11 resultados para J11 - Demographic Trends and Forecasts

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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Differential phenological responses to climate among species are predicted to disrupt trophic interactions, but datasets to evaluate this are scarce. We compared phenological trends for species from 4 levels of a North Sea food web over 24 yr when sea surface temperature (SST) increased significantly. We found little consistency in phenological trends between adjacent trophic levels, no significant relationships with SST, and no significant pairwise correlations between predator and prey phenologies, suggesting that trophic mismatching is occurring. Finer resolution data on timing of peak energy demand (mid-chick-rearing) for 5 seabird species at a major North Sea colony were compared to modelled daily changes in length of 0-group (young of the year) lesser sandeels Ammodytes marinus. The date at which sandeels reached a given threshold length became significantly later during the study. Although the phenology of all the species except shags also became later, these changes were insufficient to keep pace with sandeel length, and thus mean length (and energy value) of 0-group sandeels at mid-chick-rearing showed net declines. The magnitude of declines in energy value varied among the seabirds, being more marked in species showing no phenological response (shag, 4.80 kJ) and in later breeding species feeding on larger sandeels (kittiwake, 2.46 kJ) where, due to the relationship between sandeel length and energy value being non-linear, small reductions in length result in relatively large reductions in energy. However, despite the decline in energy value of 0-group sandeels during chick-rearing, there was no evidence of any adverse effect on breeding success for any of the seabird species. Trophic mismatch appears to be prevalent within the North Sea pelagic food web, suggesting that ecosystem functioning may be disrupted.

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A comprehensive expert consultation was conducted in order to assess the status, trends and the most important drivers of change in the abundance and geographical distribution of kelp forests in European waters. This consultation included an on-line questionnaire, results from a workshop and data provided by a selected group of experts working on kelp forest mapping and eco-evolutionary research. Differences in status and trends according to geographical areas, species identity and small-scale variations within the same habitat where shown by assembling and mapping kelp distribution and trend data. Significant data gaps for some geographical regions, like the Mediterranean and the southern Iberian Peninsula, were also identified. The data used for this study confirmed a general trend with decreasing abundance of some native kelp species at their southern distributional range limits and increasing abundance in other parts of their distribution (Saccharina latissima and Saccorhiza polyschides). The expansion of the introduced species Undaria pinnatifida was also registered. Drivers of observed changes in kelp forests distribution and abundance were assessed using experts’ opinions. Multiple possible drivers were identified, including global warming, sea urchin grazing, harvesting, pollutionand fishing pressure, and their impact varied between geographical areas. Overall, the results highlight major threats for these ecosystems but also opportunities for conservation. Major requirements to ensure adequate protection of coastal kelp ecosystems along European coastlines are discussed, based on the local to regional gaps detected in the study.

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A comprehensive expert consultation was conducted in order to assess the status, trends and the most important drivers of change in the abundance and geographical distribution of kelp forests in European waters. This consultation included an on-line questionnaire, results from a workshop and data provided by a selected group of experts working on kelp forest mapping and eco-evolutionary research. Differences in status and trends according to geographical areas, species identity and small-scale variations within the same habitat where shown by assembling and mapping kelp distribution and trend data. Significant data gaps for some geographical regions, like the Mediterranean and the southern Iberian Peninsula, were also identified. The data used for this study confirmed a general trend with decreasing abundance of some native kelp species at their southern distributional range limits and increasing abundance in other parts of their distribution (Saccharina latissima and Saccorhiza polyschides). The expansion of the introduced species Undaria pinnatifida was also registered. Drivers of observed changes in kelp forests distribution and abundance were assessed using experts’ opinions. Multiple possible drivers were identified, including global warming, sea urchin grazing, harvesting, pollutionand fishing pressure, and their impact varied between geographical areas. Overall, the results highlight major threats for these ecosystems but also opportunities for conservation. Major requirements to ensure adequate protection of coastal kelp ecosystems along European coastlines are discussed, based on the local to regional gaps detected in the study.

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Trends in basking shark (Cetorhinus maximus) fishery catches off Achill Island, west Ireland between 1949 and 1975 were examined in relation to zooplankton (total copepod) abundance in four adjacent sea areas over a 27-year period. The numbers of basking sharks caught and copepod abundance showed downward trends and were positively correlated (r-value range, 0.44–0.74). A possible explanation for the downward trend in shark catches was that progressively fewer basking sharks occurred there between 1956 and 1975 because fewer copepods, their food resource, occurred near the surface off west Ireland over the same period. We suggest that the decline in basking sharks may have been due to a distributional shift of sharks to more productive areas, rather than a highly philopatric, localized stock that was over-exploited.

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The Russell Cycle is one of the classical examples of climate influence on biological oceanography, represented as shifts in the marine plankton over several decades with warm and cool conditions. While the time-series data associated with the phenomenon indicate cyclical patterns, the question remains whether or not the Russell Cycle should be considered a “true cycle”. Zooplankton time-series data from 1924 to 2011 from the western English Channel were analysed with principal component (PC), correlation and spectral analyses to determine the dominant trends, and cyclic frequencies of the Russell Cycle indicators in relation to long-term hydroclimatic indices. PC1 accounted for 37.4% of the variability in the zooplankton data with the main contributions from non-clupeid fish larvae, southwestern zooplankton, and overall zooplankton biovolume. For PC2 (14.6% of data variance), the dominant groups were northern fish larvae, non-sardine eggs, and southern fish larvae. Sardine eggs were the major contributors to PC3 (representing 12.1% of data variance). No significant correlations were observed between the above three components and climate indices: Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and local seawater temperature. Significant 44- and 29-year frequencies were observed for PC3, but the physical mechanisms driving the cycles are unclear. Harmonic analysis did not reveal any significant frequencies in the physical variables or in PCs 1 and 2. To a large extent, this is due to the dominant cycles in all datasets generally being long term (>50 years or so) and not readily resolved in the examined time frame of 88 years, hence restricting the ability to draw firm conclusions on the multidecadal relationship between zooplankton community dynamics in the western English Channel and environmental indices. Thus, the zooplankton time-series often associated and represented as the Russell Cycle cannot be concluded as being truly cyclical.

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The Russell Cycle is one of the classical examples of climate influence on biological oceanography, represented as shifts in the marine plankton over several decades with warm and cool conditions. While the time-series data associated with the phenomenon indicate cyclical patterns, the question remains whether or not the Russell Cycle should be considered a “true cycle”. Zooplankton time-series data from 1924 to 2011 from the western English Channel were analysed with principal component (PC), correlation and spectral analyses to determine the dominant trends, and cyclic frequencies of the Russell Cycle indicators in relation to long-term hydroclimatic indices. PC1 accounted for 37.4% of the variability in the zooplankton data with the main contributions from non-clupeid fish larvae, southwestern zooplankton, and overall zooplankton biovolume. For PC2 (14.6% of data variance), the dominant groups were northern fish larvae, non-sardine eggs, and southern fish larvae. Sardine eggs were the major contributors to PC3 (representing 12.1% of data variance). No significant correlations were observed between the above three components and climate indices: Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and local seawater temperature. Significant 44- and 29-year frequencies were observed for PC3, but the physical mechanisms driving the cycles are unclear. Harmonic analysis did not reveal any significant frequencies in the physical variables or in PCs 1 and 2. To a large extent, this is due to the dominant cycles in all datasets generally being long term (>50 years or so) and not readily resolved in the examined time frame of 88 years, hence restricting the ability to draw firm conclusions on the multidecadal relationship between zooplankton community dynamics in the western English Channel and environmental indices. Thus, the zooplankton time-series often associated and represented as the Russell Cycle cannot be concluded as being truly cyclical.

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The relationship between climate, represented by the North Atlantic Oscillation (NAO), and the calanoid copepod Calanus finmarchicus has been extensively studied. The correlation between NAO and C. finmarchicus has broken down (post-1995). In the present study, we revisit the relationship between C. finmarchicus and the NAO. Our reanalysis shows that previous treatment of this data did not take into account 2 aspects of both the C. finmarchicus and NAO index time-series: (1) the presence of significant trends and (2) significant autocorrelation. Our analysis suggests that previously reported relationships between NAO and C. finmarchicus abundance can be explained largely by the trends in both data series. Removing the trend from both time-series resulted in a decrease in the amount of C. finmarchicus abundance variability explained by the NAO. Trend removal eliminated the autocorrelation from the NAO time-series, but not from the C. finmarchicus time-series. Partial autocorrelation analysis showed that the autocorrelation present in the C. finmarchicus time-series is only found at a lag of 1 yr, suggesting strong, year-to-year connectivity in this population. We included the lagged C. finmarchicus abundance into a regression with the NAO and found that C. finmarchicus variability is explained by the previous year’s abundance and, to a much smaller extent, by NAO variability. Limiting the time-series to the most recent 22 yr period (1981 to 2002) showed that the NAO is no longer correlated to C. finmarchicus abundance, and the autocorrelation in the C. finmarchicus abundance series also appears to be weakening.

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A regime shift is a large, sudden, and long-lasting change in the dynamics of an ecosystem, affecting multiple trophic levels. There are a growing number of papers that report regime shifts in marine ecosystems. However, the evidence for regime shifts is equivocal, because the methods used to detect them are not yet well developed. We have collated over 300 biological time series from seven marine regions around the UK, covering the ecosystem from phytoplankton to marine mammals. Each time series consists of annual measures of abundance for a single group of organisms over several decades. We summarised the data for each region using the first principal component, weighting either each time series or each biological component (e.g. plankton, fish, benthos) equally. We then searched for regime shifts using Rodionov’s regime shift detection (RSD) method, which found regime shifts in the first principal component for all seven marine regions. However, there are consistent temporal trends in the data for six of the seven regions. Such trends violate the assumptions of RSD. Thus, the regime shifts detected by RSD in six of the seven regions are likely to be artefacts caused by temporal trends. We are therefore developing more appropriate time series models for both single populations and whole communities that will explicitly model temporal trends and should increase our ability to detect true regime shift events.

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Regime shifts are sudden changes in ecosystem structure that can be detected across several ecosystem components. The concept that regime shifts are common in marine ecosystems has gained popularity in recent years. Many studies have searched for the step-like changes in ecosystem state expected under a simple interpretation of this idea. However, other kinds of change, such as pervasive trends, have often been ignored. We assembled over 300 ecological time series from seven UK marine regions, covering two to three decades. We developed state-space models for the first principal component of the time series in each region, a common measure of ecosystem state. Our models allowed both trends and step changes, possibly in combination. We found trends in three of seven regions and step changes in two of seven regions. Gradual and sudden changes are therefore important trajectories to consider in marine ecosystems.

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The nano- and picoplankton community at Station L4 in the Western English Channel was studied between 2007 and 2013 by flow cytometry to quantify abundance and investigate seasonal cycles within these communities. Nanoplankton included both photosynthetic and heterotrophic eukaryotic single-celled organisms while the picoplankton included picoeukaryote phytoplankton, Synechococcus sp. cyanobacteria and heterotrophic bacteria. A Box–Jenkins Transfer Function climatology analysis of surface data revealed that Synechococcus sp., cryptophytes, and heterotrophic flagellates had bimodal annual cycles. Nanoeukaryotes and both high and low nucleic acid-containing bacteria (HNA and LNA, respectively) groups exhibited unimodal annual cycles. Phaeocystis sp., whilst having clearly defined abundance maxima in spring was not detectable the rest of the year. Coccolithophores exhibited a weak seasonal cycle, with abundance peaks in spring and autumn. Picoeukaryotes did not exhibit a discernable seasonal cycle at the surface. Timings of maximum group abundance varied through the year. Phaeocystis sp. and heterotrophic flagellates peaked in April/May. Nanoeukaryotes and HNA bacteria peaked in June/July and had relatively high abundance throughout the summer. Synechococcus sp., cryptophytes and LNA bacteria all peaked from mid to late September. The transfer function model techniques used represent a useful means of identifying repeating annual cycles in time series data with the added ability to detect trends and harmonic terms at different time scales from months to decades.

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Biological responses to climate change are typically communicated in generalized terms such as poleward and altitudinal range shifts, but adaptation efforts relevant to management decisions often require forecasts that incorporate the interaction of multiple climatic and nonclimatic stressors at far smaller spatiotemporal scales. We argue that the desire for generalizations has, ironically, contributed to the frequent conflation of weather with climate, even within the scientific community. As a result, current predictions of ecological responses to climate change, and the design of experiments to understand underlying mechanisms, are too often based on broad-scale trends and averages that at a proximate level may have very little to do with the vulnerability of organisms and ecosystems. The creation of biologically relevant metrics of environmental change that incorporate the physical mechanisms by which climate trains patterns of weather, coupled with knowledge of how organisms and ecosystems respond to these changes, can offer insight into which aspects of climate change may be most important to monitor and predict. This approach also has the potential to enhance our ability to communicate impacts of climate change to nonscientists and especially to stakeholders attempting to enact climate change adaptation policies.