Ecological Monitoring Programs Research Articles

A multi-spectral fluorescence induction and relaxation (FIRe) technique for physiological and taxonomic analysis of phytoplankton communities

Phytoplankton are extraordinarily diverse, comprising 13 phylogenetic groups, with diatoms, dinoflagellates, and haptophytes among the most prominent eukaryotes in the ocean. Development of sensor technologies for rapid taxonomic and physiological analysis of phytoplankton communities is crucial for ecological monitoring programs in the global ocean. We describe a novel, ultra-sensitive, multi-spectral fluorescence induction and relaxation instrument (a mini-FIRe) and examine its analytical capability of rapidly determining phytoplankton taxonomic groups, as well as physiological characteristics and photosynthetic rates. We collected and analyzed the database of spectral and photosynthetic properties of major taxonomic groups of phytoplankton. We revealed that the spectral shape of the functional absorption cross-section of Photosystem II (PSII), sPSII(lex), is remarkably constrained within each major phylogenetic group of eukaryotic phytoplankton, including diatoms, haptophytes, dinoflagellates, and chlorophytes. Variability in sPSII(lex) within each group was significantly smaller than the difference between groups. We also examined the classical excitation spectra of chl a fluorescence yields, Fm(lex). Our comparative analysis revealed that sPSII(lex) is a better and more specific proxy for taxonomic analysis. For instance, our developed sPSII-based algorithm correctly identified 90% of experimental data, compared to 77% identified by the Fm-based algorithm. Our results suggest that the multi-color variable fluorescence analysis offers a tool for combined physiological and taxonomic analysis, including identification of major phyla within the ‘red’ lineage of eukaryotic phytoplankton.

Community dynamics and ecological shifts on Mediterranean vermetid reefs

Mediterranean coastal ecosystems experience many local and global stressors and require long-term monitoring to detect and follow trends in community structure. Between 2009 and 2017, we seasonally and annually monitored the spatiotemporal community dynamics at 11 sites on the rocky shores of the southeastern Mediterranean, focusing on the understudied intertidal vermetid reef ecosystem. Marked seasonal trends were found in biodiversity, with the highest diversity in winter and spring. Canopy-forming brown algae, dominating the northwestern Mediterranean intertidal reefs, were generally scarce on the reef platform and almost only found in tidepools. Interannual shifts in community structure were driven mostly by sharp fluctuations in a few dominant native and alien species and the regional mass mortality of an Indo-Pacific mussel in summer 2016. Compared to an older macroalgae dataset, dating back to 1973–1995, we found that some warm-affinity (summer) taxa became more dominant and cold-affinity (winter) species less dominant, while one once conspicuous species, Halimeda tuna, completely disappeared. The observed community shifts are probably driven mostly by stressors related to climate change. We encourage forming a network of long-term, multi-site ecological monitoring programs in the Mediterranean to improve our understanding of ecosystem change and to enable making better predictions at the basin scale.

Exploring variability in rangeland soil organic carbon stocks across California (USA) using a voluntary monitoring network

Rangelands are an economically and ecologically important land type that make up more than 40% of California's land area. Protecting and, where appropriate, increasing soil organic carbon (SOC) stocks across these rangelands can help to promote on-site and public ecosystem services including forage production and climate change mitigation. A necessary step toward appropriately and effectively stewarding SOC is understanding baseline variability in SOC stocks and identifying how that variability relates to factors such as climate, soil texture, and topography. While these relationships have been examined at broader spatial scales and in other contexts, analysis for California's rangelands remains lacking. We leveraged a voluntary ecological monitoring program consisting of 45 working ranches to explore how SOC varies with geographic distance, climate, vegetation, soil type, and topography within and across three regions of California. We found that there was large variability in soil C stocks across the state, with the Central Coast region storing more SOC than the San Joaquin and Sacramento Valleys. Network-wide, SOC stocks ranged from 4.83 to 63.54 Mg ha−1 for 0–10 cm depth and 12.15–205.37 Mg ha−1 for 0–40 cm depth. As hypothesized, climate was the strongest predictor of SOC stocks across the entire network, and in general other predictor groups became more important at the regional level. Within each region, we found on average a sixfold difference in SOC stocks, with much of the variation unexplained by the predictor variables included. While some differences in SOC likely result from unaccounted variables such as soil mineralogy, conceivably some of the variation is also due to differences in past and current land use—indicating that there is potential to rebuild SOC through management.

Earth and field observations underpin metapopulation dynamics in complex landscapes: Near-term study on carabids

Understanding risks to biodiversity requires predictions of the spatial distribution of species adapting to changing ecosystems and, to that end, Earth observations integrating field surveys prove essential as they provide key numbers for assessing landscape-wide biodiversity scenarios. Here, we develop, and apply to a relevant case study, a method suited to merge Earth/field observations with spatially explicit stochastic metapopulation models to study the near-term ecological dynamics of target species in complex terrains. Our framework incorporates the use of species distribution models for a reasoned estimation of the initial presence of the target species and accounts for imperfect and incomplete detection of the species presence in the study area. It also uses a metapopulation fitness function derived from Earth observation data subsuming the ecological niche of the target species. This framework is applied to contrast occupancy of two species of carabids (Pterostichus flavofemoratus, Carabus depressus) observed in the context of a large ecological monitoring program carried out within the Gran Paradiso National Park (GPNP, Italy). Results suggest that the proposed framework may indeed exploit the hallmarks of spatially explicit ecological approaches and of remote Earth observations. The model reproduces well the observed in situ data. Moreover, it projects in the near term the two species' presence both in space and in time, highlighting the features of the metapopulation dynamics of colonization and extinction, and their expected trends within verifiable timeframes.

Assessment of bioaccumulation of cu and Pb in experimentally exposed spiders, Lycosa terrestris and Pardosa birmanica, using different exposure routes.

Major concerns exist regarding the environmental and human health risks caused by exposure to heavy metals. Spiders are often used as a model in ecotoxicological studies to assess soil pollution. Here, we measured the bioaccumulation of copper (Cu) and lead (Pb) in spiders, Lycosa terrestris and Pardosa birmanica, by inductively coupled plasma mass spectrometry (ICP-MS). We investigated whether Cu and Pb accumulation differs according to different spider species, single versus combined metal exposure, and routes of exposure. Spiders were exposed to 10mM CuSO4 and 10mM PbCl2 solutions separately or in combination (10mM + 10mM) through different exposure routes (spiked soil and food) for 6weeks. The effect of metals on the survival and body mass of exposed and unexposed (control) spiders was determined. We found that in both spider species, accumulation of metals increased with exposure time. In single metal exposure, Cu accumulation from food was higher than soil exposure in both spider species, whereas the opposite was observed for Pb. The simultaneous uptake of Cu and Pb significantly decreased from food and soil, respectively. Soil exposure caused more accumulation of metals in L. terrestris than P. birmanica. Metal exposure via contaminated food caused higher mortality compared to soil exposure. Body mass of both spider species was significantly decreased and negatively correlated with metal's concentration. Overall, our results show that bioaccumulation efficiency of Cu and Pb differs significantly in spiders exposed to metal's mixture compared to single metal exposure and is dependent on the exposure route, the type of metal, and spider species. More understanding of the effects of exposure to metal mixture and exposure routes is essential for designing and supporting risk assessment and ecological monitoring programs.

Spatially balanced designs for transect‐based surveys

AbstractMany sampling techniques rely on taking measurements along a transect; an example is underwater imagery from towed platforms used for marine ecological studies. Despite transect‐based sampling being commonly used, methods to generate randomized survey designs have not hitherto been developed.We develop methods to generate random transect designs, which respect the user‐defined probability of sampling each grid cell (thecell inclusion probabilities). We show how to: (a) definetransect inclusion probabilitiesfrom user‐specified cell inclusion probabilities, which allows particular environments to be sampled more often; (b) alter the cell and transect inclusion probabilities so that when transects are sampled the frequencies of sampling cells approximate the cell inclusion probabilities, and; (c) draw a spatially balanced probability sample of transects.The spatially balanced transect designs approximately maintain the cell inclusion probabilities. The greatest of the small departures occur near the extreme corners of our convex study region, which are difficult to place transects into. The proposed designs also exhibit superior spatial balance compared to the non‐balanced counterparts. We illustrate the successful application of the method to a towed‐camera survey of deep‐sea (500–2,000 m depths) seamounts off Tasmania, Australia. This was a challenging application due to the complex topology of the setting, and uneven inclusion probabilities for the property of interest – the presence of a stony coral.Our approach develops the randomization approach to transect‐based surveys, thereby ensuring that transect‐based surveys can enjoy the same benefits as random point‐based surveys. The method approximates the cell inclusion probabilities, and does so while spatially balancing the transects throughout the study area. Practitioners can access the methods through theR‐packageMBHdesign, which is available from CRAN. We anticipate that it will act as a cornerstone for transect‐based ecological monitoring programmes.

Public perception and valuation of long‐term ecological monitoring

AbstractOrganizations tasked with implementing long‐term ecological monitoring programs often struggle to stay funded. Government agencies are typically the only entities with sufficient capacity and motivation to support long‐term scientific programs that generate data for environmental management and conservation. Taxpayers bear this funding burden, yet we know of no studies assessing public perception of government‐led long‐term monitoring. We present the results of a survey designed to assess willingness to pay (WTP) for the benefits resulting from long‐term ecological monitoring in Southeast Alaska for residents and visitors. We hypothesized that four factors have the potential to influence preferences for long‐term ecological monitoring: (1) type of ecosystem service monitored (intermediate vs. final); (2) place of residence; (3) prior knowledge of monitoring; and (4) sociodemographic characteristics. We defined final ecosystem services as ecosystem attributes that have clear relevance to human well‐being and intermediate ecosystem services as those required to produce final services. We found a greater WTP for programs monitoring intermediate ecosystem services, longer‐running programs, and programs covering a larger spatial extent. Respondents with higher income and conservative political preferences were more likely to choose no monitoring program at all (status quo), whereas respondents with previous knowledge of monitoring were generally more supportive of long‐term monitoring programs.

Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

AbstractBackgroundThousands of bulk arthropod samples are collected globally every year for monitoring programs, conservation efforts, and ecosystem assessments. The taxonomic contents of these samples can be assessed either morphologically or molecularly using DNA metabarcoding coupled with high‐throughput sequencing, the latter of which has gained popularity in recent years. In a related field, only vertebrateingesting invertebrates, such as carrion flies and blood‐feeding leeches, are targeted for collection, and metabarcoding is carried out on the vertebrate DNA in their gut contents to provide information on vertebrate diversity (invertebrate‐derived DNA, iDNA).AimsHere, we show that the two approaches can be combined, that is, that vertebrate DNA can be detected through metabarcoding of bulk arthropod samples. Materials and Methods: Two metabarcoding primer sets were used to PCR amplify mammal and vertebrate DNA in DNA extracted from bulk arthropod samples collected with pitfall and Malaise traps in tropical forests in Brazil and Tanzania.ResultsIn total, 32 vertebrate taxa were detected representing mammals, amphibians, and birds. Detected taxa were within, or close to, their known geographical distributions.ConclusionThis study demonstrates that with a relatively small additional investment, information on vertebrate diversity can be obtained from bulk arthropod samples. This is of particular interest in projects where bulk arthropod samples are collected and extracted with the aim to use metabarcoding to assess arthropod taxa. In such studies, the additional information on vertebrates can further inform ecological assessments and monitoring programs and function as a supplement to traditional survey methods of vertebrates.

Land use effect on butterfly alpha and beta diversity in the Eastern Himalaya, India

• Assessed butterfly diversity along agroecosystem-forest gradient of Eastern Himalaya. • 268 species were recorded well represented by specialists and protected butterflies. • Along the gradient, alpha diversity declined but pair-wise beta diversity increased. • Environmental variables strongly influenced butterfly alpha and beta diversity. • 15 indicator species identified for long term ecological monitoring in Eastern Himalaya. Conservation of biodiversity in agroecosystems is a global challenge as conversion of forest to agroecosystems has been one of the major causes for biodiversity loss through habitat transformation. The agroecosystems, especially those traditionally managed or organic, are reported to retain high biodiversity including endemic, specialists and conservation concern species. Among others, butterflies are the most vulnerable taxa reacting sensitively and rapidly to climate and habitat changes, and represent as bio-indicators to predict the health of an ecosystem. However, the assessment of land use effect on butterfly diversity has not yet been undertaken in the Eastern Himalayas. Therefore, this study was designed along agroecosystem-forest gradient to understand: the patterns of butterfly alpha diversity taking into account the variation across seasons, elevation, forest specialization and larval host specificity; the patterns of butterfly beta diversity; and plausible environmental determinants of butterfly alpha and beta diversity. We assessed the patterns of taxonomic alpha and beta diversity of butterflies and their determinants in the Indigenous Farming Systems (IFS) {large cardamom-based agroforestry systems (LCAS), mandarin orange-based agroforestry systems (MOAS) and farm-based agroforestry systems (FAS)} along with adjacent natural forests (Forests) in the study area during December 2012–August 2017. We recorded 268 species of butterflies from six families which included two-third forest specialists, one-third monophagous and one-fifth conservation concern species. Along the agroecosystem-forest gradient, alpha diversity of butterflies declined for total, forest specialists, monophagous and protected species. However, pair-wise beta diversity increased and the multiple beta diversity was dominated by substitution components. Alpha diversity was determined by tree species richness, tree density, canopy cover, elevation, mean annual precipitation (MAP), season, whereas tree species richness, tree density, tree basal area, canopy cover, elevation, mean annual temperature, and MAP influenced beta diversity. We also identified 15 indicator species dominated by forest specialists suitable for long term ecological monitoring program in the Eastern Himalaya. The organic and traditionally managed agroecosystems of Sikkim play a complementary role to the protected areas (PAs) in fostering biodiversity conservation and ecosystem service provision, especially in the areas with high human pressure and low PA and forest coverage.

Molecular characterization and phylogenetics of Indian polychaete fauna: scope for implementation in ecological monitoring

DNA barcodes are increasingly applied to ascertain the taxonomic identification to improve the speed and accuracy of ecological monitoring programmes. The success of integrating molecular approach in routine surveys ultimately depends on the coverage of reference libraries that require constant upgradation. The present molecular study was aimed at strengthening the genetic database of Polychaeta, which at present is poorly constructed. The current effort is first of its kind that covered a large geographical area along the northwest India. The study has contributed in building a comprehensive COI database of polychaete taxocene that included new records of one family, four genera and six species. The phylogenetic analysis revealed presence of 19 distinct clades, each comprising of individual family with studied polychaete species and conspecific/congeneric reference sequences. This is the first analysis that revealed a close relationship between Longosomatidae and Cirratulidae, rather than Spioniform polychaetes. Thus, the phylogenetic information was useful in distinguishing the polychaete species in the study region. Molecular analysis also facilitated the identification of potentially new Streblospio sp. that displayed close morphological as well as genetic affinity with S. gynobranchiata, with an inter-specific distance of 0.11. The present study proves the effectiveness of molecular characterization and phylogenetics in delineating the Indian polychaete species complex for ecological monitoring. The reference database can aid the high-throughput biomonitoring programmes in future.

Evaluation of Watershed Scale Aquatic Ecosystem Health by SWAT Modeling and Random Forest Technique

In this study, we evaluated the aquatic ecosystem health (AEH) with five grades (A; very good to E; very poor) of FAI (Fish Assessment Index), TDI (Trophic Diatom Index), and BMI (Benthic Macroinvertebrate Index) using the results of SWAT (Soil and Water Assessment Tool) stream water temperature (WT) and quality (T-N, T-P, NH4, NO3, and PO4). By applying Random Forest, one of the machine learning algorithms for classification analysis, each AEH index was trained and graded from the SWAT results. For Han river watershed (34,418 km2) in South Korea, the 8 years (2008~2015) observed AEH data of Spring and Fall periods at 86 locations from NAEMP (National Aquatic Ecological Monitoring Program) were used. The AEH was separately trained for Spring (FAIs, TDIs, and BMIs) and Fall (FAIa, TDIa, and BMIa), and the AEH results of Random Forest with SWAT (WT, T-N, T-P, NH4, NO3, and PO4) as input variables showed the accuracy of 0.42, 0.48, 0.62, 0.45, 0.4, and 0.58, respectively. The reason for low accuracy was from the weak strength of the individual trees and high correlation between the trees composing the Random Forest due to the data imbalance. The AEH distribution results showed that the number of Grade A of total FAI, TDI, and BMI were 84, 0, and 158 respectively and they were mostly located at the upstream watersheds. The number of Grade E of total FAI, TDI, and BMI were 4, 50, and 13 and they were shown at downstream watersheds.

Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams

Anthropogenic activities, such as land use and land cover modifications in riparian areas, can alter the degree of fragmentation of riparian vegetation, lead to the degradation of stream habitats, and affect biological communities in the streams. The characteristics of the riparian forests can modify the condition of stream environments and the transporting mechanisms of materials, sediments, nutrients, and pollutants loaded from the watersheds. This study aimed to examine the relationships between forest fragmentation and three biological indicators of trophic diatom, benthic macroinvertebrate, and the fish assessment in the Nakdong River, Korea. Eighty-nine biological assessment sampling sites in the National Aquatic Ecological Monitoring Program of South Korea were identified. For each sampling site, riparian forest data within a 500 m radius were extracted from national LULC using GIS to compute fragmentation metrics using FRAGSTATS software. Four fragmentation metrics—number of forest patches, percentage of riparian forest cover (PLAND), largest riparian forest patch index (LPI), and riparian forest division index (DIVISION)—were correlated with the biological indicators. Also, due to severe spatial autocorrelation among observations, the fragmentation metrics and stream environmental variables were regressed to biological indicators using regression tree analysis. Our results indicate that the biological indicators were significantly associated with most forest fragmentation metrics. We found positive correlations of PLAND and LPI with biological indicators, whereas DIVISION was negatively correlated with biological indicators. Both correlation and regression tree analyses revealed that the biological conditions of streams were likely to be better if riparian forests are less fragmented. Particularly, stronger relationships were revealed between macroinvertebrates and fish with the fragmentation metrics of riparian forests than with benthic diatoms. However, these relationships varied with elevation, stream size, and slope conditions. The results of this study reinforced the importance of including riparian forests in the planning, restoration, and management of stream environments. These results also suggested that planners and managers may need to consider different strategies for different stream environments and topographic characteristics in managing riparian forests.

Development and evaluation of NatureServe’s multi-metric ecological integrity assessment method for wetland ecosystems

Abstract Many ecological monitoring and assessment programs include rapid assessment methods that employ indicators or metrics to track the degree of divergence of ecosystem condition from reference conditions. Although these rapid assessment methods use a combination of metrics to rate overall ecological condition, they rarely include tests of either the merits of the component metrics being assessed or the method of aggregating the metrics into an overall rating. We used a conceptual model of ecological integrity for wetlands and field data to select and test 15 rapid assessment indicators (using specific metrics) across a spectrum of major ecological factors or MEFs (landscape, buffer, vegetation, hydrology, soil). We applied these metrics to 220 wetland sites across six states (Colorado, Indiana, Michigan, New Hampshire, New Jersey, and Washington), using two assessment area (AA) approaches: 106 sites used 0.5 ha point-based AAs; 114 sites used variable-sized polygon-based AAs. We statistically tested metric ratings and factor scores for their discriminatory power (DP) in relation to a stressor index using the Kruskal-Wallis test, and for redundancy using Spearman rank correlation and scattergrams. Of the 15 metrics, 12 had good or strong DP and were not redundant. Across all metrics, only two pairs (vegetation pair and buffer pair) were strongly correlated. The soil metric had the lowest DP, but it was among the least redundant of any metric. The DP of buffer metrics was lower for point-based approaches than for polygon-based approaches because the buffer for point-based AAs often included additional wetland area. Aggregating individual metrics into MEF scores (e.g., vegetation, hydrology, soil), primary factors scores (Landscape Context, on-site Condition) and overall ecological integrity ratings, either maintained or improved the interpretability of the ratings. Our analyses support the use of 12 rapid field-based metrics, spanning Landscape Context and on-site Condition, to assess the ecological integrity of wetlands. Although tested here for wetlands, the models and metrics are also being applied to upland terrestrial ecosystems. Our findings confirm the merits of our rapid assessment method in providing an intermediate level of assessment that is efficient and ecologically meaningful, within states and across watersheds and regions.

Sign, strength and shape of stream fish-based metric responses to geo-climatic and human pressure gradients

Abstract Efficient community indices and indicators are crucial for the adequate management and design of measures ensuring the ecosystem integrity. In this study we analyse the shape, sign and strength of the response of some biotic integrity indices and indicators of structure and function of fish communities along geo-climatic and human pressures gradients at catchment scale. To that purpose, >300 sites all over the Iberian Peninsula were characterized at the catchment scale by means of two anthropogenic drivers (agricultural and urban land proportion) and seven natural environmental descriptors covering geographical and climatic aspects. Regarding to fish-based metrics, a set of the most frequently used in stream health assessment studies have been selected, including taxonomic classic indicators, size related indicators and also recent multimetric indices created in the European context (WFD). We applied boosted regression trees that allow estimating the sign and strength of the response as well as considering non-linearity and impact thresholds. Our results show that the jointly contribution of anthropic drivers was lower than geo-climatic drivers. For most of indices and indicators, one single land cover contributed more markedly to the total deviance explained than the other, and they responded rather consistently to land-use variables, i.e., most of them responded negatively to the increase of anthropic use in the catchment. Size diversity, Fish Region Index (FRI) and maximum weight were those more sensible to agriculture land, while EFI+, mean weight, distinctness and FRI were those more sensitive to urban land. Regarding the shape of the response, urban land proportion affects normally at extremely low values, while agriculture land proportion induces smoother changes on a wider range. Our results may have practical implications, such as the selection of an efficient array of fish-based metrics to be included in ecological assessment and monitoring programs.

Patterning emergent marsh vegetation assemblages in coastal Louisiana,USA, with unsupervised artificial neural networks

AbstractQuestionsAre self‐organizing maps (SOMs) useful for patterning coastal wetland vegetation communities? DoSOMs provide robust alternatives to traditional classification methods, particularly when underlying species response functions are unknown or difficult to approximate, or when a need exists to continuously classify new samples obtained under ongoing long‐term ecosystem monitoring programs as they become available?LocationCoastal Louisiana,USA.MethodsASOMwas trained from in‐situ observations of 559 vegetation species relative cover data from 2,526 samples collected over 8 years at 343 locations across coastal Louisiana. Hierarchical cluster analysis was applied to theSOMoutput to delineate vegetation community types, and indicator species analysis was conducted. Salinity and flood duration were compared across the delineated community types.ResultsTheSOMpatterned the 2,526 training samples into 260 output neurons, which were further clustered into eleven community types. Clear gradients in salinity and flood duration existed among the community types, and geographic zonation of the communities was evident across the landscape. At some locations assemblages were temporally stable; at other locations, they varied considerably. Samples not used in training the network were effectively projected onto theSOMand assigned to one of the delineated community types.ConclusionsTheSOMwas effective in delineating plant communities in the region that were qualitatively similar to those obtained in previous investigations. Being robust to skewed distributions and the presence of outliers,SOMs provide an alternative to traditional distribution‐based statistical approaches. Their ability to efficiently classify new data into existing community types makes their use an ideal approach to classifying samples obtained from ongoing, long‐term ecological monitoring programs.

Eighteen years of ecological monitoring reveals multiple lines of evidence for tundra vegetation change

AbstractThe Arctic tundra is warming rapidly, yet the exact mechanisms linking warming and observed ecological changes are often unclear. Understanding mechanisms of change requires long‐term monitoring of multiple ecological parameters. Here, we present the findings of a collaboration between government scientists, local people, park rangers, and academic researchers that provide insights into changes in plant composition, phenology, and growth over 18 yr on Qikiqtaruk‐Herschel Island, Canada. Qikiqtaruk is an important focal research site located at the latitudinal tall shrub line in the western Arctic. This unique ecological monitoring program indicates the following findings: (1) nine days per decade advance of spring phenology, (2) a doubling of average plant canopy height per decade, but no directional change in shrub radial growth, and (3) a doubling of shrub and graminoid abundance and a decrease by one‐half in bare ground cover per decade. Ecological changes are concurrent with satellite‐observed greening and, when integrated, suggest that indirect warming from increased growing season length and active layer depths, rather than warming summer air temperatures alone, could be important drivers of the observed tundra vegetation change. Our results highlight the vital role that long‐term and multi‐parameter ecological monitoring plays in both the detection and attribution of global change.

An approach to identifying homogeneity in community functioning of periphytic ciliates in colonization surveys for marine bioassessment

Functional diversity/distinctness, as important biodiversity parameters of a community, have proved to be a feasible tool to summarize ecosystem functions and community structures both ecological research and monitoring program. For determining the homogeneity in community functioning of periphytic ciliates during colonization process, a 1-month baseline survey was conducted at four depths of 1, 2, 3.5 and 5 m in coastal waters of the Yellow Sea, northern China. The colonization dynamics in functional trait distribution of periphytic ciliates generally showed different temporal variations during colonization period at four depths. The functional diversity (Δχ), functional distinctness (Δ*χ), average functional distinctness (Δχ+) and variation in functional distinctness (Λχ+) indices generally represented different models within colonization process at four depths. Ellipse test on the paired functional distinctness measures (Δχ+ -Λχ+) revealed that the mature samples (14–28 days) were inside the expected patterns of community functioning at only one water depth (1 m), although the 14-day communities were fallen into the contours of 10 sub-list size at the other two water layers (2 and 3.5 m). These findings suggest that the functional distinctness measures might be a useful indicator to determine the optimal sampling strategy with high homogeneity of community functioning in colonization surveys for marine bioassessment.

Comparative analysis of heavy metal accumulation and bioindication in three seagrasses: Which species is more suitable as a bioindicator?

The present study aimed to assess the utilization of three seagrasses (Zostera marina, Z. japonica, and Z. caespitosa) along the eastern coast of the Shandong Peninsula as bioindicators of heavy metal pollution. Heavy metal concentrations (Cd, Cr, Cu, Pb and Zn) were investigated in the sediments and in the aboveground and belowground tissues of seagrasses. The results show that the aboveground tissues of seagrasses accumulated higher levels of Cd and Cu (excluding Z. caespitosa), whereas other metals, such as Cr, Pb and Zn, were mainly restricted to the belowground tissues. Compared to Z. japonica and Z. caespitosa, Z. marina had a higher enrichment capacity for heavy metals. Overall, the seagrasses can reflect the levels of metals in the sediments, especially Z. marina, whose heavy metal tissue levels were significantly and positively correlated with the levels of all metals in the sediments. This study showed that Z. marina could be used as an effective bioindicator for heavy metal pollution of sediments in ecological quality monitoring programs in the future, at least in the temperate waters of China.

ESA Historical Records Committee Newsletter January 2019

ESA Historical Records Committee Newsletter January 2019

Do Terrestrial Salamanders Indicate Ecosystem Changes in New England Forests?

Long-term ecological research (LTER) and monitoring programs accrue invaluable ecological data that inform policy and improve decisions that enable adaptation to and mitigation of environmental changes. There is great interest in identifying ecological indicators that can be monitored easily and effectively to yield reliable data about environmental changes in forested ecosystems. However, the selection, use, and validity of ecological indicators to monitor in LTER programs remain challenging tasks for ecologists and conservation biologists. Across the eastern United States of America, the foundation tree species eastern hemlock (Tsuga canadensis (L.) Carrière) is declining and dying from irruptions of a non-native insect, the hemlock woolly adelgid (Adelges tsugae Annand). We use data from the Harvard Forest LTER site’s Hemlock Removal Experiment together with information from other eastern US LTER sites to show that plethodontid salamanders can be reliable indicators of ongoing ecological changes in forested ecosystems in the eastern USA. These salamanders are abundant, they have a history of demographic stability, are both predators and prey, and can be sampled and monitored simply and cost-effectively. At the Harvard Forest LTER, red-backed salamanders (Plethodon cinereus Green) were strong indicators of intact forests dominated by eastern hemlock (Tsuga canadensis); their high site fidelity and habitat specificity yielded an indicator value (robust Dufrêne and Legendre’s “IndVal”) for this species of 0.99. Eastern red-spotted newts (Notopthalmus viridescens viridescens Rafinesque) were better indicators of nearby stands made up of young, mixed hardwood species, such as those which replace hemlock stands following adelgid infestation. At the Hubbard Brook and Coweeta LTER sites, plethodontid salamanders were associated with intact riparian habitats, which may also be dominated by eastern hemlock. We conclude that plethodontid salamanders satisfy most criteria for reliable ecological indicators of environmental changes in eastern US forests.