Characterizing driver-response relationships in marine pelagic ecosystems for improved ocean management

Dose-response curves: the next frontier in plant ecology

A large fraction of experimental work in plant ecology, and thus also on ecosystem functioning and the delivery of ecosystem services, describes experiments that have been carried out under controlled (glasshouse) conditions. Controlled growth settings commonly sacrifice realism through, for example, reducing the densities of plant species in the pots and controlling how environmental settings such as moisture and light vary in favor of a higher mechanistic resolution, which makes these studies particularly suitable for subsequent syntheses. We explore the possibility that further integration of dose-response curves can maximize the impact of existing studies. We suggest that we can expand considerably the scope of the dose and response variables that are considered in plant ecology.

Inclusive Fitness May Explain Some but Not All Benefits Derived from Helping Behavior in a Cooperatively Breeding Bird

AbstractIn cooperative breeding systems, inclusive fitness theory predicts that nonbreeding helpers more closely related to the breeders should be more willing to provide costly alloparental care and thus have more impact on breeder fitness. In the red-cockaded woodpecker (Dryobates borealis), most helpers are the breeders' earlier offspring, but helpers do vary within groups in both relatedness to the breeders (some even being unrelated) and sex, and it can be difficult to parse their separate impacts on breeder fitness. Moreover, most support for inclusive fitness theory has been positive associations between relatedness and behavior rather than actual fitness consequences. We used functional linear models to evaluate the per capita effects of helpers of different relatedness on eight breeder fitness components measured for up to 41 years at three sites. In support of inclusive fitness theory, helpers more related to the breeding pair made greater contributions to six fitness components. However, male helpers made equal contributions to increasing prefledging survival regardless of relatedness. These findings suggest that both inclusive fitness benefits and other direct benefits may underlie helping behaviors in the red-cockaded woodpecker. Our results also demonstrate the application of an underused statistical approach to disentangle a complex ecological phenomenon.

Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Chronic exposure to inorganic arsenic (As) and uranium (U) in the United States (US) occurs from unregulated private wells and federally regulated community water systems (CWSs). The contribution of water to total exposure is assumed to be low when water As and U concentrations are low.

OBJECTIVE

We examined the contribution of water As and U to urinary biomarkers in the Strong Heart Family Study (SHFS), a prospective study of American Indian communities, and the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of racially/ethnically diverse urban U.S. communities.

METHODS

We assigned residential zip code-level estimates in CWSs (µg/L) and private wells (90th percentile probability of As >10 µg/L) to up to 1485 and 6722 participants with dietary information and urinary biomarkers in the SHFS (2001-2003) and MESA (2000-2002; 2010-2011), respectively. Urine As was estimated as the sum of inorganic and methylated species, and urine U was total uranium. We used linear mixed-effects models to account for participant clustering and removed the effect of dietary sources via regression adjustment.

RESULTS

The median (interquartile range) urine As was 5.32 (3.29, 8.53) and 6.32 (3.34, 12.48) µg/L for SHFS and MESA, respectively, and urine U was 0.037 (0.014, 0.071) and 0.007 (0.003, 0.018) µg/L. In a meta-analysis across both studies, urine As was 11% (95% CI: 3, 20%) higher and urine U was 35% (5, 73%) higher per twofold higher CWS As and U, respectively. In the SHFS, zip-code level factors such as private well and CWS As contributed 46% of variation in urine As, while in MESA, zip-code level factors, e.g., CWS As and U, contribute 30 and 49% of variation in urine As and U, respectively.

IMPACT STATEMENT

We found that water from unregulated private wells and regulated CWSs is a major contributor to urinary As and U (an estimated measure of internal dose) in both rural, American Indian populations and urban, racially/ethnically diverse populations nationwide, even at levels below the current regulatory standard. Our findings indicate that additional drinking water interventions, regulations, and policies can have a major impact on reducing total exposures to As and U, which are linked to adverse health effects even at low levels.

An Examination of the Non-linear Relationship Between Cognition and Total Hemoglobin Among the Cognitively Normal Older Adults by Gender

Objectives: This exploratory study aimed to identify the potential non-linear relationship between hemoglobin (Hgb) and cognition among cognitively normal older adults and how this relationship differs in terms of gender in generalized additive models (GAM). Methods: This is a secondary data analysis using Wave II (2010-2011) data from the National Social Life, Health, and Aging Project. A generalized additive model was used to understand the non-linear relationship between Hgb and cognition, and to identify critical Hgb point related to cognition. Results: While both genders had a non-linear association between Hgb and cognition, the degree of non-linearity was more pronounced in male older adults with EDF value close to 2. The inflection point of 15.10 g/dL for male older adults and inflection point of 11.72 g/dL for female older adults were obtained. Conclusion: Further studies are needed to validate these results and develop precision medicine approaches to integrate these results into clinical practice.

Longitudinal Associations between Prenatal Exposure to Phthalates and Steroid Hormones in Maternal Hair Samples from the SEPAGES Cohort

We assessed phthalate-hormone associations in 382 pregnant women of the new-generation SEPAGES cohort (2014-2017, France) using improved exposure and outcome assessments. Metabolites from seven phthalate compounds and the replacement di(isononyl)cyclohexane-1,2-dicarboxylate (DINCH) were measured in within-subject pools of repeated urine samples collected at the second and third pregnancy trimesters (≈21 samples/trimester). Metabolites from five steroid hormones were measured in maternal hair samples collected at delivery, reflecting cumulative levels over the previous weeks to months. Adjusted linear regression and Bayesian weighted quantile sum (BWQS) mixture models were performed. Each doubling in third-trimester urinary mono-benzyl phthalate (MBzP) concentrations was associated with an average increase of 13.3% (95% CI: 2.65, 24.9) for ∑cortisol, 10.0% (95% CI: 0.26, 20.7) for ∑cortisone, 17.3% (95% CI: 1.67, 35.4) for 11-dehydrocorticosterone, and 16.2% (95% CI: 2.20, 32.1) for testosterone, together with a suggestive 10.5% (95% CI: -1.57, 24.1) increase in progesterone levels. Each doubling in second-trimester urinary di-isononyl phthalate (DiNP) concentrations was inversely associated with testosterone levels (-11.6%; 95% CI: -21.6, -0.31). For most hormones, a nonsignificant trend toward a positive phthalate mixture effect was observed in the third but not in the second trimester. Our study showed that exposure to some phthalate metabolites, especially MBzP, may affect adrenal and reproductive hormone levels during pregnancy.

Prenatal Exposure to Perfluoroalkyl Substances and Child Behavior at Age 12: A PELAGIE Mother-Child Cohort Study

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are chemical substances spread throughout the environment worldwide. Exposure during pregnancy represents a specific window of vulnerability for child health.

OBJECTIVE

Our objective was to assess the impact of prenatal exposure to multiple PFAS on emotional and behavioral functions in 12-y-old children.

METHOD

In the PELAGIE mother-child cohort (France), prenatal exposure to nine PFAS was measured from concentrations in cord serum samples. Behavior was assessed at age 12 y using the parent-reported Strengths and Difficulties Questionnaire (SDQ) and the self-reported Dominic Interactive for Adolescents (DIA) for 444 children. Associations were estimated using negative binomial models for each PFAS. Bayesian kernel machine regression (BKMR) models were performed to assess the exposure mixture effect on children's behavior.

RESULTS

In our study population, 73% of mothers had spent more than 12 y in education. Higher scores on SDQ externalizing subscale were observed with increasing cord-serum concentration of perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA) [adjusted mean ratio ( aMR ) = 1.18 , 95% confidence interval (CI): 1.03, 1.34, and aMR = 1.14 (95% CI: 1.00, 1.29) for every doubling of concentration, respectively]. Results for the hyperactivity score were similar [aMR = 1.20 (95% CI: 1.04, 1.40) and aMR = 1.18 (95% CI: 1.02, 1.36), respectively]. With regard to major depressive disorder and internalizing subscales, perfluorodecanoic acid (PFDA) was associated with higher self-reported DIA scores [aMR = 1.14 (95% CI: 1.01, 1.27) and aMR = 1.11 (95% CI: 1.02, 1.21), respectively]. In terms of the anxiety subscale, PFDA and PFNA were associated with higher scores [aMR = 1.11 (95% CI: 1.02, 1.21) and aMR = 1.10 (95% CI: 1.01, 1.19), respectively]. Concurrent increases in the PFAS concentrations included in the BKMR models showed no change in the SDQ externalizing and DIA internalizing subscales scores.

CONCLUSION

Prenatal exposure to PFNA and PFOA were associated with increasing scores for measures of externalizing behaviors, specifically hyperactivity. We also identified associations between PFNA and PFDA prenatal exposure levels and increasing scores related to internalizing behaviors (general anxiety and major depressive disorder), which adds to the as yet sparse literature examining the links between prenatal exposure to PFAS and internalizing disorders. https://doi.org/10.1289/EHP12540.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Exploring multiple stressor effects with Ecopath, Ecosim, and Ecospace: Research designs, modeling techniques, and future directions

Understanding the cumulative effects of multiple stressors is a research priority in environmental science. Ecological models are a key component of tackling this challenge because they can simulate interactions between the components of an ecosystem. Here, we ask, how has the popular modeling platform Ecopath with Ecosim (EwE) been used to model human impacts related to climate change, land and sea use, pollution, and invasive species? We conducted a literature review encompassing 166 studies covering stressors other than fishing mostly in aquatic ecosystems. The most modeled stressors were physical climate change (60 studies), species introductions (22), habitat loss (21), and eutrophication (20), using a range of modeling techniques. Despite this comprehensive coverage, we identified four gaps that must be filled to harness the potential of EwE for studying multiple stressor effects. First, only 12% of studies investigated three or more stressors, with most studies focusing on single stressors. Furthermore, many studies modeled only one of many pathways through which each stressor is known to affect ecosystems. Second, various methods have been applied to define environmental response functions representing the effects of single stressors on species groups. These functions can have a large effect on the simulated ecological changes, but best practices for deriving them are yet to emerge. Third, human dimensions of environmental change - except for fisheries - were rarely considered. Fourth, only 3% of studies used statistical research designs that allow attribution of simulated ecosystem changes to stressors' direct effects and interactions, such as factorial (computational) experiments. None made full use of the statistical possibilities that arise when simulations can be repeated many times with controlled changes to the inputs. We argue that all four gaps are feasibly filled by integrating ecological modeling with advances in other subfields of environmental science and in computational statistics.

Serum cystatin C and mild cognitive impairment: The mediating role of glucose homeostasis

Background

This study explored the mediating role of glucose homeostasis indicators in the relationship between serum cystatin C and mild cognitive impairment (MCI).

Methods

The present study used a cross-sectional design and included 514 participants aged ≥50 years in Beijing, China. The Mini-Mental State Examination was used to assess cognitive function. Serum cystatin C and a comprehensive set of glucose homeostasis indicators were detected, including fasting blood glucose (FBG), glycosylated albumin percentage (GAP), glycated hemoglobin (HbAlc), insulin, and homeostatic model assessment of insulin resistance (HOMA-IR), and beta cell function (HOMA-β). Generalized linear models were used to investigate the associations among cystatin C, glucose homeostasis indicators, and cognitive function. Mediation analysis was conducted to explore potential mediator variables.

Results

In this study of 514 participants, 76 (14.8%) had MCI. Those with cystatin C levels ≥1.09 mg/L had a 1.98-fold higher risk of MCI than those with levels <1.09 mg/L (95% CI, 1.05–3.69). FBG, GAP, and HbA1c increased the risk of MCI, while HOMA-β decreased the risk. Notably, the associations between MCI risk and cystatin C or glucose homeostasis were only founded in diabetes patients. Serum cystatin C was found to be positively associated with HOMA-β (beta (95% CI): 0.20 [0.06, 0.34]), HOMA-IR (0.23 [0.09, 0.36]), and insulin (0.22 [0.09, 0.34]) levels. Moreover, HOMA-β was identified as playing a negative mediating role (proportion mediated: −16%) in the relationship between cystatin C and MCI.

Conclusion

Elevated levels of cystatin C are associated with an increased risk of MCI. The glucose homeostasis indicator, HOMA-β, plays a negative mediating role in the relationship between cystatin C and MCI risk.

The cumulative impacts of anthropogenic stressors vary markedly along environmental gradients

Understanding the cumulative effects of multiple stressors on biodiversity is key to managing their impacts. Stressor interactions are often studied using an additive/antagonistic/synergistic typology, aimed at identifying situations where individual stressor effects are reduced or amplified when they act in combination. Here, we analysed variation in the family richness of stream macroinvertebrates in the groups Ephemeroptera, Plecoptera and Trichoptera (EPT) at 4658 sites spanning a 32° latitudinal range in eastern Australia in relation to two largely human-induced stressors, salinity and turbidity, and two environmental gradients, temperature and slope. The cumulative and interactive effect of salinity and turbidity on EPT family richness varied across the landscape and by habitat (edge or riffle) such that we observed additive, antagonistic and synergistic outcomes depending on the environmental context. Our findings highlight the importance of understanding the consistency of multiple stressor impacts, which will involve higher-order interactions between multiple stressors and environmental factors.

Coexistence between similar invaders: The case of two cosmopolitan exotic insects

Biological invasions are usually examined in the context of their impacts on native species. However, few studies have examined the dynamics between invaders when multiple exotic species successfully coexist in a novel environment. Yet, long-term coexistence of now established exotic species has been observed in North American lady beetle communities. Exotic lady beetles Harmonia axyridis and Coccinella septempunctata were introduced for biological control in agricultural systems and have since become dominant species within these communities. In this study, we investigated coexistence via spatial and temporal niche partitioning among H. axyridis and C. septempunctata using a 31-year data set from southwestern Michigan, USA. We found evidence of long-term coexistence through a combination of small-scale environmental, habitat, and seasonal mechanisms. Across years, H. axyridis and C. septempunctata experienced patterns of cyclical dominance likely related to yearly variation in temperature and precipitation. Within years, populations of C. septempunctata peaked early in the growing season at 550 degree days, while H. axyridis populations grew in the season until 1250 degree days and continued to have high activity after this point. C. septempunctata was generally most abundant in herbaceous crops, whereas H. axyridis did not display strong habitat preferences. These findings suggest that within this region H. axyridis has broader habitat and abiotic environmental preferences, whereas C. septempunctata thrives under more specific ecological conditions. These ecological differences have contributed to the continued coexistence of these two invaders. Understanding the mechanisms that allow for the coexistence of dominant exotic species contributes to native biodiversity conservation management of invaded ecosystems.

The impact of the demographic shift on limb amputation incidence in Saskatchewan, Canada, 2006–2019

Background

Changing demographics in a population may have an inevitable influence on disease incidence including limb amputation. However, the extent to which these changes affect limb amputation (LA) is unknown. Understanding the impact of changing demographics on LA would provide the best opportunity to plan for the future. We assessed the impact of changes in age and sex on limb amputation in Saskatchewan between 2006 and 2019.

Methods

Retrospective linked Saskatchewan’s LA cases, and demographic characteristics and residents population from 2006–2019 was used. The amputation rate was calculated by dividing the total number of LA cases recorded each year by the annual Saskatchewan resident population and the results expressed per 100,000 populations. Furthermore, decomposition analysis was used to assess the impact of changes in age and sex on LA in a decade (2008–2017) and the Generalized Additive Model (GAM) was employed to examine the linear and non-linear effect of age.

Results

We found that in the ten years (2008–2017), the absolute LA rate difference was 9.0 per 100,000 population. Changes in age structure alone contributed 7.7% to the LA rate increase and 92.3% to changes in age-specific LA rates. The decade witnessed a marginal population difference between males and females, but the LA rate was 2.1–2.2 times higher in males than in females. The GAM revealed a non-linear relationship between LA and age, and further indicates that the risk of LA significantly increased as age increases.

Conclusions

In a decade, we found that changes in age distribution and age-specific rate substantially impacted the increase in the LA rate observed in the province. This highlights the urgent need for strategized programs to respond to these changes as both the population and diabetes, which is age-dependent and a leading cause of LA, are expected to increase in the province by 2030. As changes in population and demographic factors are inevitable, this study provides data for policy makers on the need for continuous incorporation of the shift in population in the design of future health services.

Quantitative Analysis of Natural and Anthropogenic Factors Influencing Vegetation NDVI Changes in Temperate Drylands from a Spatial Stratified Heterogeneity Perspective: A Case Study of Inner Mongolia Grasslands, China

The detection and attribution of vegetation dynamics in drylands is an important step for the development of effective adaptation and mitigation strategies to combat the challenges posed by human activities and climate change. However, due to the spatial heterogeneity and interactive influences of various factors, quantifying the contributions of driving forces on vegetation change remains challenging. In this study, using the normalized difference vegetation index (NDVI) as a proxy of vegetation growth status and coverage, we analyzed the temporal and spatial characteristics of the NDVI in China’s Inner Mongolian grasslands using Theil–Sen slope statistics and Mann–Kendall trend test methods. In addition, using the GeoDetector method, a spatially-based statistical technique, we assessed the individual and interactive influences of natural factors and human activities on vegetation-NDVI change. The results show that the growing season average NDVI exhibited a fluctuating upward trend of 0.003 per year from 2000 to 2018. The areas with significant increases in NDVI (p < 0.05) accounted for 45.63% of the entire region, and they were mainly distributed in the eastern part of the Mu Us sandy land and the eastern areas of the Greater Khingan Range. The regions with a decline in the NDVI were mainly distributed in the central and western regions of the study area. The GeoDetector results revealed that both natural and human factors had significant impacts on changes in the NDVI (p < 0.001). Precipitation, livestock density, wind speed, and population density were the dominant factors affecting NDVI changes in the Inner Mongolian grasslands, explaining more than 15% of the variability, while the contributions of the two topography factors (terrain slope and slope aspect) were relatively low (less than 2%). Furthermore, NDVI changes responded to the changes in the level of specific influencing factors in a nonlinear way, and the interaction of two factors enhanced the effect of each singular factor. The interaction between precipitation and temperature was the highest among all factors, accounting for 39.3% of NDVI variations. Findings from our study may aid policymakers in better understanding the relative importance of various factors and the impacts of the interactions between factors on vegetation change, which has important implications for preventing and mitigating land degradation and achieving sustainable pasture use in dryland ecosystems.

Exploring the type and strength of nonlinearity in water quality responses to nutrient loading reduction in shallow eutrophic water bodies: Insights from a large number of numerical simulations

Reducing the load of nutrients is essential to improve water quality while water quality may not respond to the load reduction in a linear way. Despite nonlinear water quality responses being widely mentioned by studies, there is a lack of comprehensive assessment on the extent and type of nonlinear responses considering the seasonal changes. This study aimed to measure the strength of nonlinearity of theoretically possible water quality responses and explore their potential types in shallow eutrophic water bodies. Hereto, we generated 14,710 numerical water body cases that describe the water quality processes using the Environmental Fluid Dynamics Code (EFDC) and applied eight load reduction scenarios on each water body case. Inflows are simplified from Lake Dianchi. The climate conditions consider three cases: Lake Dianchi, Wissahickon Creek, and Famosa Slough. We then developed a nonlinearity strength indicator to quantify the strength and frequency of nonlinear water quality responses. Based on the quantification of nonlinearity, we clustered all the samples of water quality responses using K-Means, an unsupervised Machine Learning algorithm, to find the potential types of nonlinear water quality responses for TN (total nitrogen), TP (total phosphorus), and Chla (chlorophyll a). Results show linear or near-linear response types account for 90%, 69%, and 20% of TN, TP, and Chla samples respectively. TP and Chla could perform more types of nonlinearity. Representative nonlinear water quality responses include disproportional improvement, peak change (disappear, move forwards or afterward), and seasonal deterioration of TN after load reduction. This study would contribute to the current understanding of nonlinear water quality responses to load reduction and provide a basis to study under which conditions the nonlinear responses may emerge.

Temporal scope influences ecosystem driver-response relationships: A case study of Lake Erie with implications for ecosystem-based management

Understanding environmental driver-response relationships is critical to the implementation of effective ecosystem-based management. Ecosystems are often influenced by multiple drivers that operate on different timescales and may be nonstationary. In turn, contrasting views of ecosystem state and structure could arise depending on the temporal perspective of analysis. Further, assessment of multiple ecosystem components (e.g., biological indicators) may serve to identify different key drivers and connections. To explore how the timescale of analysis and data richness can influence the identification of driver-response relationships within a large, dynamic ecosystem, this study analyzed long-term (1969-2018) data from Lake Erie (USA-Canada). Data were compiled on multiple biological, physical, chemical, and socioeconomic components of the ecosystem to quantify trends and identify potential key drivers during multiple time intervals (20 to 50 years duration), using zooplankton, bird, and fish community metrics as indicators of ecosystem change. Concurrent temporal shifts of many variables occurred during the 1980s, but asynchronous dynamics were evident among indicator taxa. The strengths and rank orders of predictive drivers shifted among intervals and were sometimes taxon-specific. Drivers related to nutrient loading and lake trophic status were consistently strong predictors of temporal patterns for all indicators; however, within the longer intervals, measures of agricultural land use were the strongest predictors, whereas within shorter intervals, the stronger predictors were measures of tributary or in-lake nutrient concentrations. Physical drivers also tended to increase in predictive ability within shorter intervals. The results highlight how the time interval examined can filter influences of lower-frequency, slower drivers and higher-frequency, faster drivers. Understanding ecosystem change in support of ecosystem-based management requires consideration of both the temporal perspective of analysis and the chosen indicators, as both can influence which drivers are identified as most predictive of ecosystem trends at that timescale.

Practical implementation of cumulative‐effects management of marine ecosystems in western North America

Globally, ecosystem structure and function have been degraded by the cumulative effects (CE) of multiple stressors. To maintain ecosystem resilience, there is an urgent need to better account for CE in management decision‐making at various scales. Current laws and regulations are supported by a multitude of frameworks and strategies that vary in application and terminology use across management agencies and geopolitical boundaries. We synthesized management frameworks that accounted for CE in marine ecosystems at the regional and national levels across western North America (Canada, United States, Mexico) to identify similarities and shared challenges to successful implementation. We examined examples of solutions to the identified challenges (e.g., interagency and cross‐border partnerships to overcome challenges of managing for ecologically relevant spatial scales). Management frameworks in general consisted of 3 phases: scoping and structuring the system; characterizing relationships; and evaluating management options. Challenges in the robust implementation of these phases included lack of interagency coordination, minimal incorporation of diverse perspectives, and data deficiencies. Cases that provided solutions to these challenges encouraged coordination at ecological rather than jurisdictional scales, enhanced involvement of stakeholders and Indigenous groups, and used nontraditional data sources for decision‐making. Broader implementation of these approaches, combined with increased interagency and international coordination and collaboration, should facilitate the rapid advancement of more effective CE assessment and ecosystem management in North America and elsewhere.

Macrobenthic community responses to multiple environmental stressors in a subtropical estuary

We assessed how multi- and univariate models reflect marine environmental health based on macrobenthic community responses to three environmental stressor categories: hydrodynamics, organic enrichment and metal contamination. We then compared the models with the benthic index AMBI (AZTI Marine Biotic Index). Macrobenthic community and physicochemical variables were sampled at 35 sites along Babitonga Bay, a subtropical estuary in Southern Brazil. Distance-based linear modelling identified depth, grain size and organic matter as well as Cu and Zn as key stressors affecting the macrobenthos. Using canonical analysis of principal coordinates (CAP), we developed three multivariate models based on the variability in community composition, creating stress gradients. The metal gradient showed better correlation with the benthic community. Sediment quality indices (Geoaccumulation Index and Contamination Factor) showed a low to moderate contamination status, with higher concentrations for Cr, Ni and Zn at the inner areas of the bay. According to AMBI, Babitonga Bay has a “good” environmental health status, and the AMBI values show stronger correlations with the hydrodynamic and organic enrichment gradients (r = 0.50 and r = 0.47) rather than the metal gradient (r = 0.29). Lumbrineridae polychaetes (not included in the AMBI list) and Scoloplos sp. were negatively related to the metal contamination gradient and were considered sensitive, while Sigambra sp., Magelona papillicornis, the gastropod Heleobia australis and species of the crustacean order Mysida were positively related to the gradient and considered tolerant to higher concentrations of metals in the sediment. Despite the inconsistency in the ecological classification provided by AMBI and its relationship with the metal gradient, our results suggest that the environmental quality was satisfactory for the studied gradients. The metal gradient showed the weakest correlation to AMBI. In such cases, the ecological classification of taxa by the index should be evaluated under the perspective of the action of inorganic genotoxic contaminants represented by metals.

River connectivity and climate behind the long-term evolution of tropical American floodplain lakes

This study presents the long-term evolution of two floodplains lakes (San Juana and Barbacoas) of the Magdalena River in Colombia with varying degree of connectivity to the River and with different responses to climate events (i.e., extreme floods and droughts). Historical limnological changes were identified through a multiproxy-based reconstruction including diatoms, sedimentation, and sediment geochemistry, while historical climatic changes were derived from the application of the Standardised Precipitation-Evapotranspiration Index. The main gradients in climatic and limnological change were assessed via multivariate analysis and generalized additive models. The reconstruction of the more isolated San Juana Lake spanned the last c. 500 years. Between c. 1,620 and 1,750 CE, riverine-flooded conditions prevailed as indicated by high detrital input, reductive conditions, and dominance of planktonic diatoms. Since the early 1800s, the riverine meander became disconnected, conveying into a marsh-like environment rich in aerophil diatoms and organic matter. The current lake was then formed around the mid-1960s with a diverse lake diatom flora including benthic and planktonic diatoms, and more oxygenated waters under a gradual increase in sedimentation and nutrients. The reconstruction for Barbacoas Lake, a waterbody directly connected to the Magdalena River, spanned the last 60 years and showed alternating riverine-wetland-lake conditions in response to varying ENSO conditions. Wet periods were dominated by planktonic and benthic diatoms, while aerophil diatom species prevailed during dry periods; during the two intense ENSO periods of 1987 and 1992, the lake almost desiccated and sedimentation rates spiked. A gradual increase in sedimentation rates post-2000 suggests that other factors rather than climate are also influencing sediment deposition in the lake. We propose that hydrological connectivity to the Magdalena River is a main factor controlling lake long-term responses to human pressures, where highly connected lakes respond more acutely to ENSO events while isolated lakes are more sensitive to local land-use changes.

A roadmap towards quantitative cumulative impact assessments: Every step of the way

Currently most Cumulative Impacts Assessments (CIAs) are risk-based approaches that assess the potential impact of human activities and their pressures on the ecosystem thereby compromising the achievement of policy objectives. While some of these CIAs apply actual data (usually spatial distributions) they often have to rely on categorical scores based on expert judgement if they actually assess impact which is often expressed as a relative measure that is difficult to interpret in absolute terms. Here we present a first step-wise approach to conduct a fully quantitative CIA based on the selection and subsequent application of the best information available. This approach systematically disentangles risk into its exposure and effect components that can be quantified using known ecological information, e.g. spatial distribution of pressures or species, pressure-state relationships and population dynamics models with appropriate parametrisation, resulting in well-defined assessment endpoints that are meaningful and can be easily communicated to the recipients of advice. This approach requires that underlying assumptions and methodological considerations are made explicit and translated into a measure of confidence. This transparency helps to identify the possible data-handling or methodological decisions and shows the resulting improvement through its confidence assessment of the applied information and hence the resulting accuracy of the CIA. To illustrate this approach, we applied it in a North Sea CIA focussing on two sectors, i.e. fisheries and offshore windfarms, and how they impact the ecosystem and its components, i.e. seabirds, seabed habitats and marine mammals through various pressures. The results provide a "proof of concept" for this generic approach as well as rigorous definitions of several of the concepts often used as part of risk-based approaches, e.g. exposure, sensitivity, vulnerability, and how these can be estimated using actual data. As such this widens the scope for increasingly more quantitative CIAs using the best information available.

Predictability of temporal variation in climate and the evolution of seasonal polyphenism in tropical butterfly communities

Phenotypic plasticity in heterogeneous environments can provide tight environment-phenotype matching. However, the prerequisite is a reliable environmental cue(s) that enables organisms to use current environmental information to induce the development of a phenotype with high fitness in a forthcoming environment. Here, we quantify predictability in the timing of precipitation and temperature change to examine how this is associated with seasonal polyphenism in tropical Mycalesina butterflies. Seasonal precipitation in the tropics typically results in distinct selective environments, the wet and dry seasons, and changes in temperature can be a major environmental cue. We sampled communities of Mycalesina butterflies from two seasonal locations and one aseasonal location. Quantifying environmental predictability using wavelet analysis and Colwell's indices confirmed a strong periodicity of precipitation over a 12-month period at both seasonal locations compared to the aseasonal one. However, temperature seasonality and periodicity differed between the two seasonal locations. We further show that: (a) most females from both seasonal locations synchronize their reproduction with the seasons by breeding in the wet season but arresting reproduction in the dry season. In contrast, all species breed throughout the year in the aseasonal location and (b) species from the seasonal locations, but not those from the aseasonal location, exhibited polyphenism in wing pattern traits (eyespot size). We conclude that seasonal precipitation and its predictability are primary factors shaping the evolution of polyphenism in Mycalesina butterflies, and populations or species secondarily evolve local adaptations for cue use that depend on the local variation in the environment.

Association between exposure to polyfluoroalkyl chemicals and increased fractional exhaled nitric oxide in adults

BACKGROUND

Perfluoroalkyl chemicals (PFCs) are widely detected in the environment and human body, and they have been linked to asthma and a number of respiratory responses in children and mice. However, no previous studies have investigated the association between exposure to PFCs and airway inflammation in adults.

OBJECTIVES

To evaluate the associations between serum PFCs and fractional exhaled nitric oxide (FeNO), a biomarker of airway inflammation, in adults.

METHODS

A cross-sectional study of 3630 adults aged 20-79 years who participated in the National Health and Nutrition Examination Survey (NHANES, 2007-2012) was conducted. Serum concentrations of five major PFCs were measured using SPE-HPLC-TIS-MS/MS method, including perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), and perfluorodecanoic acid (PFDE). The detection rates of them were all >85%. Weighted multivariable linear regression and Bayesian kernel machine regression (BKMR) analyses were applied to examine the associations between serum PFCs and FeNO.

RESULTS

After adjusted for potential confounding factors, linear regression analyses found that compared with their lowest tertiles, highest tertiles of PFOS, PFDE and PFOA were significantly associated with 5.02% (95% CI: 1.40%, 8.77%), 3.77% (95% CI: 0.30%, 7.36%) and 6.34% (95% CI: 2.81%, 10.01%) increases in FeNO, respectively. The second tertile of PFNA was significantly correlated with a 4.79% (95% CI: 1.41%, 8.29%) increase in FeNO compared with the lowest tertile. In the BKMR analysis, the mixture effect of PFCs on FeNO increased significantly when the PFC levels were at or above the 60th percentiles compared to those at their medians. PFOS and PFOA displayed significant positive single-exposure effects on FeNO when all the other PFCs are set at a particular threshold.

CONCLUSIONS

This study provided preliminary evidence that serum PFCs were positively associated with increased FeNO in adults.

Fish harvesting advice under climate change: A risk-equivalent empirical approach

The rate of climate change (CC) has accelerated to the point where it now affects the mid- to long-term sustainability of fishing strategies. Therefore, it is important to consider practical and effective ways to incorporate CC into fisheries advice so that the advice can be considered conditioned to CC. We developed a model to characterise the empirical relationship between a variable affected by climate and fish production. We then used model projections as a foundation for a risk analysis of CC effects on harvesting of Greenland halibut Reinhardtius hippoglossoides in the Gulf of St Lawrence, Canada. The risk-based approach quantified a) the relative change in risk of a status quo fishing strategy under various CC scenarios, and b) the change in fishery exploitation rates required to achieve a management objective over a specified time period at a level of risk considered acceptable (risk equivalent fishery exploitation advice). This empirical approach can be used to develop risk-based advice for any other external variable that affects stock production in addition to climate-related variables and it can be applied in most situations where there is an index of stock biomass and fisheries catch. Shifting the focus from process-based understanding of the responses of fish stocks to CC to quantification of how CC-contributed uncertainty can alter the risks associated with different fishing strategies and/or management options, can ensure timely delivery of robust scientific advice for fisheries under non-stationary environmental conditions.

Cumulative stressors reduce the self-regulating capacity of coastal ecosystems

Marine ecosystems are prone to tipping points, particularly in coastal zones where dramatic changes are associated with interactions between cumulative stressors (e.g., shellfish harvesting, eutrophication and sediment inputs) and ecosystem functions. A common feature of many degraded estuaries is elevated turbidity that reduces incident light to the seafloor, resulting from multiple factors including changes in sediment loading, sea-level rise and increased water column algal biomass. To determine whether cumulative effects of elevated turbidity may result in marked changes in the interactions between ecosystem components driving nutrient processing, we conducted a large-scale experiment manipulating sediment nitrogen concentrations in 15 estuaries across a national-scale gradient in incident light at the seafloor. We identified a threshold in incident light that was related to distinct changes in the ecosystem interaction networks (EIN) that drive nutrient processing. Above this threshold, network connectivity was high with clear mechanistic links to denitrification and the role of large shellfish in nitrogen processing. The EIN analyses revealed interacting stressors resulting in a decoupling of ecosystem processes in turbid estuaries with a lower capacity to denitrify and process nitrogen. This suggests that, as turbidity increases with sediment load, coastal areas can be more vulnerable to eutrophication. The identified interactions between light, nutrient processing and the abundance of large shellfish emphasizes the importance of actions that seek to manage multiple stressors and conserve or enhance shellfish abundance, rather than actions focusing on limiting a single stressor.

Investigating the Diffusion of Workload-Induced Stress—A Simulation Approach

Work-induced stress is widely acknowledged as harming physical and psychosocial health and has been linked with adverse outcomes such as a decrease in productivity. Recently, workplace stressors have increased due to the COVID-19 pandemic. This study aims to contribute to the literature base in a couple of areas. First, it extends the current knowledge base by utilising generative additive modelling (GAMs) to uncover the nature of the relationship between workload (a key workplace stressor) and productivity based on real-world event logs. Additionally, it uses recursive partitioning modelling to shed light on the factors that drive the relationship between these variables. Secondly, it utilises a simulation-based approach to investigate the diffusion of workload-induced stress in the workplace. Simulation is a valuable tool for exploring the effect of changes in a risk-free manner as it provides the ability to run multiple scenarios in a safe and virtual environment with a view to making recommendations to stakeholders. However, there are several recognised issues with traditional simulation approaches, such as inadequate resource modelling and the limited use of simulations for operational decision making. In this study, we propose an approach which extracts the required parameters from an event log and subsequently utilises them to initialise a workload-induced stress diffusion simulation model accurately. We also explore the effects of varying the parameters to control the spread of workload-induced stress within the network. With suitable amendments, this approach can be extended to model the spread of disease (e.g., COVID-19), diffusion of ideas, among other things, in the workplace.

Synergistic interactions among growing stressors increase risk to an Arctic ecosystem

Oceans provide critical ecosystem services, but are subject to a growing number of external pressures, including overfishing, pollution, habitat destruction, and climate change. Current models typically treat stressors on species and ecosystems independently, though in reality, stressors often interact in ways that are not well understood. Here, we use a network interaction model (OSIRIS) to explicitly study stressor interactions in the Chukchi Sea (Arctic Ocean) due to its extensive climate-driven loss of sea ice and accelerated growth of other stressors, including shipping and oil exploration. The model includes numerous trophic levels ranging from phytoplankton to polar bears. We find that climate-related stressors have a larger impact on animal populations than do acute stressors like increased shipping and subsistence harvesting. In particular, organisms with a strong temperature-growth rate relationship show the greatest changes in biomass as interaction strength increased, but also exhibit the greatest variability. Neglecting interactions between stressors vastly underestimates the risk of population crashes. Our results indicate that models must account for stressor interactions to enable responsible management and decision-making.

Lack of definition of mathematical terms in ecology: The case of the sigmoid class of functions in macro-ecology

Defining mathematical terms and objects is a constant issue in ecology; often definitions are absent, erroneous, or imprecise. Through a bibliographic prospection, we show that this problem appears in macro-ecology (biogeography and community ecology) where the lack of definition for the sigmoid class of functions results in difficulties of interpretation and communication. In order to solve this problem and to help harmonize papers that use sigmoid functions in ecology, herein we propose a comprehensive definition of these mathematical objects. In addition, to facilitate their use, we classified the functions often used in the ecological literature, specifying the constraints on the parameters for the function to be defined and the curve shape to be sigmoidal. Finally, we interpreted the different properties of the functions induced by the definition through ecological hypotheses in order to support and explain the interest of such functions in ecology and more precisely in biogeography.

Phosphorus and suspended matter retention in mangroves affected by shrimp farm effluents in NE Brazil

This study compares two mangroves with different land uses in the Jaguaribe River estuary, harboring large shrimp farms, and in the more pristine Pacotí River estuary. Normalized Difference Vegetation Index (NDVI) was used to compare the overall health of the forests. Measures of suspended matter (TSS), total (TP), particulate (PartP) and soluble reactive phosphorus (SRP) in the inflow and outflow waters of tidal channels draining the mangroves were performed during tidal cycles. NDVI varied from 0.65 in the Jaguaribe estuary to 0.85 in the Pacotí, suggesting the impact of shrimp farm effluents on mangrove canopy cover. The shrimp farm influenced site showed 10 times larger absolute ∑P (TP + PartP + SRP) = 1.2-5.2 kg.hr-1) flux than the pristine site (∑P = 0.22 kg.hr-1). Tidal balances showed smaller retentions of the total influx: 28-54%; 44-45%; 38-65% and 8-53% for TSS; TP; SRP; and PartP respectively, in the shrimp farm influenced site to over 93% of the total tidal input of TSS and all P fractions in the pristine mangrove. This suggests that mangrove phosphorus accumulation is decreased in the forest with lower NDVI and limits mangrove's potential as a natural barrier to the nutrient transport to adjacent estuarine and coastal waters.

Comparison of two commonly used methods for identifying water quality thresholds in freshwater ecosystems using field and synthetic data

Defining ecological thresholds has become increasingly relevant for water resource management. Despite the fact that there has been a rapid expansion in methods to evaluate ecological threshold responses to environmental stressors, evaluation of the relative benefits of various methods has received less attention. This study compares the performance of Gradient Forest (GF) and Threshold Indicator Taxa Analysis (TITAN) for identifying water quality thresholds in both field and synthetic data. Analysis of 14 years of macroinvertebrates data from the Mediterranean catchments of the Torrens and Onkaparinga Rivers, South-Australia, identified electrical conductivity (EC) and total phosphorus (TP) as the most important water quality variables affecting macroinvertebrates. Water quality thresholds for macroinvertebrates identified by both methods largely corresponded at low EC (GF: 400-900 μS cm^-1 vs. TITAN: 407-951 μScm^-1), total phosphorus (TP) (GF: 0.02-0.18 mg L^-1 vs. TITAN: 0.02-0.04 mg L^-1) and total nitrogen (TN) (GF: 0.2 mg L^-1 vs. TITAN: 0.28-0.67 mg L^-1) concentrations. However, multiple GF-derived thresholds, particularly at high stressor concentrations, were representative of low data distribution, and thus need to be considered with caution. In another case study of South Australian diatom data, there were marked differences in GF and TITAN identified thresholds for EC (GF: 5000 μScm^-1 vs. TITAN 1004-2440 μS cm^-1) and TP (GF: 250-500 μg L^-1 vs. TITAN: 11-329 μg L^-1). These differences were due to the fact that while TITAN parsed species responses into negative and positive taxa, GF overestimated thresholds by aggregating the response of taxa that increase and decrease along environmental gradients. Given these findings, we also evaluated the methods' performance using different distributions of synthetic data i.e. with both skewed and uniform distribution of samples and species responses. Both methods identified similar change-points in the case of a uniform environmental gradient, except when species optima were simulated at centre of the gradient. Here GF detected the change-points but TITAN failed to do so. GF also outperformed TITAN when four simulated species change-points were present. Thus, the distribution of species responses and optima and the evenness of the environment gradient can affect the models' performance. This study has shown that both methods are robust in identifying change in species response but threshold identification differs depending both on the analysis used and the nature of ecological data. We recommend the careful application of GF and TITAN, noting these differences in performance, will improve their application for water resource management.

Identification of Regime Shifts and Their Potential Drivers in the Shallow Eutrophic Lake Yilong, Southwest China

Regime shifts in shallow lakes can lead to great changes in ecosystem structures and functions, making ecosystem management more complicated. Lake Yilong, located in Yunnan Province, is one of the most eutrophic lakes in China. Although there is a high possibility that this lake has undergone regime shift one or more times, the presence of regime shifts and their drivers remain unknown. Here, we employed the sequential t-test analysis of regime shifts to detect the regime shifts based on the long-term (1989–2018) dataset of the lake. We further determined their potential drivers, and explored the nutrient thresholds of regime shifts and hysteresis. The results showed that during the testing period, three regime shifts occurred in 1996 (restorative type), 2009 (catastrophic type) and 2014 (restorative type). The potential key drivers for the first two regime shifts (1996 and 2009) were both related to aquaculture. The abolition of cage fish culture may have led to the restorative regime shift in 1996, and the stocking of crabs and excessive premature releasing of fry possibly caused the catastrophic regime shift in 2009. However, the third regime shift, which occurred in 2014, was possibly related to the drought and succedent hydration. These results indicate that adjustments of aquaculture strategy and hydrological conditions are critical for the lake ecosystem’s recovery. Moreover, the total phosphorus thresholds were identified to be lower than 0.046 mg/L (restorative type) and higher than 0.105 mg/L (catastrophic type), respectively. In addition, an obvious hysteresis was observed after 2014, suggesting that nutrient reduction is important for this lake’s management in the future.

A Model for Disentangling Dependencies and Impacts among Human Activities and Marine Ecosystem Services

Understanding and communicating the links among human activities and marine ecosystem services are fundamental for ecosystem-based management, which aims at attaining ecological, economic and social sustainability in the use of our seas. Relationships are typically complex and may differ between geographic areas. Here, an assessment model that combines available quantitative, semi-quantitative and qualitative information, rooted in the DAPSIR (Driver-Activity-Pressure-State-Impact-Response) framework and assessment requirements of the EU Marine Strategy Framework Directive, is developed and applied. Focusing on Swedish marine waters, major human activities at sea are evaluated in relation to their dependencies and impacts on the status of marine ecosystem services. This case study is a consensus assessment based on evaluation of available literature and data. By relating degrees of dependencies and impacts to values of different economic sectors, discrepancies among sectors with respect to their impact versus their monetary value can be identified. In our case, commercial fishing depends on and influences a wide range of ecosystem services, while other sectors, such as shipping, depend little on marine ecosystem services. At the extreme end of the range, pressures from human activities in the past, such as historical nutrient emissions, still have prominent influence on ecosystem services today, entailing considerable losses. Marine tourism and commercial fishing show similar dependencies on ecosystem services, but tourism has a clearly lower impact on ecosystem services and a higher monetary value. The model may serve as a useful tool for communicating and guiding priorities in integrated environmental management and maritime spatial planning.

Estimation of nonlinear water-quality trends in high-frequency monitoring data

Recent advances in high-frequency water-quality sensors have enabled direct measurements of physical and chemical attributes in rivers and streams nearly continuously. Water-quality trends can be used to identify important watershed-scale changes driven by natural and anthropogenic influences. Statistical methods to estimate trends using high-frequency data are lacking. To address this gap, an evaluation of the generalized additive model (GAM) approach to test for trends in high-frequency data was conducted. Our proposed framework includes methods for handling serial correlation, trend estimation and slope-change detection, and trend interpretation at arithmetic scale for log-transformed variables. Water-temperature and turbidity data, representing two analytes with different temporal patterns, collected from the James River at Cartersville, Virginia, USA, were chosen for this analysis. Results indicated that the model, including flow, season, time covariates, and interaction between flow and season performed well for both analytes. The same model structure was applied to specific conductance data, collected from a small highly urbanized watershed, with satisfactory model performance. The water temperature GAM results indicated that the significant decreasing-then-increasing patterns after 2012 were mainly driven by air temperature changes. The turbidity trend was not significant over time. The specific conductance results showed a consistently upward trend over the last decade due to ever-increasing urbanization in the small watershed. This study suggests that the GAM method has great potential as a useful tool for trend analysis on high-frequency data, and for informing watershed managers of hydro-climatic and human influences on water quality by detecting crucial signal variation over time.

Recent pace of change in human impact on the world's ocean

Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities – and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003–2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all countries saw increases in cumulative impacts in their coastal waters, as did all ecosystems, with coral reefs, seagrasses and mangroves at most risk. Mitigation of stressors most contributing to increases in overall cumulative impacts is urgently needed to sustain healthy oceans.

Recent pace of change in human impact on the world's ocean

Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities - and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003-2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all countries saw increases in cumulative impacts in their coastal waters, as did all ecosystems, with coral reefs, seagrasses and mangroves at most risk. Mitigation of stressors most contributing to increases in overall cumulative impacts is urgently needed to sustain healthy oceans.

Monitoring for tipping points in the marine environment

Increasingly studies are reporting sudden and dramatic changes in the structure and function of communities or ecosystems. The prevalence of these reports demonstrates the importance for management of being able to detect whether these have happened and, preferably, whether they are likely to occur. Ecological theory provides the rationale for why such changes occur and a variety of statistical indicators of approach that have generic properties have been developed. However, whether the theory has successfully translated into monitoring programmes is unknown. We searched the literature for guidelines that would drive design of monitoring programmes able to detect past and approaching tipping points and analysed marine monitoring programmes in New Zealand. We found very few guidelines in the ecological, environmental or monitoring literature, although both simulation and marine empirical studies suggest that within-year sampling increases the likelihood of detecting approaching tipping points. The combination of the need to monitor both small and medium scale temporal dynamics of multiple variables to detect tipping points meant that few marine monitoring programmes in New Zealand were fit for that purpose. Interestingly, we found many marine examples of studies detecting past and approaching TP with fewer data than was common in the theoretical literature. We, therefore, suggest that utilizing ecological knowledge is of paramount importance in designing and analyzing time-series monitoring for tipping points and increasing the certainty for short-term or infrequent datasets of whether a tipping point has occurred. As monitoring plays an important role in management of tipping points by providing supporting information for other locations about when and why a tipping point may occur, we believe that monitoring for tipping points should be promoted.

Exploring variability in environmental impact risk from human activities across aquatic ecosystems

Aquatic ecosystems are under severe pressure. Human activities introduce an array of pressures that impact ecosystems and their components. In this study we focus on the aquatic domains of fresh, coastal and marine waters, including rivers, lakes and riparian habitats to transitional, coastal as well as shelf and oceanic habitats. In an environmental risk assessment approach, we identified impact chains that link 45 human activities through 31 pressures to 82 ecosystem components. In this linkage framework >22,000 activity-pressure-ecosystem component interactions were found across seven European case studies. We identified the environmental impact risk posed by each impact chain by first categorically weighting the interactions according to five criteria: spatial extent, dispersal potential, frequency of interaction, persistence of pressure and severity of the interaction, where extent, dispersal, frequency and persistence account for the exposure to risk (spatial and temporal), and the severity accounts for the consequence of the risk. After assigning a numerical score to each risk criterion, we came up with an overall environmental impact risk score for each impact chain. This risk score was analysed in terms of (1) the activities and pressures that introduce the greatest risk to European aquatic domains, and (2) the aquatic ecosystem components and realms that are at greatest risk from human activities. Activities related to energy production were relevant across the aquatic domains. Fishing was highly relevant in marine and environmental engineering in fresh waters. Chemical and physical pressures introduced the greatest risk to the aquatic realms. Ecosystem components that can be seen as ecotones between different ecosystems had high impact risk. We show how this information can be used in informing management on trade-offs in freshwater, coastal and marine resource use and aid decision-making.

Investigating cumulative effects across ecological scales

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.

Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans

Increasing anthropogenic pressure on marine ecosystems from fishing, pollution, climate change, and other sources is a big concern in marine conservation. Scientists have thus developed spatial models to map cumulative human impacts on marine ecosystems. However, these models are based on many assumptions and incorporate data that suffer from substantial incompleteness and inaccuracies. Rather than using a single model, we used Monte Carlo simulations to identify which parts of the oceans are subject to the most and least impact from anthropogenic stressors under 7 simulated sources of uncertainty (factors: e.g., missing stressor data and assuming linear ecosystem responses to stress). Most maps agreed that high-impact areas were located in the Northeast Atlantic, the eastern Mediterranean, the Caribbean, the continental shelf off northern West Africa, offshore parts of the tropical Atlantic, the Indian Ocean east of Madagascar, parts of East and Southeast Asia, parts of the northwestern Pacific, and many coastal waters. Large low-impact areas were located off Antarctica, in the central Pacific, and in the southern Atlantic. Uncertainty in the broad-scale spatial distribution of modeled human impact was caused by the aggregate effects of several factors, rather than being attributable to a single dominant source. In spite of the identified uncertainty in human-impact maps, they can-at broad spatial scales and in combination with other environmental and socioeconomic information-point to priority areas for research and management.

A dynamic management framework for socio-ecological system stewardship: A case study for the United States Bureau of Ocean Energy Management

An effective and efficient stewardship of natural resources requires consistency across all decision-informing approaches and components involved, i.e., managerial, governmental, political, and legal. To achieve this consistency, these elements must be aligned under an overarching management goal that is consistent with current and well-accepted knowledge. In this article, we investigate the adoption by the US Bureau of Ocean Energy Management of an environmental resilience-centered system that manages for resilience of marine ecological resources and its associated social elements. Although the framework is generally tailored for this Bureau, it could also be adapted to other federal or non-federal organizations. This paper presents a dynamic framework that regards change as an inherent element of the socio-ecological system in which management structures, e.g., federal agencies, are embedded. The overall functioning of the management framework being considered seeks to mimic and anticipate environmental change in line with well-accepted elements of resilience-thinking. We also investigate the goal of using management for resilience as a platform to enhance socio-ecological sustainability by setting specific performance metrics embedded in pre-defined and desired social and/or ecological scenarios. Dynamic management frameworks that couple social and ecological systems as described in this paper can facilitate the efficient and effective utilization of resources, reduce uncertainty for decision and policy makers, and lead to more defensible decisions on resources.

A regional assessment of cumulative impact mapping on Mediterranean coralligenous outcrops

In the last decade, the ‘Cumulative Pressure and Impact Assessment’ (CPIA) approach emerged as a tool to map expected impacts on marine ecosystems. However, CPIA assumes a linear response of ecosystems to increasing level of cumulative pressure weighting sensitivity to different anthropogenic pressures through expert judgement. We applied CPIA to Mediterranean coralligenous outcrops over 1000 km of the Italian coastline. Extensive field surveys were conducted to assess the actual condition of coralligenous assemblages at varying levels of human pressure. As pressure increased, a clear shift from bioconstructors to turf-dominated assemblages was found. The linear model originally assumed for CPIA did not fit the actual relationship between expected cumulative impact versus assemblage degradation. A log-log model, instead, best fitted the data and predicted a different map of cumulative impact in the study area able to appreciate the whole range of impact scenarios. Hence, the relative importance of different drivers in explaining the observed pattern of degradation was not aligned with weights from the expert opinion. Such findings stress the need for more incisive efforts to collect empirical evidence on ecosystem-specific responses to human pressure in order to refine CPIA predictions.

Conservation planning for freshwater-marine carryover effects on Chinook salmon survival

Experiences of migratory species in one habitat may affect their survival in the next habitat, in what is known as carryover effects. These effects are especially relevant for understanding how freshwater experience affects survival in anadromous fishes. Here, we study the carryover effects of juvenile salmon passage through a hydropower system (Snake and Columbia rivers, northwestern United States). To reduce the direct effect of hydrosystem passage on juveniles, some fishes are transported through the hydrosystem in barges, while the others are allowed to migrate in-river. Although hydrosystem survival of transported fishes is greater than that of their run-of-river counterparts, their relative juvenile-to-adult survival (hereafter survival) can be less. We tested for carryover effects using generalized linear mixed effects models of survival with over 1 million tagged Chinook salmon, Oncorhynchus tshawytscha (Walbaum) (Salmonidae), migrating in 1999-2013. Carryover effects were identified with rear-type (wild vs. hatchery), passage-type (run-of-river vs. transported), and freshwater and marine covariates. Importantly, the Pacific Decadal Oscillation (PDO) index characterizing cool/warm (i.e., productive/nonproductive) ocean phases had a strong influence on the relative survival of rear- and passage-types. Specifically, transportation benefited wild Chinook salmon more in cool PDO years, while hatchery counterparts benefited more in warm PDO years. Transportation was detrimental for wild Chinook salmon migrating early in the season, but beneficial for later season migrants. Hatchery counterparts benefited from transportation throughout the season. Altogether, wild fish could benefit from transportation approximately 2 weeks earlier during cool PDO years, with still a benefit to hatchery counterparts. Furthermore, we found some support for hypotheses related to higher survival with increased river flow, high predation in the estuary and plume areas, and faster migration and development-related increased survival with temperature. Thus, pre- and within-season information on local- and broad-scale conditions across habitats can be useful for planning and implementing real-time conservation programs.

Spatial and temporal changes in cumulative human impacts on the world's ocean

Human pressures on the ocean are thought to be increasing globally, yet we know little about their patterns of cumulative change, which pressures are most responsible for change, and which places are experiencing the greatest increases. Managers and policymakers require such information to make strategic decisions and monitor progress towards management objectives. Here we calculate and map recent change over 5 years in cumulative impacts to marine ecosystems globally from fishing, climate change, and ocean- and land-based stressors. Nearly 66% of the ocean and 77% of national jurisdictions show increased human impact, driven mostly by climate change pressures. Five percent of the ocean is heavily impacted with increasing pressures, requiring management attention. Ten percent has very low impact with decreasing pressures. Our results provide large-scale guidance about where to prioritize management efforts and affirm the importance of addressing climate change to maintain and improve the condition of marine ecosystems.

Human pressure on the ocean is thought to be increasing globally, yet the magnitude and patterns of these changes are largely unknown. Here, the authors produce a global map of change in cumulative human pressures over the past 5 years, and show that ∼66% of the ocean has experienced elevated human impact.