Search

Response diversity increases the potential ‘options’ for ecological communities to respond to stress (i.e. response capacity). An indicator of community response diversity is the diversity of different traits associated with their capacity to be resistant to stress, to recover and to regulate ecosystem functions. We conducted a network analysis of traits using benthic macroinvertebrate community data from a large-scale field experiment to explore the loss of response diversity along environmental gradients. We elevated sediment nutrient concentrations (a process that occurs with eutrophication) at 24 sites (in 15 estuaries) with varying environmental conditions (water column turbidity and sediment properties). Macroinvertebrate community response capacity to nutrient stress was dependent on the baseline trait network complexity in the ambient community (i.e. non-enriched sediments). The greater the complexity of the baseline network, the less variable the network response to nutrient stress was; in contrast, more variable responses to nutrient stress occurred with simpler networks. Thus, stressors or environmental variables that shift baseline network complexity also shift the capacity for these ecosystems to respond to additional stressors. Empirical studies that explore the mechanisms responsible for loss of resilience are essential to inform our ability to predict changes in ecological states.

Ecosystems simultaneously deliver multiple functions that relate to both the activities of resident species and environmental conditions. One of the biggest challenges in multifunctionality assessment is balancing analytical simplicity with ecosystem complexity. As an alternative to index‐based approaches, we introduce a multivariate network analysis that uses network theory to assess multifunctionality in terms of the relationships between species' functional traits, environmental characteristics, and functions. We tested our approach in a complex and heterogeneous ecosystem, marine intertidal sandflats. We considered eight ecosystem function, five macrofaunal functional trait groups derived from 36 species, and four environmental characteristics. The indicators of ecosystem functions included the standing stock of primary producers, oxygen production, benthic oxygen consumption, DIN (ammonium and NOx efflux) and phosphate release from the sediments, denitrification, and organic matter degradation at the sediment surface. Trait clusters included functional groups of species that shared combinations of biological traits that affect ecosystem function: small mobile top 2 cm dwellers, suspension feeders, deep‐dwelling worms, hard‐bodied surface dwellers, and tube‐forming worms. Environmental characteristics included sediment organic matter, %mud, %shell hash, and %sediment water content. Our results visualize and quantify how multiple ecosystem elements are connected and contribute to the provision of functions. Small mobile top 2 cm dwellers (among trait clusters) and %mud (among environmental characteristics) were the best predictor for multiple functions. Detailed knowledge of multifunctionality relationships can significantly increase our understanding of the real‐world complexity of natural ecosystems. Multivariate network analysis, as a standalone method or applied alongside already existing single index multifunctionality methods, provides means to advance our understanding of how environmental change and biodiversity loss can influence ecosystem performance across multiple dimensions of functionality. Embedding such a detailed yet holistic multifunctionality assessment in environmental decision‐making will support the assessment of multiple ecosystem services and social‐ecological values., Our manuscript presents the method, multivariate network analysis, that allows studying complex mechanistic ecological underpinnings of ecosystem multifunctionality at the ecosystem scale, overcoming information loss generated by commonly used indices such as species richness.

It can be challenging to differentiate community changes caused by human activities from the influence of natural background variability. Using gradient forest analysis, we explored the relative importance of environmental factors, operating across multiple spatio-temporal scales, in influencing patterns of compositional turnover in estuarine benthic macroinvertebrate communities across New Zealand. Both land-derived stressors (represented by sediment mud content and total sediment nitrogen and phosphorus content) and natural environmental variables (represented by sea surface temperature, Southern Oscillation Index, and wind-wave exposure) were important predictors of compositional turnover, reflecting a matrix of processes interacting across space and time. Generalized linear models were used to determine whether measures of benthic macroinvertebrate diversity, which are commonly used as indicators of ecological health on a local scale, changed in a way that was consistent with the compositional turnover along the environmental gradient. As expected, compositional turnover along land-derived stressor gradients was negatively associated with diversity indices, suggesting a decline in ecological health as land-derived stressors increase. This study moves towards an ecosystem-based management approach that focusses on cumulative effects rather than single stressors by considering how multiple land-derived stressors influence indicators of estuarine health, against a background of natural variability across several spatio-temporal scales.

One of the challenges in modern ecology is reconciling how biotic interactions and abiotic factors are interwoven drivers of community assembly. β‐diversity is a measure of the variation in species composition across space and time. The drivers of variability in β‐diversity are thus responsible for dictating the trajectory of assembling communities. With data from multiscale surveys conducted in three marine intertidal sandflats, we aimed to determine the relative importance and interdependencies of biotic engineering, environment and spatial distances for β‐diversity. In each sandflat, macrofauna and environmental properties were assessed in 400 samples collected at different spatial distances over 300 000 m². The role of environmental variability in driving patterns in β‐diversity and species turnover was dependent on the abundances of ecosystem engineers and spatial connectivity among seascapes as shown by the variance explained by the interaction terms in the variance partitioning. Our results highlight the interdependence between space, environment and species interactions in driving community assembly. Given that most models aiming to explain β‐diversity variation only consider abiotic factors, our findings call for the incorporation of biotic interactions into these models and we argue that this is essential for understanding resilience to environmental change. The degree of interdependence between environment, space and biotic interactions in driving ecological assembly is pivotal to our understanding of how biodiversity will respond to predicted changes in habitats, environment and key species distributions.

To enable environmental management actions to be more effectively prioritized, cumulative effects between multiple stressors need to be accounted for in risk-assessment frameworks. Ecological risk and uncertainty are generally high when multiple stressors occur. In the face of high uncertainty, transparent communication is essential to inform decision-making. The impact of stressor interactions on risk and uncertainty was assessed using generalized linear models for additive and multiplicative effect of six anthropogenic stressors on the abundance of estuarine macrofauna across New Zealand. Models that accounted for multiplicative stressor interactions demonstrated that non-additive effects dominated, had increased explanatory power (6 to 73 % relative increase between models), and thereby reduced the risk of unexpected ecological responses to stress. Secondly, 3D-plots provide important insights in the direction, magnitude and gradients of change, and aid transparency and communication of complex stressor effects. Notably, small changes in a stressor can cause a disproportionally steep gradient of change for a synergistic effect where the tolerance to stressors are lost, and would invoke precautionary management. 3D-plots were able to clearly identify directional shifts where the nature of the interaction changed from antagonistic to synergistic along increasing stressor gradients. For example, increased nitrogen load and exposure caused a shift from positive to negative effect on the abundance of a deposit-feeding polychaete (Magelona). Assessments relying on model coefficient estimates, which provide one effect term, could not capture the complexities observed in 3D-plots and are at risk of mis-identifying interaction types. Finally, visualising model uncertainty demonstrated that although error terms were higher for multiplicative models, they better captured the uncertainty caused by data availability. Together, the steep gradients of change identified in 3D-plots and the higher uncertainty in model predictions in multiplicative models urges more conservative limits to be set for management that account for risk and uncertainty in multiple stressor effects.

The biodiversity crisis has increased interest in understanding the role of biodiversity for ecosystem functioning. Functional traits are often used to infer ecosystem functions to increase our understanding of these relationships over larger spatial scales. The links between specific traits and ecosystem functioning are, however, not always well established. We investigated how the choice of analyzing either individual species, selected modalities, or trait combinations affected the spatial patterns observed on a sandflat and how this was related to the natural variability in ecosystem functioning. A large dataset of 400 benthic macrofauna samples was used to explore distribution patterns. We hypothesized that (1) if multiple species (redundancy) represent a trait combination or a modality their spatial patterns would be smoothed out, and (2) the lost spatial variability within a trait combination or modality, due to the smoothing effect, would potentially affect their utility for predicting ecosystem functioning (tested on a dataset of 24 samples). We predicted that species would show heterogeneous small spatial patterns, while modalities and trait combinations would show larger and more homogeneous patterns because they would represent a collection of many distributions. If modalities and trait combinations are better predictors of ecosystem functioning than species, then the smoother spatial patterns of modalities and trait combinations would result in a more homogeneous landscape of ecosystem function and the number of species exhibiting specific traits would provide functional redundancy. Our results showed some smoothing of spatial patterns progressing from species through modalities to trait combinations, but generally spatial patterns reflected a few dominant key species. Moreover, some individual modalities and species explained more or equal proportions of the variance in the ecosystem functioning than the combined traits. The findings thus suggest that only some spatial variability is lost when species are combined into modalities and trait combinations and that a homogeneous landscape of ecosystem function is not likely., Functional traits are often used to infer ecosystem functioning across larger scales, but how do they reflect species distributions and how well do they actually explain the natural spatial variability in ecosystem functioning? This was examined with a rarely seen extensive dataset of benthic macrofauna samples and solute flux measurements across the sediment–water interface.

To cope with increasing nitrogen loading to estuarine systems, the demand for removal via denitrification is rising. Understanding how the connections between biogeochemistry and ecology regulate denitrification rates along gradients of nutrient and sediment loading is necessary to predict ecosystem function. Previous studies have shown that denitrification rates are typically highest in muddy, nutrient-rich sediments and decrease in sandy, nutrient-poor sites. Denitrification rates were measured at four subtidal sites positioned from the upper to lower estuary. Site 1 was closest to the primary riverine nutrient supply with the highest suspended sediment and benthic mud content that decreased with distance downstream. Contrary to expectations, denitrification rates were lowest at the most upstream site (22.35 ± 13.34 μmol N2 m−2 h−1) and higher downstream (57.84 ± 5.72 μmol N2 m−2 h−1). While respiration, primary production, and sediment characteristics affected net denitrification rates and efficiency, results indicated that macrofaunal abundance (Site 1, 60.8 ± 7.3 individuals/core; Sites 2–4, 177.7 ± 10.8 individuals/core), primarily tube-dwelling polychaetes (Site 1, 0.5 ± 0.5 individuals/core; sites 2–4, 122.5 ± 8.0 individuals/core), played an important role. Their influence was highest in muddier sediments (median grain size

International audience; Despite many sectors of society striving for sustainability in environmental management, humans often fail to identify and act on the connections and processes responsible for social-ecological tipping points. Part of the problem is the fracturing of environmental management and social-ecological research into ecosystem domains (land, freshwater, and sea), each with different scales and resolution of data acquisition and distinct management approaches. We present a perspective on the social-ecological connections across ecosystem domains that emphasize the need for management reprioritization to effectively connect these domains. We identify critical nexus points related to the drivers of tipping points, scales of governance, and the spatial and temporal dimensions of social-ecological processes. We combine real-world examples and a simple dynamic model to illustrate the implications of slow management responses to environmental impacts that traverse ecosystem domains. We end with guidance on management and research opportunities that arise from this cross-domain lens to foster greater opportunity to achieve environmental and sustainability goals.

Similar to other coastal biogenic habitats (e.g. tidal marshes, kelp forests, mangroves and coral reefs), a key function of seagrass meadows is the enhancement of biodiversity. Variability at multiple spatial scales is a driver of biodiversity, but our understanding of the response of macrofauna communities to variability of seagrass meadows is limited. We examined the macrofauna community structure (abundance and biomass) and diversity patterns (alpha- and beta-diversity) across a seascape gradient of eleven seagrass meadows differing in the number, composition and density of plant species. The variability of the macrobenthic communities was regulated by a combination of sedimentary (mainly for the infauna) and macrophyte (mainly for the epifauna) predictors. We demonstrate that the natural occurrence of drifting algae trapped in the aboveground complexity of the meadows benefits seagrass macrofauna. Seagrass-associated macrofauna showed a clear increase in abundance and alpha-diversity metrics with increasing habitat complexity attributes (i.e. shoot density, plant biomass and canopy height). Furthermore, partitioning of beta-diversity (i.e. the variation of species composition between sites) implied the replacement of some species by others between sites (i.e. spatial turnover) instead of a process of species loss (or gain) from site to site (i.e. nestedness). Therefore, the enhancement of macrofauna diversity across an increasing gradient of seagrass complexity, and the dominance of the turnover component suggest that devoting conservation efforts on many different types of meadows, including the less diverse, should be a priority for coastal habitat-management., Open access funding provided by University of Helsinki including Helsinki University Central Hospital. The study was funded by the Academy of Finland (Project ID 294853) and the University of Helsinki and Stockholm University strategic fund for collaborative research (The Baltic Bridge initiative). DL, JH, and ST JH were supported by a senior visiting research fellowship funded by the Walter and Andree de Nottbeck Foundation

Many cetacean species are at risk from anthropogenic disturbances including climate change, pollution, and habitat degradation. Identifying cetacean hotspots for conservation management is therefore required. Aotearoa–New Zealand waters are used by 53% of the world’s cetacean species and are a global cetacean diversity hotspot. Using geographic predictions of cetacean taxa, we aimed to identify important areas within New Zealand waters using two methods: estimates of cetacean richness and a spatial prioritization analysis. For both methods, we investigated how varying levels of uncertainty in predictions of the taxa’ occurrence layers would affect our interpretation of cetacean hotspots. Despite some marked spatial differences in distribution of important areas for cetacean diversity, both methods, across all uncertainty scenarios, highlighted six distinct deep offshore regions as important habitat. Generally, inshore areas had lower richness estimates than offshore areas, but these remain important for conservation for species with limited ranges (e.g., the endemic Māui and Hector’s dolphins), and in some places had similar richness values to offshore hotspots. Furthermore, inshore hotspots had lower uncertainty in predicted taxa distribution and richness estimates. The use of two different uncertainty estimates allows the integration of distributional information from differing sources (different modeling methods with varying numbers of cetacean records) to be integrated in a robust and conservative way. Identification of cetacean hotspots with varying levels of uncertainty provides a robust and efficient step toward prioritizing areas for conservation management in a participatory process.

The approach of applying stressor load limits or thresholds to aid estuarine management is being explored in many global case studies. However, there is growing concern regarding the influence of multiple stressors and their cumulative effects on the functioning of estuarine ecosystems due to the considerable uncertainty around stressor interactions. Recognising that empirical data limitations hinder parameterisation of detailed models of estuarine ecosystem responses to multiple stressors (suspended sediment, sediment mud and metal content, and nitrogen inputs), an expert driven Bayesian network (BN) was developed and validated. Overall, trends in estuarine condition predicted by the BN model were well supported by field observations, including results that were markedly higher than random (71–84% concordance), providing confidence in the overall model dynamics. The general BN framework was then applied to a case study estuary to demonstrate the model's utility for informing management decisions. Results indicated that reductions in suspended sediment loading were likely to result in improvements in estuarine condition, which was further improved by reductions in sediment mud and metal content, with an increased likelihood of high abundance of ecological communities relative to baseline conditions. Notably, reductions in suspended sediment were also associated with an increased probability of high nuisance macroalgae and phytoplankton if nutrient loading was not also reduced (associated with increased water column light penetration). Our results highlight that if stressor limit setting is to be implemented, limits must incorporate ecosystem responses to cumulative stressors, consider the present and desired future condition of the estuary of interest, and account for the likelihood of unexpected ecological outcomes regardless of whether the experts (or empirical data) suggest a threshold has or has not been triggered.

Global climate change has profound implications on species distributions and ecosystem functioning. In the coastal zone, ecological responses may be driven by various biogeochemical and physical environmental factors. Synergistic interactions can occur when the combined effects of stressors exceed their individual effects. The Red Sea, characterized by strong gradients in temperature, salinity, and nutrients along the latitudinal axis provides a unique opportunity to study ecological responses over a range of these environmental variables. Using multiple linear regression models integrating in situ, satellite and oceanographic data, we investigated the response of coral reef taxa to local stressors and recent climate variability. Taxa and functional groups responded to a combination of climate (temperature, salinity, air-sea heat fluxes, irradiance, wind speed), fishing pressure and biogeochemical (chlorophyll a and nutrients - phosphate, nitrate, nitrite) factors. The regression model for each species showed interactive effects of climate, fishing pressure and nutrient variables. The nature of the effects (antagonistic or synergistic) was dependent on the species and stressor pair. Variables consistently associated with the highest number of synergistic interactions included heat flux terms, temperature, and wind speed followed by fishing pressure. Hard corals and coralline algae abundance were sensitive to changing environmental conditions where synergistic interactions decreased their percentage cover. These synergistic interactions suggest that the negative effects of fishing pressure and eutrophication may exacerbate the impact of climate change on corals. A high number of interactions were also recorded for algae, however for this group, synergistic interactions increased algal abundance. This study is unique in applying regression analysis to multiple environmental variables simultaneously to understand stressor interactions in the field. The observed responses have important implications for understanding climate change impacts on marine ecosystems and whether managing local stressors, such as nutrient enrichment and fishing activities, may help mitigate global drivers of change.

9 pages, 4 figures, 1 table, supplementary data https://doi.org/10.1016/j.jenvman.2018.09.034, It is crucial that societies are informed on the risks of impoverished ecosystem health for their well-being. For this purpose, Ecological Integrity (EI) is a useful concept that seeks to capture the complex nature of ecosystems and their interaction with social welfare. But the challenge remains to measure EI and translate scientific terminology into operational language to inform society. We propose an approach that simplifies marine ecosystem complexity by applying scientific knowledge to identify which components reflect the state or state change of ecosystems. It follows a bottom-up structure that identifies, based on expert knowledge, biological components related with past and present changing conditions. It is structured in 5 stages that interact in an adaptive way: stage 1, in situ observations suggest changes could be happening; stage 2 explores available data that represent EI; stage 3, experts' workshops target the identification of the minimum set of variables needed to define EI, or the risk of losing EI; an optative stage 4, where deviance from EI, or risk of deviance, is statistically assessed; stage 5, findings are communicated to society. We demonstrate the framework effectiveness in three case studies, including a data poor situation, an area where lack of reference sites hampers the identification of historical changes, and an area where diffuse sources of stress make it difficult to identify simple relationships with of ecological responses. The future challenge is to operationalise the approach and trigger desirable society actions to strengthen a social-nature link, Funding for JH was provided by NIWA Coasts and Oceans Centre (MBIE CORE). SdJ was funded by H2020-Marie Skłodowska-Curie Action MSCA-IF-2016 [Project ID: 743545]. MDS was funded by FONDECYT 1130580 grant and ICM grant CCM – RC130004 from Ministerio de Economía, Fomento y Turismo (Chilean Government)

Demonstrating changes over time in soft-sediment ecosystems is critical to understanding ecosystem dynamics and predicting how they may change. Monitoring is thus an essential process providing insight into how complex ecological systems change and has important implications in adaptive management, impact assessment and stewardship. The chapter describes how both slow and fast processes operate in soft sediments and drive changes across multiple time scales. The role of time series data in helping to understand detailed short-term studies is discussed. The interactions between space and time have important implications in study design, interpretation and accounting for inconsistency in results. The chapter finishes by discussing two types of temporal change of significant concern these days due to their implications for resilience and ecosystem dynamics: tipping points and hysteresis.

This chapter addresses the biological processes that influence community composition and dynamics, highlighting the multi-trophic and multi-functional nature of soft-sediment communities. Characterising the biological interactions into competition, predation, adult–juvenile interaction, facilitation, parasitism and disease, the chapter initially focusses on what we know about these processes, their effect on other biological components and their importance in different benthic habitats. It then extends to consider how they, in conjunction with mobility of species, can influence the broader-scale spatial structure and temporal dynamics connecting communities and functions. The chapter recognises the importance of differences in strength of interaction and the potential for weak interactions to affect community dynamics. This is framed around the concept of self-organisation as an emergent characteristic of ecosystem interaction networks and how meta-communities may be constructed.

Squeezed between the land and the sea, coastal ecosystems are at the forefront of climate change. This chapter identifies climate change as a multiple stressor and cumulative effects problem associated with elevated temperature, increased frequency of extreme events, increased storms, ocean acidification and sea level rise, considering how these are likely to interact to affect ecosystem structure and functions and can be an important driver of tipping points. Mitigation measures for some of the effects in coastal ecosystems are discussed to help identify the importance of working with both stressors and ecosystem response to find solutions to climate impacts.

This chapter deals with the challenge we all face of translating ideas into the design of empirical research in soft-sediment habitats. It addresses the issues of study design and the inferences that can be drawn from different kinds of studies. Spatial and temporal scale is a critical issue in study design and the interpretation of results and the chapter introduces various elements of scale and how they can help you design rigorous and meaningful experiments. It focusses on the development of flow charts to help guide decisions needed to design field studies and the benefits of integrating experiments and surveys to improve mechanistic understanding and generality.

This chapter highlights the questions to ask of data collection methods and statistical analyses before you plunge into their use. It discusses data collection methods within the context of study design, focussing on the resolution and size (in area or time) that methods collect over. The methods covered are those that help explain patterns and processes produced by plants and animals interacting with the sediment and the water column. Similarly, statistical analyses that increase the interpretation of data and allow understanding of interacting processes are highlighted. The need to balance information, replication and costs associated with statistical power is also discussed. As this chapter provides a brief overview only on subjects that have been the subjects of entire books, it also contains references to more extensive coverage.

This chapter describes various aspects of how we can define ecosystem function and situations ecosystem function in a continuum from ecosystem processes to services. Illustrating that functions are about connections, the chapter uses examples of productivity, organic matter decomposition, ecosystem metabolism, habitat creation and foodwebs. Changes in the contributions of function to ecosystem dynamics are considered. Sedimentary ecosystems are multifunctional, requiring the development of new methods to assess this aspect of sediments and trait-based approaches are discussed. The role of ecosystem functions in underpinning ecosystem services is described to ensure that valuation and mapping exercises do not lose sight of the foundational role of ecosystem functions.

This chapter looks at the links between biodiversity and ecosystem function in soft sediments to help understand the implications of biodiversity loss on ecosystem services. The chapter contains a focus on the challenges in developing real-world tests of biodiversity–ecosystem function (BEF) relationships. The various forms of BEF relationships, their implications and the different elements of biodiversity that link to function are described. Given the multiple functions that occur in soft-sediment ecosystems, this has important implications for the assessment and implications of BEF relationships and functional performance in the up-scaling of BEF relationships. The role of BEF in underpinning many ecosystem services and the interconnections in biodiversity and ecosystem service relationships close out the chapter.

This chapter introduces the roles of sediment properties and hydrodynamic conditions in influencing soft-sediment communities. It identifies environmental factors that are commonly used to characterise soft-sediment habitats and used to tease out the role of habitat variation from other factors that influence populations and communities. The differences between cohesive and non-cohesive sediments that profoundly influence ecosystem functions are described. Hydrodynamics particularly at the sediment–water interface are introduced as a critical factor affecting many ecosystem processes. The chapter introduces the differences in laminar and turbulent flows. Coastal soft sediments in particular are places of high organic matter remineralisation and thus critical for the recycling of primary nutrients and primary production, particularly by microphytobenthos. These factors underpin the important role of marine sediments in biogeochemistry and earth system processes.

This chapter explores the interactions of plants and animals with their immediate sedimentary environment. Plants and animals fundamentally change the physical and chemical characteristics of their sedimentary environment. The changes they effect are dependent on their size, living position, feeding mode and mobility. The types of changes are discussed as well as the resultant ability of plants and animals to actually create seafloor habitats and contribute to sediment heterogeneity at both small and large scales. Seafloor habitats are therefore best defined by a mix of physical and biology rather than physical descriptors alone. But the differences between how different animals feed and move and their ability to create structures such as tubes and burrows that influence the flows of oxygen and porewater within the sediments and across the sediment–water interface mean that there are not only a variety of vegetated seafloor habitats but a variety of non-vegetated ones.

This chapter provides insight into the biodiversity of soft sediments, and how it can be measured using a range of univariate, bivariate and multivariate techniques. It highlights that biodiversity can be described across a range of organisational scales and includes the extension of diversity to cover habitats, behavioural characteristics (biological traits) and functional traits. Scale is an important characterisation of biodiversity and the chapter discusses scale both in its effect on the measurement of biodiversity and also for how it links the components of α‎-, β‎- and γ‎-diversity. These linkages are crucial to help us understand the roles of heterogeneity, species turnover and the ecological connections between local species richness and regional species pools. Most species are rare and thus any description of biodiversity would not be complete without consideration of rarity and its contribution to community structure and dynamics.

Ecologists have long acknowledged the importance of context dependency related to position along spatial gradients. It is also acknowledged that broad-scale climate patterns can directly and indirectly alter population dynamics. What is not often addressed is whether climate patterns such as the Southern Oscillation interact with population-level temporal patterns and affect the ability of time-series data, such as long-term state of the environment monitoring programmes, to detect change. Monitoring design criteria generally focus on number of data points, sampling frequency and duration, often derived from previous information on species seasonal and multi-year temporal patterns. Our study questioned whether the timing of any changes relative to Southern Oscillation, interacting with species populations dynamics, would also be important. We imposed a series of simulated reductions on macrofaunal abundance data collected regularly over 29 years from two sites, using species selected for observed differences in temporal dynamics. We hypothesized that (1) high within-year sampling frequency would increase detection ability for species with repeatable seasonality cycles and (2) timing of the reduction in abundance relative to the Southern Oscillation was only likely to affect detection ability for long-lived species with multi-year cyclic patterns in abundance. However, regardless of species population dynamics, we found both within-year sampling frequency and the timing of the imposed reduction relative to the Southern Oscillation Index affected detection ability. The latter result, while apparently demonstrating a confounding influence on monitoring, offers the opportunity to improve our ability to detect and interpret analyses of monitoring data, and thus our ability to make recommendations to managers.

© Copyright © 2020 Hope, Hewitt, Pilditch, Savage and Thrush. Benthic diatoms are a high-quality food resource providing essential fatty acids to benthic grazers. Different stressors may alter the proportion of diatoms and other microalgae and thus can affect the quality as well as quantity of food available to benthic consumers. Microphytobenthos (MPB) lipid biomarkers were assessed in a field experiment to elucidate changes to the biosynthesis of fatty acids (FA) under nitrogen (N) enrichment (three levels) at eight intertidal sites that spanned a turbidity gradient. Influences on the flow of carbon and energy were determined using FA biomarkers of a functionally important deposit-feeding tellinid bivalve (Macomona liliana). Site-specific effects of N enrichment were detected in MPB quantity and quality measurements. Enrichment generally increased MPB biomass (chl a) across all sites, while the proportion of diatom associated fatty acid biomarkers was more variable at some sites. Analysis of sediment FA biomarkers and environmental variables suggested that changes to the microbial community composition and quality were related to water clarity and mud content of the bed. The ability of the MPB to utilize the increased nitrogen, as indicated by the resource use efficiency index, was also important. Despite the increase in MPB biomass, lipid reserves in the tissue of M. liliana, a primary consumer of MPB, were reduced (by up to 6 orders of magnitude) in medium and high N addition plots compared to control plots. Further, the nutritional quality of the bivalves to higher trophic levels [indicated by a lower ratio of essential FAs (ω3:ω6)] was reduced in high treatment plots compared to control plots suggesting the bivalves were adversely affected by nutrient enrichment but not due to a reduction in food availability. This study suggests anthropogenic nutrient enrichment and turbidity may indirectly alter the structure and function of the benthic food web, in terms of carbon flow and ecosystem productivity. This may indirectly change the interactions between MPB and key bivalves as suspended sediment concentrations and nutrient enrichment continue to increase globally. This has implications for various ecosystem functions that are mediated by these interactions, such as nutrient cycling as well as primary and secondary production.

Analysis of the biological traits (e.g., feeding mode and size) that control how organisms interact with their environment has been used to identify environmental drivers of, or impacts on, species and to explain the importance of biodiversity loss. Biological trait analysis (BTA) could also be used within risk-assessment frameworks or in conservation planning if one understands the groups of traits that predict the sensitivity of habitats or communities to specific human activities. Deriving sensitivities from BTA should extend sensitivity predictions to a variety of habitats, especially those in which it would be difficult to conduct experiments (e.g., due to depth or risk to human life) and to scales beyond the norm of most experiments. We used data on epibenthos, collected via video along transects at 27 sites in a relatively pristine region of the seafloor, to determine scales of natural spatial variability of derived sensitivities and the degree to which predictions of sensitivity differed among 3 stressors (extraction of species, sedimentation, and suspended sediments) or were affected by underlying community compositions. We used 3 metrics (weighted abundance, abundance of highly sensitive species, and number of highly sensitive species) to derive sensitivity to these stressors and simulated the ability of these metrics to detect a range of stressor intensities. Regardless of spatial patterns of sensitivities across the sampled area, BTA distinguished differences in sensitivity to different stressors. The BTA also successfully separated differences in community composition from differences in sensitivity to stressors. Conversely, the 3 metrics differed widely in their ability to detect simulated impacts and likely reflect underlying ecological processes, suggesting that use of multiple metrics would be informative for spatial planning and allocating conservation priorities. Our results suggest BTA could be used as a first step in strategic prioritization of protected areas and as an underlying layer for spatial planning.

Cumulative effects in the marine environment increase the risk of environmental, economic or social collapse because the combined effects of new and existing marine industries, climate change and other stressors are often not accounted for in the determination of environmental capacity. Ecosystem-based management and the development of tools that translate complex social-ecological processes into dynamic, adaptable management strategies are needed to avoid these pitfalls. Previous work has highlighted disconnects between how cumulative effects are interpreted and assessed by science agencies, funding agencies, and management agencies, but has largely missed how investors are interpreting them. These social-ecological boundary and threshold issues illuminate the pivotal challenge of institutional change and agency behaviors that are needed to address cumulative effects. Using scenario planning techniques, a team of researchers from the Sustainable Seas National Science Challenge in Aotearoa New Zealand engaged key decision makers and stakeholders in creative thinking and constructive conversation aimed at bridging some of these institutional and behavioral disconnects. A range of different strategies regarding how to address cumulative effects were proposed by the assembled participants, but the need for collaborative networks that enable collective thought and action across boundaries was emphasized throughout the day. This paper explores the themes that emerged and some of the barriers that must be addressed to facilitate bold action on the topic of cumulative effects.

Seascapes contain a mosaic of ecosystem types, including ‘small natural features’ that support a diverse fauna and flora, and provide ecosystem services disproportionate to their size. These include tropical coral reefs, seagrass meadows, rhodolith beds, kelp and mangrove forests as well as deep-sea coral reefs, sponge gardens and hydrothermal vents. The contributions of coral reefs, mangrove forests and seagrass meadows are well recognised as important components of tropical marine seascapes. In temperate regions, hotspots of primary productivity such as kelp forests, and vegetation-based ecosystems found at coastal margins play significant roles in nutrient and sediment trapping and coastal protection. Biogenic features in coastal regions can also play important roles, including shellfish reefs, sponge gardens and macroalgal mats that provide physical structure within soft sediment ecosystems. Similar biogenic features are found in the deep sea, which often occur associated with seamounts, canyon features, cold seeps and hydrothermal vents. Many marine small natural features are globally threatened as they are found at the interface with human-influenced landscapes (coastal ecosystems) or are the focus of resource exploitation (e.g., trawling for fish associated with seamounts and canyons). Challenges in management are, however, consistent across depths, and highlight the restricted spatial extent of such features, and the limited information typically available on their distributions, and the ecosystem services they provide. Numerous strategies can be utilized to sustainably manage, protect, create and restore these marine small natural features and their associated biodiversity.

Scale has a profound influence on how we conduct ecological studies, interpret results and understand the links between processes operating at different rates. All of these factors profoundly influence our ability to predict responses to change. The ecological patterns and variability we observe range from millimetres to across ocean basins and from seconds to the expanse of evolutionary history. Patterns apparent at one scale can collapse to noise when viewed from other scales, indicating that perceptions of the importance of different processes vary in a scale-dependent manner. Moreover, rather than the environment simply providing an arena within which organisms are born grow and die, many organisms interact with the environment, altering it for both for themselves and for other species. Because of these factors, studying ecological systems is far from simple and scale needs to be considered in study design and analysis. Key concepts: The pattern you see depends on the scale at which you study it. Threats from human activities occur at varying scales, from small point sources to large diffuse threats and changes in disturbance regimes across landscapes. How organisms interact with the environment depends on how they perceive it and how patchy it is. How an organism moves and how far it can move is crucial to how an organism perceives and responds to their environment. Many organisms can alter their environment, both for themselves and for other species. Because most processes are scale-dependent, studies must explicitly consider scale in their design. Understanding both the scale of threats and the scale over which species live are essential for successful management and conservation. Keywords: scale; mobility; metapopulations; study design; conservation; protected area networks

New Zealand cockles ( Austrovenus stutchburyi ) are ecologically important, intertidal bivalves that have been shown to influence nutrient cycles and the productivity of microphytobenthos on sandflats. Here, we investigated the potential for cockles to impact the productivity of seagrass, Zostera muelleri , and examined interactions between these habitat-defining species where they co-occur. We sampled bivalve densities and sizes, sediment properties, and seagrass shoot densities across the boundaries of two seagrass patches on an intertidal sandflat in northern New Zealand, and measured dissolved oxygen and nutrient fluxes in light and dark benthic incubation chambers in conjunction with a 0–97% gradient in seagrass cover. Although gross primary production (GPP, μmol O 2 m −2 h −1 ) increased predictably with the cover of live seagrass, the density of cockles and sediment properties also contributed directly and indirectly. Seagrass cover was positively correlated with cockle density (ranging from 225 to 1350 individuals per m 2 ), sediment mud percentage (0.5–9.5%), and organic matter content (0.5–2.2%), all of which can affect the efflux of ammonium (readily utilisable inorganic nitrogen) from sediments. Moreover, the cover of green seagrass blades plateaued (never exceeded 70%) in the areas of highest total seagrass cover, adding complexity to cockle-seagrass interactions and contributing to a unimodal cockle-GPP relationship.

The Waitematā Harbour is a drowned river valley in the south-west of the Hauraki Gulf, on the north east of New Zealand’s North Island. The central business district for the city of Auckland is situated on the southern shore of the central Waitematā Harbour and is New Zealand’s largest and fastest growing city. The Waitematā Harbour hosts a major international port, New Zealand’s primary naval base and international cruise terminal, as well as a large and committed community of recreational users. In comparison with the marine ecosystems surrounding many of the world’s coastal cities, the Waitematā Harbour and the Hauraki Gulf have experienced a relatively short period of human occupation. Nonetheless, rapid and widespread changes have occurred within these ecosystems. Habitat loss and declines in biodiversity as well as impacts on human activities such as safe swimming and recreational harvesting have motivated several conservation and restoration initiatives. Here, we review the natural and social context of the Waitematā Harbour and Hauraki Gulf, and summarise some of the pressures the region faces. Last, we present three case studies highlighting current participatory initiatives aimed at ensuring more sustainable management of the region’s marine ecosystems. The Waitematā Harbour and Hauraki Gulf have provided considerable ecological, social and economic wealth for the people of Auckland; accordingly, conserving these ecosystems and preserving future prosperity should be a collective priority for all sectors of society.