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.

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).

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.

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.

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.

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.

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.

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.

Long-term environmental monitoring for assessment of change: measurement inconsistencies over time and potential solutions.

The importance of long-term environmental monitoring and research for detecting and understanding changes in ecosystems and human impacts on natural systems is widely acknowledged. Over the last decades, a number of critical components for successful long-term monitoring have been identified. One basic component is quality assurance/quality control protocols to ensure consistency and comparability of data. In Norway, the authorities require environmental monitoring of the impacts of the offshore petroleum industry on the Norwegian continental shelf, and in 1996, a large-scale regional environmental monitoring program was established. As a case study, we used a sub-set of data from this monitoring to explore concepts regarding best practices for long-term environmental monitoring. Specifically, we examined data from physical and chemical sediment samples and benthic macroinvertebrate assemblages from 11 stations from six sampling occasions during the period 1996-2011. Despite the established quality assessment and quality control protocols for this monitoring program, we identified several data challenges, such as missing values and outliers, discrepancies in variable and station names, changes in procedures without calibration, and different taxonomic resolution. Furthermore, we show that the use of different laboratories over time makes it difficult to draw conclusions with regard to some of the observed changes. We offer recommendations to facilitate comparison of data over time. We also present a new procedure to handle different taxonomic resolution, so valuable historical data is not discarded. These topics have a broader relevance and application than for our case study.

Changes in the location of biodiversity-ecosystem function hot spots across the seafloor landscape with increasing sediment nutrient loading.

Declining biodiversity and loss of ecosystem function threatens the ability of habitats to contribute ecosystem services. However, the form of the relationship between biodiversity and ecosystem function (BEF) and how relationships change with environmental change is poorly understood. This limits our ability to predict the consequences of biodiversity loss on ecosystem function, particularly in real-world marine ecosystems that are species rich, and where multiple ecosystem functions are represented by multiple indicators. We investigated spatial variation in BEF relationships across a 300 000 m2 intertidal sandflat by nesting experimental manipulations of sediment pore water nitrogen concentration into sites with contrasting macrobenthic community composition. Our results highlight the significance of many different elements of biodiversity associated with environmental characteristics, community structure, functional diversity, ecological traits or particular species (ecosystem engineers) to important functions of coastal marine sediments (benthic oxygen consumption, ammonium pore water concentrations and flux across the sediment-water interface). Using the BEF relationships developed from our experiment, we demonstrate patchiness across a landscape in functional performance and the potential for changes in the location of functional hot and cold spots with increasing nutrient loading that have important implications for mapping and predicating change in functionality and the concomitant delivery of ecosystem services.

Same pattern, different mechanism: Locking onto the role of key species in seafloor ecosystem process.

Seafloor biodiversity is a key mediator of ecosystem functioning, but its role is often excluded from global budgets or simplified to black boxes in models. New techniques allow quantification of the behavior of animals living below the sediment surface and assessment of the ecosystem consequences of complex interactions, yielding a better understanding of the role of seafloor animals in affecting key processes like primary productivity. Combining predictions based on natural history, behavior of key benthic species and environmental context allow assessment of differences in functioning and process, even when the measured ecosystem property in different systems is similar. Data from three sedimentary systems in New Zealand illustrate this. Analysis of the behaviors of the infaunal ecosystem engineers in each system revealed three very different mechanisms driving ecosystem function: density and excretion, sediment turnover and surface rugosity, and hydraulic activities and porewater bioadvection. Integrative metrics of ecosystem function in some cases differentiate among the systems (gross primary production) and in others do not (photosynthetic efficiency). Analyses based on behaviors and activities revealed important ecosystem functional differences and can dramatically improve our ability to model the impact of stressors on ecosystem and global processes.

The role of time and species identities in spatial patterns of species richness and conservation.

Many conservation actions are justified on the basis of managing biodiversity. Biodiversity, in terms of species richness, is largely the product of rare species. This is problematic because the intensity of sampling needed to characterize communities and patterns of rarity or to justify the use of surrogates has biased sampling in favor of space over time. However, environmental fluctuations interacting with community dynamics lead to temporal variations in where and when species occur, potentially affecting conservation planning by generating uncertainty about results of species distribution modeling (including range determinations), selection of surrogates for biodiversity, and the proportion of biodiversity composed of rare species. To have confidence in the evidence base for conservation actions, one must consider whether temporal replication is necessary to produce broad inferences. Using approximately 20 years of macrofaunal data from tidal flats in 2 harbors, we explored variation in the identity of rare, common, restricted range, and widespread species over time and space. Over time, rare taxa were more likely to increase in abundance or occurrence than to remain rare or disappear and to exhibit temporal patterns in their occurrence. Space-time congruency in ranges (i.e., spatially widespread taxa were also temporally widespread) was observed only where samples were collected across an environmental gradient. Fifteen percent of the taxa in both harbors changed over time from having spatially restricted ranges to having widespread ranges. Our findings suggest that rare species can provide stability against environmental change, because the majority of species were not random transients, but that selection of biodiversity surrogates requires temporal validation. Rarity needs to be considered both spatially and temporally, as species that occur randomly over time are likely to play a different role in ecosystem functioning than those exhibiting temporal structure (e.g., seasonality). Moreover, temporal structure offers the opportunity to place management and conservation activities within windows of maximum opportunity.

Multiple stressors, nonlinear effects and the implications of climate change impacts on marine coastal ecosystems.

Global climate change will undoubtedly be a pressure on coastal marine ecosystems, affecting not only species distributions and physiology but also ecosystem functioning. In the coastal zone, the environmental variables that may drive ecological responses to climate change include temperature, wave energy, upwelling events and freshwater inputs, and all act and interact at a variety of spatial and temporal scales. To date, we have a poor understanding of how climate-related environmental changes may affect coastal marine ecosystems or which environmental variables are likely to produce priority effects. Here we use time series data (17 years) of coastal benthic macrofauna to investigate responses to a range of climate-influenced variables including sea-surface temperature, southern oscillation indices (SOI, Z4), wind-wave exposure, freshwater inputs and rainfall. We investigate responses from the abundances of individual species to abundances of functional traits and test whether species that are near the edge of their tolerance to another stressor (in this case sedimentation) may exhibit stronger responses. The responses we observed were all nonlinear and some exhibited thresholds. While temperature was most frequently an important predictor, wave exposure and ENSO-related variables were also frequently important and most ecological variables responded to interactions between environmental variables. There were also indications that species sensitive to another stressor responded more strongly to weaker climate-related environmental change at the stressed site than the unstressed site. The observed interactions between climate variables, effects on key species or functional traits, and synergistic effects of additional anthropogenic stressors have important implications for understanding and predicting the ecological consequences of climate change to coastal ecosystems.

Detecting Subtle Shifts in Ecosystem Functioning in a Dynamic Estuarine Environment.

Identifying the effects of stressors before they impact ecosystem functioning can be challenging in dynamic, heterogeneous 'real-world' ecosystems. In aquatic systems, for example, reductions in water clarity can limit the light available for photosynthesis, with knock-on consequences for secondary consumers, though in naturally turbid wave-swept estuaries, detecting the effects of elevated turbidity can be difficult. The objective of this study was to investigate the effects of shading on ecosystem functions mediated by sandflat primary producers (microphytobenthos) and deep-dwelling surface-feeding macrofauna (Macomona liliana; Bivalvia, Veneroida, Tellinidae). Shade cloths (which reduced incident light intensity by ~80%) were deployed on an exposed, intertidal sandflat to experimentally stress the microphytobenthic community associated with the sediment surface. After 13 weeks, sediment properties, macrofauna and fluxes of oxygen and inorganic nutrients across the sediment-water interface were measured. A multivariate metric of ecosystem function (MF) was generated by combining flux-based response variables, and distance-based linear models were used to determine shifts in the drivers of ecosystem function between non-shaded and shaded plots. No significant differences in MF or in the constituent ecosystem function variables were detected between the shaded and non-shaded plots. However, shading reduced the total explained variation in MF (from 64% in non-shaded plots to 15% in shaded plots) and affected the relative influence of M. liliana and other explanatory variables on MF. This suggests that although shade stress may shift the drivers of ecosystem functioning (consistent with earlier investigations of shading effects on sandflat interaction networks), ecosystem functions appear to have a degree of resilience to those changes.