tox program in 1980, the Allium/Vicia root tip chromosome aberration assay and the Tradescantia stamen hair mutation and micronucleus assays were adopted by the International Program on Plant Bioassays (IPPB) for monitoring or testing environmental pollutants. These assays are highly sensitive and capable of detecting mutagens, clastogens and carcinogens from the environment. They are effective in situ monitors. These bioassays were validated and their protocols were standardized through a program under the International Program on Chemical Safety (IPPB), the precursor of the IPPB program which currently is in operation under the auspices of the United Nations Environment Program (UNEP). Six different categories of environmental studies, ranging from wastewater, surface or ground water, soil samples, ambient air, pesticides, and radiation, were carried out and are reported in this special issue. The mission of the IPPB/UNEP is to use these bioassays to monitor or test environmental mutagens and clastogens in the air, water, and soil to safeguard the quality of these essential elements in life and to use these simple and clear indicators of pollution damage as the tool for environmental education for the general public. The published reports of the monitoring and testing results will establish the database for environmental conditions in a number of locations around the world. An international monitoring network for the detection of genotoxicity of environmental pollutants is being established under the auspices of UNEP to protect the global environment.     

A Three-Tiered Approach to Long Term Monitoring Program Optimization

Long term monitoring optimization (LTMO) has proved a valuable method for reducing costs, assuring proper remedial decisions are made, and streamlining data collection and management requirements over the life of a monitoring program. A three-tiered approach for LTMO has been developed that combines a qualitative evaluation with an evaluation of temporal trends in contaminant concentrations, and a spatial statistical analysis. The results of the three evaluations are combined to determine the degree to which a monitoring program addresses the monitoring program objectives, and a decision algorithm is applied to assess the optimal frequency of monitoring and spatial distribution of the components of the monitoring network. Ultimately, application of the three-tiered method can be used to identify potential modifications in sampling locations and sampling frequency that will optimally meet monitoring objectives. To date, the three-tiered approach has been applied to monitoring programs at 18 sites and has been used to identify a potential average reduction of over one-third of well sampling events per year. This paper discusses the three-tiered approach methodology, including data compilation and site screening, qualitative evaluation decision logic, temporal trend evaluation, and spatial statistical analysis, illustrated using the results of a case study site. Additionally, results of multiple applications of the three-tiered LTMO approach are summarized, and future work is discussed.     

A Three-Tiered Approach to Long Term Monitoring Program Optimization

Long term monitoring optimization (LTMO) has proved a valuable method for reducing costs, assuring proper remedial decisions are made, and streamlining data collection and management requirements over the life of a monitoring program. A three-tiered approach for LTMO has been developed that combines a qualitative evaluation with an evaluation of temporal trends in contaminant concentrations, and a spatial statistical analysis. The results of the three evaluations are combined to determine the degree to which a monitoring program addresses the monitoring program objectives, and a decision algorithm is applied to assess the optimal frequency of monitoring and spatial distribution of the components of the monitoring network. Ultimately, application of the three-tiered method can be used to identify potential modifications in sampling locations and sampling frequency that will optimally meet monitoring objectives. To date, the three-tiered approach has been applied to monitoring programs at 18 sites and has been used to identify a potential average reduction of over one-third of well sampling events per year. This paper discusses the three-tiered approach methodology, including data compilation and site screening, qualitative evaluation decision logic, temporal trend evaluation, and spatial statistical analysis, illustrated using the results of a case study site. Additionally, results of multiple applications of the three-tiered LTMO approach are summarized, and future work is discussed.     

Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.     

环境质量评价中的生物指示与生物监测

通过比较生物指示与生物监测技术和仪器分析技术的分析过程及原理,结合北京市土壤中土壤脲酶与土壤重金属含量之间的相关关系的案例,及生物指示与生物监测技术在水生生态系统及大气污染研究中的应用状况,系统阐述了生物指示与生物监测技术研究的发展历程、研究前沿及发展方向.指出定量校正及不同学科与地区的科学团队的合作是生物指示与生物监测技术研究中需要克服的关键问题,并提出生物指示与生物监测技术研究的目标是整合不同学科的研究方向,为人类健康与环境安全的保护与预测提供技术支持.     

Estimating occupancy dynamics for large‐scale monitoring networks: amphibian breeding occupancy across protected areas in the northeast United States

Regional monitoring strategies frequently employ a nested sampling design where a finite set of study areas from throughout a region are selected and intensive sampling occurs within a subset of sites within the individual study areas. This sampling protocol naturally lends itself to a hierarchical analysis to account for dependence among subsamples. Implementing such an analysis using a classic likelihood framework is computationally challenging when accounting for detection errors in species occurrence models. Bayesian methods offer an alternative approach for fitting models that readily allows for spatial structure to be incorporated. We demonstrate a general approach for estimating occupancy when data come from a nested sampling design. We analyzed data from a regional monitoring program of wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in vernal pools using static and dynamic occupancy models. We analyzed observations from 2004 to 2013 that were collected within 14 protected areas located throughout the northeast United States. We use the data set to estimate trends in occupancy at both the regional and individual protected area levels. We show that occupancy at the regional level was relatively stable for both species. However, substantial variation occurred among study areas, with some populations declining and some increasing for both species. In addition, When the hierarchical study design is not accounted for, one would conclude stronger support for latitudinal gradient in trends than when using our approach that accounts for the nested design. In contrast to the model that does not account for nesting, the nested model did not include an effect of latitude in the 95% credible interval. These results shed light on the range‐level population status of these pond‐breeding amphibians, and our approach provides a framework that can be used to examine drivers of local and regional occurrence dynamics.     

Towards a global terrestrial species monitoring program

The Convention on Biological Diversity's strategic plan lays out five goals: “(A) address the underlying causes of biodiversity loss by mainstreaming biodiversity across government and society; (B) reduce the direct pressures on biodiversity and promote sustainable use; (C) improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity; (D) enhance the benefits to all from biodiversity and ecosystem services; (E) enhance implementation through participatory planning, knowledge management and capacity building.” To meet and inform on the progress towards these goals, a globally coordinated approach is needed for biodiversity monitoring that is linked to environmental data and covers all biogeographic regions. During a series of workshops and expert discussions, we identified nine requirements that we believe are necessary for developing and implementing such a global terrestrial species monitoring program. The program needs to design and implement an integrated information chain from monitoring to policy reporting, to create and implement minimal data standards and common monitoring protocols to be able to inform Essential Biodiversity Variables (EBVs), and to develop and optimize semantics and ontologies for data interoperability and modelling. In order to achieve this, the program needs to coordinate diverse but complementary local nodes and partnerships. In addition, capacities need to be built for technical tasks, and new monitoring technologies need to be integrated. Finally, a global monitoring program needs to facilitate and secure funding for the collection of long-term data and to detect and fill gaps in under-observed regions and taxa. The accomplishment of these nine requirements is essential in order to ensure data is comprehensive, to develop robust models, and to monitor biodiversity trends over large scales. A global terrestrial species monitoring program will enable researchers and policymakers to better understand the status and trends of biodiversity.     

Environmental DNA facilitates accurate,inexpensive, and multiyear population estimates of millions of anadromous fish

Although environmental DNA shed from an organism is now widely used for species detection in a wide variety of contexts, mobilizing environmental DNA for management requires estimation of population size and trends in addition to assessing presence or absence. However, the efficacy of environmental‐DNA‐based indices of abundance for long‐term population monitoring have not yet been assessed. Here we report on the relationship between six years of mark‐recapture population estimates for eulachon (Thaleichthys pacificus) and “eDNA rates” which are calculated from the product of stream flow and DNA concentration. Eulachon are a culturally and biologically important anadromous fish that have significantly declined in the southern part of their range but were historically rendered into oil and traded. Both the peak eDNA rate and the area under the curve of the daily eDNA rate were highly predictive of the mark‐recapture population estimate, explaining 84.96% and 92.53% of the deviance, respectively. Even in the absence of flow correction, the peak of the daily eDNA concentration explained an astonishing 89.53% while the area under the curve explained 90.74% of the deviance. These results support the use of eDNA to monitor eulachon population trends and represent a >80% cost savings over mark‐recapture, which could be further increased with automated water sampling, reduced replication, and focused temporal sampling. Due to its logistical ease and affordability, eDNA sampling can facilitate monitoring a larger number of rivers and in remote locations where mark‐recapture is infeasible.     

Impact of water quality on macroinvertebrate assemblages along a tropical stream in Kenya

Prudent management of lotic systems requires information on their ecological status that can be estimated by monitoring water quality and biodiversity attributes. To understand environmental conditions in Gatharaini drainage basin in Central Kenya, a study was carried out to establish the relationship between water quality and macroinvertebrate assemblages between the months of March and September 1996. Six sampling sites, each 25 m long were selected along a 24‐km stretch of the stream, which drained land under agricultural, residential and industrial use. Water physico‐chemical data was explored using multivariate analysis of Principal Component Analysis to detect environmental trends downstream. Both macroinvertebrates and water physico‐chemical data of suggested trends were analysed for variations and correlations. Temperatures and invertebrate densities changed significantly between the dry and wet season (P < 0.01) but the fluctuations were not evident downstream. Water physico‐chemical characteristics (total dissolved solids (TDS), pH, turbidity, dissolved oxygen) and biodiversity indices (species richness, diversity, dominance, evenness) changed markedly downstream (P < 0.01). Biodiversity indices correlated inversely with TDS, pH and turbidity but positively with dissolved O₂. It was evident macroinvertebrate assemblages changed significantly downstream as opposed to functional feeding groups. Diptera was important in most sites whilst Oligochaeta dominance increased downstream corresponding to the deterioration in water quality. Collectors/browsers were the dominant functional feeding groups at most sites. This study showed that significant changes in aquatic macroinvertebrate assemblages were primarily due to water quality rather than prevailing climatic conditions.