A new framework for selecting environmental surrogates

Assessment of emerging and persistent contaminants in an anthropogenic-impacted watershed: Application using targeted, non-targeted, and in vitro bioassay techniques

Emerging and persistent contaminants (EPC) pose a significant challenge to water quality monitoring efforts. Effect-based monitoring (EBM) techniques provide an efficient and systematic approach in water quality monitoring, but they tend to be resource intensive. In this study, we investigated the EPC distribution for various land uses using target analysis (TA) and non-target screening (NTS) and in vitro bioassays, both individually and integrated, in the upper Ping River Catchment, northern Thailand. Our findings of NTS showed that urban areas were the most contaminated of all land use types, although agriculture sites had high unexpected pollution levels. We evaluated the reliability of NTS data by comparing it to TA and observed varying inconsistencies likely due to matrix interferences and isobaric compound interferences. Integrating NTS with in vitro bioassays for a thorough analysis posed challenges, primary due to a scarcity of concentration data for key compounds, and potentially additive or non-additive effects of mixture samples that could not be accounted for. While EBM approaches place emphasis on toxic sites, this study demonstrated the importance of considering non-bioactive sites that contain toxic compounds with antagonistic effects that may go undetected by traditional monitoring approaches. The present work emphasizes the importance of improving NTS workflows and ensuring high-quality EBM analyses in future water quality monitoring programs.

Construction, evaluation, and AOP framework-based application of the EpPRS as a genetic surrogate for assessing environmental pollutants

BACKGROUND

Environmental pollutant measurement is essential for accurate health risk assessment. However, the detection of humans' internal exposure to pollutants is cost-intensive and consumes time and energy. Polygenic risk scores (PRSs) have been widely applied in genetic studies of complex trait diseases. It is important to construct a genetically relevant environmental surrogate for pollutant exposure and to explore its utility for disease prediction and risk assessment.

OBJECTIVES

This study enrolled 714 individuals with complete genomic data and exposomic data on 22 plasma-persistent organic pollutants (POPs).

METHODS

We first conducted 22 POP genome-wide association studies (GWAS) and constructed the corresponding environmental pollutant-based PRS (EpPRS) by clumping and P value thresholding (C + T), lassosum, and PRS-CS methods. The best-fit EpPRS was chosen by its regression R2. An adverse outcome pathway (AOP) framework was developed to assess the effects of contaminants on candidate diseases. Furthermore, Mendelian randomization (MR) analysis was performed to explore the causal association between POPs and cancer risk.

RESULTS

The C + T method produced the best-performing EpPRSs for 7 PCBs and 4 PBDEs. EpPRSs replicated the correlations of environmental exposure measurements based on consistent patterns. The diagnostic performance of type 2 diabetes mellitus (T2DM) PRS was improved by the combined model of T2DM-EpPRS of PCB126/BDE153. Finally, the AKT1-mediated AOP framework illustrated that PCB126 and BDE153 may increase the risk of T2DM by decreasing AKT1 phosphorylation through the cGMP-PKG pathway and promoting abnormal glucose homeostasis. MR analysis showed that digestive system tumors, such as colorectal cancer and biliary tract cancer, are more sensitive to POP exposure.

CONCLUSIONS

EpPRSs can serve as a proxy for assessing pollutant internal exposure. The application of the EpPRS to disease risk assessment can reveal the toxic pathway and mode of action linking exposure and disease in detail, providing a basis for the development of environmental pollutant control strategies.

How Do Taxonomic and Functional Diversity Metrics Change Along an Aridity Gradient in a Tropical Dry Forest?

Ecological indicators based on biodiversity metrics are valuable and cost-effective tools to quantify, track and understand the effects of climate change on ecosystems. Studying changes in these indicators along climatic gradients in space is a common approach to infer about potential impacts of climate change over time, overcoming the limitations of lack of sufficiently long time-series data. Here, we studied the response of complementary biodiversity metrics in plants: taxonomic diversity (species richness and Simpson index) and functional diversity (diversity and redundancy) in 113 sampling sites along a spatial aridity gradient (from 0.27 to 0.69 of aridity index-AI) of 700 km in a Tropical dry forest. We found different responses of taxonomic and functional diversity metrics to aridity. Species diversity showed a hump-shaped curve peaking at intermediate levels of aridity between 0.38 and 0.52 AI as an ecotone, probably because it is where most species, from both drier and more mesic environments, still find conditions to co-exist. Functional diversity showed a positive linear relation with increasing aridity, suggesting higher aridity favors drought-adapted species with diverse functional traits. In contrast, redundancy showed a negative linear relation with increasing aridity, indicating that drier sites have few species sharing the same functional traits and resource acquisition strategies. Thus, despite the increase in functional diversity toward drier sites, these communities are less resilient since they are composed of a small number of plant species with unique functions, increasing the chances that the loss of one of such "key species" could lead to the loss of key ecosystem functions. These findings show that the integration of complementary taxonomic and functional diversity metrics, beyond the individual response of each one, is essential for reliably tracking the impacts of climate change on ecosystems. This work also provides support to the use of these biodiversity metrics as ecological indicators of the potential impact of climate change on drylands over time.

Internal phosphorus loading and its driving factors in the dry period of Brazilian semiarid reservoirs

This study investigated the relationships between physical, limnological and climatic drivers with the internal total phosphorus (TP) loading produced over the dry period in 30 water supply reservoirs of the Brazilian semiarid. Improvements in the understanding of sedimentary TP fluxes in reservoirs of dryland regions are pressing as they usually have serious water quality related issues, remaining mostly eutrophic especially under frequent drought events. Gross daily fluxes and net seasonal average release rates were calculated from mass balance and regression equations considering water and sediment TP concentrations, anoxic duration, water temperature and fish contribution. Additionally, the ratio of wind speed to reservoir volume was proposed as a new surrogate and then applied as explanatory variable to predictive models. The results indicated TP release rates higher than reported for non-semiarid lakes/reservoirs with average gross fluxes ranging from 17.64 to 35.99 mg m^-2 day^-1. This may be attributed to the enriched sediments (1029.49 ± 552.49 mg kg^-1) allied with warmer water temperature, high trophic state, and prolonged anoxic periods (average duration of about 60 days). The average release rates were negatively correlated with water transparency and water depth, and positively correlated with Chl-a, wind speed and trophic state. The release rates increased across the trophic gradient (p < 0.05), about 10-fold higher under hypertrophic conditions than in oligotrophic ones. As anoxia is linked with eutrophication, phosphorus release is more likely in eutrophic ecosystems. Regarding the new surrogate, a strong predictive ability for TP release (R²: 0.26-0.93) was observed. Similarly, the proposed models presented a physically consistent behavior with a stabilizing releasing pattern suggesting the achievement of equilibrium in nutrient exchange between sediment-water interface. This research advanced by combining and proposing methods to assess and quantify sedimentary fluxes in data-scarce regions balancing accuracy and transferability, in order to be replicable to other dryland environments globally.

Detection Rate of Bird Species and What It Depends on: Tips for Field Surveys

Bird counting inevitably suffers from imperfect detection, which varies across species, habitats, period of the day, and seasons. Although various modeling techniques have recently been developed to account for this phenomenon, the biological basis of natural variation in detection remains insufficiently known. This study examined the bird species’ detection rate throughout the day, considering their body mass and diet type, concerning the environment and weather characteristics. Species detection rates were significantly affected by the number of individuals of that species but were unrelated to body mass. Overall, species with the highest detection rate were Corn bunting, Blackbird, European robin, House sparrow and Common chiffchaff. Granivores-insectivores and insectivores showed significant differences in detection rates throughout the day among habitats, with higher detection rates in grasslands during the afternoon. Insectivores showed higher detection rates in farmland during midday (warmest time of the day). Granivores, omnivores and scavengers did not show changes in detection rates in different day periods. Such patterns in daily detection rates were significant even when considering abundance and total species richness in each community. Finally, cloudiness was unrelated to the overall detection rate of birds, while temperature and wind affected detection rates in some guilds. Our findings provide some advice for choosing a suitable ornithological sampling method by considering the avian communities composition in combination with the type of environment, the diet of bird species, and the period of the day.

A new evaluation framework for nature-based solutions (NBS) projects based on the application of performance questions and indicators approach

One of the key features of nature-based solutions (NBSs) is their high effectiveness and economic and resource efficiency in solving problems compared to traditional grey interventions. These aspects, however, have so far attracted little attention in the literature but should be considered, as the evaluation of NBS projects before implementation provides an opportunity to use them as practical tools. This paper aims to present a new evaluation framework of NBS projects (at the stage of solution selection) based on the application of performance questions and the indicators approach. The framework consists of three main stages: (1) the formulation of the project aim(s), including the problem(s) to be solved, the scales of the expected effects and the thresholds to be achieved; (2) the elimination of solutions that do not fit the local conditions and setting requirements; and (3) the examination of the performance questions. To consider the whole spectrum of influencing factors, a systematic review was performed to indicate the main concepts related to the issue of NBS effectiveness, including (1) stakeholders' participation, (2) policy and management capability, (3) economic efficiency, (4) analysis of synergies and trade-offs, (5) adaptation to local conditions, (6) adequate spatial scale and (7) performance in the long term. In the current study around 130 indicators were identified for the evaluation of NBS projects. Regarding the impact on the state of knowledge, the present work contributes to the discussion on the conceptual sphere of NBS and its practical implementation by introducing multi-perspective standards and guidelines for the selection of possible NBS projects, and it deals with the complexity of synergies and the trade-offs between benefits.

Habitat Models of Focal Species Can Link Ecology and Decision-Making in Sustainable Forest Management

A fundamental problem of sustainability is how to reduce the double complexity of ecological and social systems into simple operational terms. We highlight that the conservation concept of focal species (selected species sensitive to a set of anthropogenic threats to their habitat) links multiple issues of ecological sustainability, and their habitat models can provide a practical tool for solving these issues. A review of the literature shows that most spatial modeling of focal species focuses on vertebrates, lacks the aspect of aquatic and soil habitats, and has been slow in the uptake by actual management planning. We elaborate on a deductive modeling approach that first generalizes the main influential dimensions of habitat change (threats), which are then parameterized as habitat quality estimates for focal species. If built on theoretical understanding and properly scaled, the maps produced with such models can cost-effectively describe the dynamics of ecological qualities across forest landscapes, help set conservation priorities, and reflect on management plans and practices. The models also serve as ecological hypotheses on biodiversity and landscape function. We illustrate this approach based on recent additions to the forest reserve network in Estonia, which addressed the insufficient protection of productive forest types. For this purpose, mostly former production forests that may require restoration were set aside. We distinguished seven major habitat dimensions and their representative taxa in these forests and depicted each dimension as a practical stand-scale decision tree of habitat quality. The model outcomes implied that popular stand-structural targets of active forest restoration would recover passively in reasonable time in these areas, while a critically degraded condition (loss of old trees of characteristic species) required management beyond reserve borders. Another hidden issue revealed was that only a few stands of consistently low habitat quality concentrated in the landscape to allow cost-efficient restoration planning. We conclude that useful habitat models for sustainable forest management have to balance single-species realism with stakeholder expectations of meaningful targets and scales. Addressing such social aspects through the focal species concept could accelerate the adoption of biodiversity distribution modeling in forestry.

The Methodology of Landscape Quality (LQ) Indicators Analysis Based on Remote Sensing Data: Polish National Parks Case Study

Landscape quality (LQ) encompasses diverse characteristic of the natural and cultural environment. The most effective tool to analyze LQ is the use of indicators. The main problem in the assessment of LQ is not the lack of indicators, but its multitude. That is why, the indicators’ categorization is a problematic issue. The paper aims to introduce and test the methodology for selecting the suitable indicators based on the example of two national parks located in the south-east part of Poland. The method composed of the following stages: (1) Selection of spatial units being analyzed; (2) selection of indicators type(s); (3) selection of specific indicators; (4) calculation of indicator set no 1; (5) analysis of the correlation between indicators’ pairs; (6) selection of a final set of indicators; (7) analysis of effectiveness. The latter stage, refers to the statistical analysis of significance between results obtained dependently on the data sources, a spatial unit of analysis and analyzed regions. The results showed that the categorization composed of ten, mainly composite indicators, can be applied to conclude on different levels of LQ of protected areas. The differences between two analyzed data sources, different spatial units, as well as diverse regions, occurred to be statistically insignificant. Generally, the results of the effectiveness analysis showed that a final categorization of LQ indicators is adequate to conclude on the diverse dimensions of LQ of analyzed protected areas.

Demystifying dominant species

The pattern of a few abundant species and many rarer species is a defining characteristic of communities worldwide. These abundant species are often referred to as dominant species. Yet, despite their importance, the term dominant species is poorly defined and often used to convey different information by different authors. Based on a review of historical and contemporary definitions we develop a synthetic definition of dominant species. This definition incorporates the relative local abundance of a species, its ubiquity across the landscape, and its impact on community and ecosystem properties. A meta-analysis of removal studies shows that the loss of species identified as dominant by authors can significantly impact ecosystem functioning and community structure. We recommend two metrics that can be used jointly to identify dominant species in a given community and provide a roadmap for future avenues of research on dominant species. In our review, we make the case that the identity and effects of dominant species on their environments are key to linking patterns of diversity to ecosystem function, including predicting impacts of species loss and other aspects of global change on ecosystems.

Quantifying Ecological Integrity of Terrestrial Systems to Inform Management of Multiple-Use Public Lands in the United States

The concept of ecological integrity has been applied widely to management of aquatic systems, but still is considered by many to be too vague and difficult to quantify to be useful for managing terrestrial systems, particularly across broad areas. Extensive public lands in the western United States are managed for diverse uses such as timber harvest, livestock grazing, energy development, and wildlife conservation, some of which may degrade ecological integrity. We propose a method for assessing ecological integrity on multiple-use lands that identifies the components of integrity and levels in the ecological hierarchy where the assessment will focus, and considers existing policies and management objectives. Both natural reference and societally desired environmental conditions are relevant comparison points. We applied the method to evaluate the ecological integrity of shrublands in Nevada, yielding an assessment based on six indicators of ecosystem structure, function, and composition, including resource- and stressor-based indicators measured at multiple scales. Results varied spatially and among indicators. Invasive plant cover and surface development were highest in shrublands in northwest and southeast Nevada. Departure from reference conditions of shrubland area, composition, patch size, and connectivity was highest in central and northern Nevada. Results may inform efforts to control invasive species and restore shrublands on federal lands in Nevada. We suggest that ecological integrity assessments for multiple-use lands be grounded in existing policies and monitoring programs, incorporate resource- and stressor-based metrics, rely on publicly available data collected at multiple spatial scales, and quantify both natural reference and societally desired resource conditions.

Which Species Should We Focus On? Umbrella Species Assessment in Southwest China

In conservation biology, umbrella species are often used as agents for a broader set of species, or as representatives of an ecosystem, and their conservation is expected to benefit a large number of naturally co-occurring species. Southwest China is home to not only global biodiversity hotspots, but also rapid economic and population growth and extensive changes in land use. However, because of the large regional span, the diverse species distributions, and the difficulty of field investigations, traditional methods used to assess umbrella species are not suitable for implementation in Southwest China. In the current study, we assessed 810 key protected species from seven taxa by indicator value analysis, correlation analysis, and factor analysis. We selected 32 species as umbrella species, whose habitats overlapped the habitats of 97% of the total species. Furthermore, the selected species were significantly correlated with 70% of all species in the study area. A total of 16 out of 19 selected animal species have been previously mentioned as umbrella species, compared with only 3 out of 13 plants species; this is despite plants accounting for a large proportion of the total species in Southwest China. We discuss the roles of indicator species and co-occurring species, and provide suggestions for species protection in Southwest China based on the current results. Our research provides valuable scientific information for research on umbrella conservation species over large geographical scales, and related fields of biodiversity conservation.

Invasive shrub re-establishment following management has contrasting effects on biodiversity

Effective control of an invasive species is frequently used to infer positive outcomes for the broader ecosystem. In many situations, whether the removal of an invasive plant is of net benefit to biodiversity is poorly assessed. We undertook a 10-year study on the effects of invasive shrub management (bitou bush, Chrysanthemoides monilifera ssp. rotundata) on native flora and fauna in a eucalypt forest in south-eastern Australia. Bitou bush eradication is a management priority, yet the optimal control regime (combination of herbicide spray and fire) is difficult to implement, meaning managed sites have complex management histories that vary in effectiveness of control. Here we test the long-term response of common biodiversity indicators (species richness, abundance and diversity of native plants, birds, herpetofauna and small mammals) to both the management, and the post-management status of bitou bush (% cover). While average bitou bush cover decreased with management, bitou bush consistently occurred at around half of our managed sites despite control efforts. The relationship between biodiversity and bitou bush cover following management differed from positive, neutral or negative among species groups and indicators. Native plant cover was lower under higher levels of bitou bush cover, but the abundance of birds and small mammals were positively related to bitou bush cover. Evidence suggests that the successful control of an invader may not necessarily result in beneficial outcomes for all components of biodiversity.

How practitioners integrate decision triggers with existing metrics in conservation monitoring

Decision triggers are defined thresholds in the status of monitored variables that indicate when to undertake management, and avoid undesirable ecosystem change. Decision triggers are frequently recommended to conservation practitioners as a tool to facilitate evidence-based management practices, but there has been limited attention paid to how practitioners are integrating decision triggers into existing monitoring programs. We sought to understand whether conservation practitioners' use of decision triggers was influenced by the type of variables in their monitoring programs. We investigated this question using a practitioner-focused workshop involving a structured discussion and review of eight monitoring programs. Among our case studies, direct measures of biodiversity (e.g. native species) were more commonly monitored, but less likely to be linked to decision triggers (10% with triggers) than measures being used as surrogates (54% with triggers) for program objectives. This was because decision triggers were associated with management of threatening processes, which were often monitored as a surrogate for a biodiversity asset of interest. By contrast, direct measures of biodiversity were more commonly associated with informal decision processes that led to activities such as management reviews or external consultation. Workshop participants were in favor of including more formalized decision triggers in their programs, but were limited by incomplete ecological knowledge, lack of appropriately skilled staff, funding constraints, and/or uncertainty regarding intervention effectiveness. We recommend that practitioners consider including decision triggers for discussion activities (such as external consultation) in their programs as more than just early warning points for future interventions, particularly for direct measures. Decision triggers for discussions should be recognized as a critical feature of monitoring programs where information and operational limitations inhibit the use of decision triggers for interventions.

Green spaces are not all the same for the provision of air purification and climate regulation services: The case of urban parks

The growing human population concentrated in urban areas lead to the increase of road traffic and artificial areas, consequently enhancing air pollution and urban heat island effects, among others. These environmental changes affect citizen's health, causing a high number of premature deaths, with considerable social and economic costs. Nature-based solutions are essential to ameliorate those impacts in urban areas. While the mere presence of urban green spaces is pointed as an overarching solution, the relative importance of specific vegetation structure, composition and management to improve the ecosystem services of air purification and climate regulation are overlooked. This avoids the establishment of optimized planning and management procedures for urban green spaces with high spatial resolution and detail. Our aim was to understand the relative contribution of vegetation structure, composition and management for the provision of ecosystem services of air purification and climate regulation in urban green spaces, in particular the case of urban parks. This work was done in a large urban park with different types of vegetation surrounded by urban areas. As indicators of microclimatic effects and of air pollution levels we selected different metrics: lichen diversity and pollutants accumulation in lichens. Among lichen diversity, functional traits related to nutrient and water requirements were used as surrogates of the capacity of vegetation to filter air pollution and to regulate climate, and provide air purification and climate regulation ecosystem services, respectively. This was also obtained with very high spatial resolution which allows detailed spatial planning for optimization of ecosystem services. We found that vegetation type characterized by a more complex structure (trees, shrubs and herbaceous layers) and by the absence of management (pruning, irrigation and fertilization) had a higher capacity to provide the ecosystems services of air purification and climate regulation. By contrast, lawns, which have a less complex structure and are highly managed, were associated to a lower capacity to provide these services. Tree plantations showed an intermediate effect between the other two types of vegetation. Thus, vegetation structure, composition and management are important to optimize green spaces capacity to purify air and regulate climate. Taking this into account green spaces can be managed at high spatial resolutions to optimize these ecosystem services in urban areas and contribute to improve human well-being.

The common cuckoo is an effective indicator of high bird species richness in Asia and Europe

Common cuckoo Cuculus canorus is a charismatic bird species with a dominant presence in human culture: from folklore legends to nowadays there is evidence of cuckoos being a prime candidate as a surrogate of bird diversity. Recent studies demonstrated that the cuckoo can predict hotspots of taxonomic diversity and functional diversity of bird communities in European countries. In this study, we demonstrated that the cuckoo is an excellent bioindicator at multi-spatial scale, extending cuckoo surrogacy from Europe to Asia. Even using three different survey methods (transect, square, point counts), comparing the new findings with results of our research in Europe, sites where the cuckoo is present were characterized by greater species richness, while the cuckoo was absent from sites with low species richness. The goodness of fit of models based on point counts ranged between 71 and 92%. Furthermore, the cuckoo population trend mirrors the average population trend and climate suitability of overall bird communities in Europe. The common cuckoo is therefore a suitable intercontinental bioindicator of hotspots of bird richness, even under climate change scenarios or in areas where the species co-occurs with other cuckoo species, opening a new avenue for standardized citizen science on bird biodiversity surveys worldwide.

Models of Eucalypt phenology predict bat population flux

Fruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt-focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86-93% accuracy. Negative binomial models explained 43-53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt-based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar-based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology and disease dynamics. This work provides a foundation for further studies on landscape-scale population movement and spatiotemporal disease dynamics.