Climatic, oceanic, freshwater, and local environmental drivers of New Zealand estuarine macroinvertebrates.

Understanding the responses of organisms to different environmental drivers is critical for improving ecosystem management and conservation. Estuarine ecosystems are under pressure from multiple anthropogenic stressors (e.g. increasing sediment and nutrient loads, pollution, climate change) that are affecting the functions and services these ecosystems provide. Here, we used long-term estuarine benthic invertebrate monitoring data (∼30 year time-series) to evaluate the responses of macrobenthic invertebrate communities and indicator species to climatic, oceanic, freshwater, and local environmental drivers in New Zealand estuaries. We aimed to improve our ability to predict ecosystem change and understand the effects of multiple environment drivers on benthic communities. Our analyses showed that the abundance and richness of macrobenthic fauna and four indicator taxa (bivalves known to have differing tolerances to sediment mud content: Austrovenus stutchburyi, Macomona liliana, Theora lubrica, and Arthritica bifurca) responded to unique combinations of multiple environmental drivers across sites and times. Macrobenthic responses were highly mixed (i.e., positive and negative) and site-dependent. We also show that responses of macrobenthic fauna were lagged and most strongly related to climatic and oceanic drivers. The way the macrobenthos responded has implications for predicting and understanding the ecological consequences of a rapidly changing environment and how we conserve and manage coastal ecosystems.

Toward a network perspective in coastal ecosystem management.

Environmental management in coastal ecosystems has been challenged by the complex cumulative effects that occur when many small issues result in large ecological shifts. Current environmental management of these spaces focuses on identifying and limiting problematic stressors via a series of assessment techniques. Whilst there is a strong desire among managers to consider complexity in ecological responses to cumulative effects, current approaches for assessing risk focus on breaking down the issues into multiple cause and effect relationships. However, uncertainty arises when data and information for a place are limited, as is commonly the case, and this creates decision paralysis while more information is generated. Here, we discuss how ecological understanding of network interactions in coastal marine ecosystems can be used as a lens to bring together multiple lines of evidence and create actions. We list and describe four characteristics of marine ecosystem interaction networks including the possibility for; 1) indirect effects, 2) effects that emerge as stressor magnitude increases the number of network components implicated, 3) network interactions that amplify these indirect effects, and 4) feedbacks that reinforce or stabilise against indirect effects. We then link these four characteristics to three case studies of common coastal environmental issues to demonstrate how a general understanding of ecological interaction networks can enhance priorities for stressor management that can be applied even when specific data is limited.

Implications for the conservation of deep-water corals in the face of multiple stressors: A case study from the New Zealand region.

The waters around New Zealand are a global hotspot of biodiversity for deep-water corals; approximately one sixth of the known deep-water coral species of the world have been recorded in the region. Deep-water corals are vulnerable to climate-related stressors and from the damaging effects of commercial fisheries. Current protection measures do not account for the vulnerability of deep-water corals to future climatic conditions, which are predicted to alter the distribution of suitable habitat for them. Using recently developed habitat suitability models for 12 taxa of deep-water corals fitted to current and future seafloor environmental conditions (under different future climatic conditions: SSP2 - 4.5 and SSP3 - 7.0) we explore possible levels of spatial protection using the decision-support tool Zonation. Specifically, we assess the impact of bottom trawling on predictions of current distributions of deep-water corals, and then assess the effectiveness of possible protection for deep-water corals, while accounting for habitat refugia under future climatic conditions. The cumulative impact of bottom trawling was predicted to impact all taxa, but particularly the reef-forming corals. Core areas of suitable habitat were predicted to decrease under future climatic conditions for many taxa. We found that designing protection using current day predictions alone, having accounted for the impacts of historic fishing impacts, was unlikely to provide adequate conservation for deep water-corals under future climate change. Accounting for future distributions in spatial planning identified areas which may provide climate refugia whilst still providing efficient protection for current distributions. These gains in conservation value may be particularly important given the predicted reduction in suitable habitat for deep-water corals due to bottom fishing and climate change. Finally, the possible impact that protection measures may have on deep-water fisheries was assessed using a measure of current fishing value (kg km-2 fish) and future fishing value (predicted under future climate change scenarios).

NZTD - The New Zealand Trait Database for shallow-water marine benthic invertebrates.

Macrobenthic traits, for example feeding mode, life history, morphology, are increasingly used for determining responses of macrobenthic fauna to environmental change and influences on ecosystem functioning. Yet, trait information is scarce or non-existent in several parts of the world, such as New Zealand. This deficit makes collecting trait data a difficult and time-consuming task, limiting its potential use in trait-based assessments. Here, we present the New Zealand Trait Database (NZTD) for marine benthic invertebrates, the first comprehensive assessment of macrobenthic traits in New Zealand. The NZTD provides trait information for more than 700 macrobenthic taxa, categorised by 18 traits and 77 trait modalities. The NZTD includes five freely downloadable datasets, (1) the macrobenthic trait dataset, with outcomes from a fuzzy coding procedure, (2) the trait source information, (3) the references by taxa, (4) the full references list, and (5) the full taxa list used in the NZTD. Establishing the NZTD closes the trait knowledge gap in New Zealand and facilitates future research applying trait-based approaches to New Zealand's coastal macrofauna.

Ecological network analysis of traits reveals variable response capacity to stress.

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.

Assessing ecological health in areas with limited data by using biological traits.

A multitude of biotic indices that represent environmental status have been developed over the past decades making status comparisons difficult. However, transferring an existing index to a new region can be problematic due to differing stressors, ecosystem components and lack of knowledge on regional species sensitivities. Here we assess whether calculating species sensitivities to specific stressors based on biological traits offers a solution. We use biological traits of macrofaunal species to assess sensitivity to suspended sediment concentrations and calculated the Benthic Quality Index (BQI) at 47 sites across a suspended sediment gradient. This trait-based modification of the BQI was well correlated (0.82) to suspended sediment. Problems previously highlighted, relating to trait plasticity and differential weightings of indifferent and beneficial species, were investigated but did not strongly affect results. A trait-based approach has the additional benefit that the data could be easily converted to evaluate ecosystem function.

Biological traits approaches in benthic marine ecology: Dead ends and new paths.

Biological traits analysis (BTA) links community structure to both ecological functions and response to environmental drivers through species' attributes. In consequence, it has become a popular approach in marine benthic studies. However, BTA will reach a dead end if the scientific community does not acknowledge its current shortcomings and limitations: (a) uncertainties related to data origins and a lack of standardized reporting of trait information; (b) knowledge gaps on the role of multiple interacting traits on driving the organisms' responses to environmental variability; (c) knowledge gaps regarding the mechanistic links between traits and functions; (d) a weak focus on the spatial and temporal variability that is inherent to the trait expression of species; and, last but not least, (e) the large reliance on expert knowledge due to an enormous knowledge gap on the basic ecology of many benthic species. BTA will only reach its full potential if the scientific community is able to standardize and unify the reporting and storage of traits data and reconsider the importance of baseline observational and experimental studies to fill knowledge gaps on the mechanistic links between biological traits, functions, and environmental variability. This challenge could be assisted by embracing new technological advances in marine monitoring, such as underwater camera technology and artificial intelligence, and making use of advanced statistical approaches that consider the interactive nature and spatio-temporal variability of biological systems. The scientific community has to abandon some dead ends and explore new paths that will improve our understanding of individual species, traits, and the functioning of benthic ecosystems.

The impact of cumulative stressor effects on uncertainty and ecological risk.

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.

Deep seabed mining and communities: A transdisciplinary approach to ecological risk assessment in the South Pacific.

Deep-sea mineral extraction is a fledgling industry whose guiding principles, legislation, protocols, and regulations are still evolving. Responsible management of the industry is difficult when it is not clearly understood what biological and environmental diversity or ecosystem services may be at risk. But the industry's infancy provides an opportunity to address this challenge by stakeholder-led development and implementation of a multidisciplinary risk assessment framework. This article aims to present the findings of a workshop held in New Zealand that hosted stakeholders from a broad range of interests and regions in the South Pacific associated with the deep-sea mineral activity. The outputs provide stakeholder-informed ecological risk assessment approaches for deep-sea mining activities, identifying tools and techniques to improve the relevance of risk assessment of deep seabed mining projects to communities in the South Pacific. Discussions highlighted the importance of trust or respect among stakeholders, valuing the "life force" of the ocean, the importance of scientific data, and the complications associated with defining acceptable change. This research highlighted the need for a holistic transdisciplinary approach that connects science, management, industry, and community, an approach most likely to provide a "social license" to operate. There is also a need to revise traditional risk assessment methods to make them more relevant to stakeholders. The development of ecotoxicological tools and approaches is an example of how existing practices could be improved to better support deep-sea mineral management. A case study is provided that highlights the current challenges within the legislative framework of New Zealand. Integr Environ Assess Manag 2022;18:664-673. © 2021 SETAC.

Beyond the single index: Investigating ecological mechanisms underpinning ecosystem multifunctionality with network analysis.

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.

Identifying "vital attributes" for assessing disturbance-recovery potential of seafloor communities.

Despite a long history of disturbance-recovery research, we still lack a generalizable understanding of the attributes that drive community recovery potential in seafloor ecosystems. Marine soft-sediment ecosystems encompass a range of heterogeneity from simple low-diversity habitats with limited biogenic structure, to species-rich systems with complex biogenic habitat structure. These differences in biological heterogeneity are a product of natural conditions and disturbance regimes. To search for unifying attributes, we explore whether a set of simple traits can characterize community disturbance-recovery potential using seafloor patch-disturbance experiments conducted in two different soft-sediment landscapes. The two landscapes represent two ends of a spectrum of landscape biotic heterogeneity in order to consider multi-scale disturbance-recovery processes. We consider traits at different levels of biological organization, from the biological traits of individual species, to the traits of species at the landscape scale associated with their occurrence across the landscape and their ability to be dominant. We show that in a biotically heterogeneous landscape (Kawau Bay, New Zealand), seafloor community recovery is stochastic, there is high species turnover, and the landscape-scale traits are good predictors of recovery. In contrast, in a biotically homogeneous landscape (Baltic Sea), the options for recovery are constrained, the recovery pathway is thus more deterministic and the scale of recovery traits important for determining recovery switches to the individual species biological traits within the disturbed patch. Our results imply that these simple, yet sophisticated, traits can be effectively used to characterize community recovery potential and highlight the role of landscapes in providing resilience to patch-scale disturbances.

Sampling frequency, duration and the Southern Oscillation influence the ability of long-term studies to detect sudden change.

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.

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.

Does the use of biological traits predict a smooth landscape of ecosystem functioning?

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.

Linking changes in species-trait relationships and ecosystem function using a network analysis of traits.

A major challenge in ecology and environmental management is linking changes in community composition to ecosystem functions. We developed the network analysis of traits (NAT) to show changes in community network structure based on the changes in the composition and connectivity between clusters of species that share traits that imply shifts in functional diversity. We tested the application of NAT on a 113 species found on an intertidal sandflat that was subject to experimental nitrogen addition (control [0 g N/m2 ], medium [150 g N/m2 ], and high [600 g N/m2 ]). This allowed us to directly link mechanistic changes in community composition and function with the trait-space network patterns revealed by NAT. We demonstrate that under medium (150 g N/m2 ) N treatment, functional diversity remained consistent, whereas increasing disturbance to high (600 g N/m2 ) N treatment affected the species-trait network structure and caused merging of functional clusters implying a loss of functional trait diversity.

Multiple stressor effects on coral reef ecosystems.

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.

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.

Assessing sensitivities of marine areas to stressors based on biological traits.

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.

The multiple roles of ß-diversity help untangle community assembly processes affecting recovery of temperate rocky shores.

Metacommunity theory highlights the potential of ß-diversity as a useful link to empirical research, especially in diverse systems where species exhibit a range of stage-dependent dispersal characteristics. To investigate the importance of different components and scales of ß-diversity in community assembly, we conducted a large-scale disturbance experiment and compared relative recovery across multiple sites and among plots within sites on the rocky shore. Six sites were spread along 80 km of coastline and, at each site, five plots were established, matching disturbed and undisturbed quadrats. Recovery was not complete at any of the sites after 1 year for either epibenthos (mostly composed of macroalgae and, locally, mussels) or infauna. Significant differences in recovery among sites were observed for epibenthos but not for infauna, suggesting that different community assembly processes were operating. This was supported by epibenthos in the recovering plots having higher species turnover than in undisturbed sediment, and recovery well predicted by local diversity, while infaunal recovery was strongly influenced by the epibenthic community's habitat complexity. However, infaunal community recovery did not simply track formation of habitat by recovering epibenthos, but appeared to be overlain by within-site and among-site aspects of infaunal ß-diversity. These results suggest that documenting changes in the large plants and animals alone will be a poor surrogate for rocky shore community assembly processes. No role for ecological connectivity (negative effect of among-site ß-diversity) in driving recovery was observed, suggesting a low risk of effects from multiple disturbances propagating along the coast, but a limited resilience at the site scale to large-scale disturbances such as landslides or oil spills.

Translating Ecological Integrity terms into operational language to inform societies.

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.