Global climate change will undoubtedly be a pressure on coastal marine ecosystems, not only affec... more Global climate change will undoubtedly be a pressure on coastal marine ecosystems, not only affecting 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 sp...
Journal of Experimental Marine Biology and Ecology, 2015
Increasing population pressure, urbanization of the coastal zone and nutrient and sediment run-of... more Increasing population pressure, urbanization of the coastal zone and nutrient and sediment run-off from agriculture and forestry has increased the number of large-scale and chronic impacts affecting coastal and estuarine systems. The need to assess cumulative impacts is a major motivation for the current desire of managers and ecologists to define ecosystem “health” and “stress”. A number of univariate metrics have been proposed to monitor health, including indicator species, indicator ratios and diversity or contaminant metrics. Alternatively, multivariate methods can be used to test for changes in community structure due to stress. In this study we developed Multivariate Models using statistical ordination techniques to identify key stressors affecting the ‘health’ of estuarine macrofaunal communities. Macrofaunal and associated environmental samples were collected across 75 sites from within Tauranga Harbour, a large estuary located on New Zealand’s North Island. The harbour receives discharges from urbanized, industrial, agricultural and horticultural catchments. Distance-based linear modelling identified sediments, nutrients and heavy metals as key ‘stressors’ affecting the ecology of the harbour. Therefore, three multivariate models were developed based on the variability in community composition using canonical analysis of principal coordinates (CAP). The multivariate models were found to be more sensitive to changing environmental health than simple univariate measures (abundance, species richness, evenness and Shannon-Wiener diversity) along an anthropogenic stress gradient. This multivariate approach can be used as a management or monitoring tool where sites are repeatedly sampled over time and tracked to determine whether the communities are moving towards a more healthy or unhealthy state. Ultimately, such statistical models provide a tool to forecast the distribution and abundance of species associated with habitat change and should enable long term degradative change from multiple disturbances to be assessed.
ABSTRACT EXECUTIVE SUMMARY This report summarises the results of biological and physical data col... more ABSTRACT EXECUTIVE SUMMARY This report summarises the results of biological and physical data collected from a broad scale intertidal survey of Tauranga Harbour conducted between December 2011 and February 2012. The survey was designed to understand more fully the role of various anthropogenic stressors on the ecology of the harbour. The research was conducted as part of the Manaaki Taha Moana (MTM) programme. The wider research project aims to restore and enhance coastal ecosystems and their services of importance to iwi/hapū, by working with iwi to improve knowledge of these ecosystems and the degradation processes that affect them. In this report we assess the health of macrofaunal benthic communities (bottom-dwelling animals) as well as trends in sediments, nutrients and contaminants. The results indicate that the sites identified as most impacted were generally located in the upper reaches of estuaries in some of the locations least exposed to wind, waves and currents. In addition, the biological community composition characterizing sites with different sediment textures, nutrient and contaminant loadings were found to vary. Sediments within Tauranga Harbour were predominantly sandy with the percentage of mud within a similar range as measured for other New Zealand estuaries. The exceptions included Te Puna Estuary and Apata Estuary, which experience higher rates of sedimentation. Heavy metal contamination in sediments is often highly correlated with the percentage of mud content due to the adherence of chemicals to fine sediments and/or organic content. It is, therefore, not surprising that heavy metal concentrations were also highest in the depositional inner areas of the harbour, such as Te Puna Estuary. The heavy metal contaminant levels within Tauranga were well below relevant guideline thresholds and lower than concentrations measured in many other estuaries in New Zealand and overseas. Although the three metals recorded were found to be highly correlated, zinc levels tended to be closer to guideline thresholds for possible biological effects. Sediment nutrient concentrations in the harbour tended to decline with distance from the inner harbour and associated rivers. Te Puna Estuary showed comparatively high nitrogen and phosphorus loadings. Comparison of sediment nutrient concentrations with other New Zealand estuaries indicates that the Tauranga Harbour sits within a range typical for slightly to moderately enriched estuaries. Although total phosphorous was low compared with other estuaries, total N:P ratios suggest Tauranga Harbour is still limited by nitrogen. We developed a BHM using statistical ordination techniques to identify key stressors affecting the ‘health’ of macrofaunal communities. Sediments, nutrients and heavy metals were identified as key ‘stressors’, i.e. variables affecting the ecology of the harbour. Therefore, three multivariate models were developed based on the variability in community composition using canonical analysis of principal coordinates (CAP). The ecological assemblages generally reflected gradients of stress or pollution very well. However, the CAP models for sediments and contaminants performed best. In general, the multivariate models were found to be more sensitive to changing environmental health than simple univariate measures (abundance, species diversity, evenness and Shannon-Wiener diversity). This finding has also been reported in the literature where univariate measures based on abundance and diversity were only able to detect significant differences between the most and least disturbed sites, but were not able to differentiate between smaller relative changes in environmental health. Hence univariate measures were less sensitive to smaller degradative changes in community composition. For Tauranga Harbour, ordination models based on community composition appear to be a more sensitive measure of ‘health’ along an ecological gradient and should enable long term degradative change from multiple disturbances to be assessed. This BHM approach can be used as a management or monitoring tool where sites are repeatedly sampled over time and tracked to determine whether the communities are moving towards a more healthy or unhealthy state. The key species at ‘healthy’ and ‘impacted’ sites as determined from the CAP models were also identified. Species at ‘impacted’ sites can be considered to be tolerant to the stressor (i.e. sediment, nutrients or contaminants), while species with high abundances at only ‘healthy’ sites are sensitive to increasing stressors. We also developed density-dependent models for key species identified in the ordination models and culturally important shellfish species. For shellfish, the results suggest the response curves to increasing stress for sedimentation, nutrients and contaminants were either negative or polynomial. A negative relationship means that as the stressor increases the abundance of shellfish decreases. A polynomial…
Global climate change will undoubtedly be a pressure on coastal marine ecosystems, not only affec... more Global climate change will undoubtedly be a pressure on coastal marine ecosystems, not only affecting 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 sp...
Journal of Experimental Marine Biology and Ecology, 2015
Increasing population pressure, urbanization of the coastal zone and nutrient and sediment run-of... more Increasing population pressure, urbanization of the coastal zone and nutrient and sediment run-off from agriculture and forestry has increased the number of large-scale and chronic impacts affecting coastal and estuarine systems. The need to assess cumulative impacts is a major motivation for the current desire of managers and ecologists to define ecosystem “health” and “stress”. A number of univariate metrics have been proposed to monitor health, including indicator species, indicator ratios and diversity or contaminant metrics. Alternatively, multivariate methods can be used to test for changes in community structure due to stress. In this study we developed Multivariate Models using statistical ordination techniques to identify key stressors affecting the ‘health’ of estuarine macrofaunal communities. Macrofaunal and associated environmental samples were collected across 75 sites from within Tauranga Harbour, a large estuary located on New Zealand’s North Island. The harbour receives discharges from urbanized, industrial, agricultural and horticultural catchments. Distance-based linear modelling identified sediments, nutrients and heavy metals as key ‘stressors’ affecting the ecology of the harbour. Therefore, three multivariate models were developed based on the variability in community composition using canonical analysis of principal coordinates (CAP). The multivariate models were found to be more sensitive to changing environmental health than simple univariate measures (abundance, species richness, evenness and Shannon-Wiener diversity) along an anthropogenic stress gradient. This multivariate approach can be used as a management or monitoring tool where sites are repeatedly sampled over time and tracked to determine whether the communities are moving towards a more healthy or unhealthy state. Ultimately, such statistical models provide a tool to forecast the distribution and abundance of species associated with habitat change and should enable long term degradative change from multiple disturbances to be assessed.
ABSTRACT EXECUTIVE SUMMARY This report summarises the results of biological and physical data col... more ABSTRACT EXECUTIVE SUMMARY This report summarises the results of biological and physical data collected from a broad scale intertidal survey of Tauranga Harbour conducted between December 2011 and February 2012. The survey was designed to understand more fully the role of various anthropogenic stressors on the ecology of the harbour. The research was conducted as part of the Manaaki Taha Moana (MTM) programme. The wider research project aims to restore and enhance coastal ecosystems and their services of importance to iwi/hapū, by working with iwi to improve knowledge of these ecosystems and the degradation processes that affect them. In this report we assess the health of macrofaunal benthic communities (bottom-dwelling animals) as well as trends in sediments, nutrients and contaminants. The results indicate that the sites identified as most impacted were generally located in the upper reaches of estuaries in some of the locations least exposed to wind, waves and currents. In addition, the biological community composition characterizing sites with different sediment textures, nutrient and contaminant loadings were found to vary. Sediments within Tauranga Harbour were predominantly sandy with the percentage of mud within a similar range as measured for other New Zealand estuaries. The exceptions included Te Puna Estuary and Apata Estuary, which experience higher rates of sedimentation. Heavy metal contamination in sediments is often highly correlated with the percentage of mud content due to the adherence of chemicals to fine sediments and/or organic content. It is, therefore, not surprising that heavy metal concentrations were also highest in the depositional inner areas of the harbour, such as Te Puna Estuary. The heavy metal contaminant levels within Tauranga were well below relevant guideline thresholds and lower than concentrations measured in many other estuaries in New Zealand and overseas. Although the three metals recorded were found to be highly correlated, zinc levels tended to be closer to guideline thresholds for possible biological effects. Sediment nutrient concentrations in the harbour tended to decline with distance from the inner harbour and associated rivers. Te Puna Estuary showed comparatively high nitrogen and phosphorus loadings. Comparison of sediment nutrient concentrations with other New Zealand estuaries indicates that the Tauranga Harbour sits within a range typical for slightly to moderately enriched estuaries. Although total phosphorous was low compared with other estuaries, total N:P ratios suggest Tauranga Harbour is still limited by nitrogen. We developed a BHM using statistical ordination techniques to identify key stressors affecting the ‘health’ of macrofaunal communities. Sediments, nutrients and heavy metals were identified as key ‘stressors’, i.e. variables affecting the ecology of the harbour. Therefore, three multivariate models were developed based on the variability in community composition using canonical analysis of principal coordinates (CAP). The ecological assemblages generally reflected gradients of stress or pollution very well. However, the CAP models for sediments and contaminants performed best. In general, the multivariate models were found to be more sensitive to changing environmental health than simple univariate measures (abundance, species diversity, evenness and Shannon-Wiener diversity). This finding has also been reported in the literature where univariate measures based on abundance and diversity were only able to detect significant differences between the most and least disturbed sites, but were not able to differentiate between smaller relative changes in environmental health. Hence univariate measures were less sensitive to smaller degradative changes in community composition. For Tauranga Harbour, ordination models based on community composition appear to be a more sensitive measure of ‘health’ along an ecological gradient and should enable long term degradative change from multiple disturbances to be assessed. This BHM approach can be used as a management or monitoring tool where sites are repeatedly sampled over time and tracked to determine whether the communities are moving towards a more healthy or unhealthy state. The key species at ‘healthy’ and ‘impacted’ sites as determined from the CAP models were also identified. Species at ‘impacted’ sites can be considered to be tolerant to the stressor (i.e. sediment, nutrients or contaminants), while species with high abundances at only ‘healthy’ sites are sensitive to increasing stressors. We also developed density-dependent models for key species identified in the ordination models and culturally important shellfish species. For shellfish, the results suggest the response curves to increasing stress for sedimentation, nutrients and contaminants were either negative or polynomial. A negative relationship means that as the stressor increases the abundance of shellfish decreases. A polynomial…
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Papers by Judi Hewitt