IDENTIFICACIÓN DEL MERCADO

Spatial heterogeneity (patchiness) in foraminiferal distribution can occur at centimetre to metre scales (e.g. Boltovskoy and Lena, 1969; Fontanier et al., 2003; Morvan et al., 2006). Currently the causes of patchiness are poorly understood but have previously been attributed to grazing and predation (Murray and Alve, 2000), or the uneven distribution of organic matter (Murray, 1991; Swallow, 2000; Morvan et al., 2006). Spatial heterogeneity can introduce bias to the calculation of foraminiferal density (absolute abundance) obscuring the understanding of temporal variability (Buzas, 1968, 1970; Schafer, 1971; Buzas et al., 2002; Morvan et al., 2006). In order to quantify the spatial heterogeneity at a site, it is recommended that replicate samples are taken and that these are independently analysed (Schönfeld et al., 2012). Although this study analysed replicate samples, in order to attain statistically significant census counts the replicates were aggregated. Consequently, it was not possible to undertake a full assessment of the degree of spatial heterogeneity in this study. However, the standard error of the absolute abundance of each pair of replicates was calculated (Figure 4.3). The difference between the absolute abundance of the pairs of replicates was most noticeable during June and July (Figure 4.3); this suggests that patchiness occurs at this site and it may be seasonally variable. However, the aggregation of replicate pairs in this study minimises the potential bias caused by patchiness and should therefore provide a good representation of the temporal variability in assemblage structure at this site (Murray, 1991; Schönfeld and Numberger, 2007).

The spatial heterogeneity exhibited between the standing crops of the two replicate samples may also be attributed to the sampling techniques employed in this study. Although significant

care was taken to collect samples from the top 1-2 cm of the sediment, no standardised volume of sediment was taken. Consequently, there is a possibility that this technique may have captured samples at different depths in the sediment. Samples taken below the optimal depth of 1-2 cm may dilute the number of live foraminifera per 100ml due to the inclusion of an increased number of empty (dead) tests from deeper layers (Fontainer et al., 2003; Schönfeld et al., 2012). The aggregation of the paired replicate samples also helps to reduce any sampling bias. This study could be strengthened by quantifying the impact of the potential sampling bias and spatial heterogeneity by analysing the foraminiferal assemblage structure from a series of push cores (circa 5) which have known volumes and sediment depths.

Another potential limitation of this study is that it uses Rose Bengal staining to identify live foraminiferal species. However, the efficacy of Rose Bengal staining was previously questioned as protoplasm can persist days or even weeks after death (Walker et al., 1974; Bernhard, 1988, 2000; Corliss and Emerson, 1990; Murray and Bowser, 2000). To address this, a stringent protocol of assessing the degree of Rose Bengal staining was implemented.

Finally, whilst this study provides a detailed account of the inter-annual variability of the foraminiferal assemblage structure, it is unclear whether the same temporal trends are replicated on an inter-annual basis. For example, previous time series studies have recognised that seasonal patterns are not always reproduced on a year to year basis, and that analysis of a single year may not reveal the underlying cyclicity in species diversity and assemblage compositions (Boltovskoy and Lena, 1969; Scott and Medioli, 1980; Basson and Murray, 1995; Alve and Murray, 2000; Swallow, 2000; Morvan et al., 2006). This highlights the necessity of further taxonomic investigation at this site to verify the reoccurrence of these seasonal trends.

4.5

Conclusions

This study provides the first time-series analysis of a coastal environment in NW Scotland in which the temporal dynamics of benthic foraminiferal diversity and assemblage composition are investigated. Notably this is the first applied taxonomic investigation which incorporates new lines of taxonomic evidence to document the seasonal variability of two previously cryptic species of Ammonia. Two species of Ammonia were identified co-existing throughout the year, with some evidence to suggest that they exhibit subtle seasonal partitioning. Ammonia

genotype S5a is dominant during November-January, whilst Ammonia genotype S6 is dominant during February-June. This subtle seasonal partitioning could indicate that these Ammonia

species occupy distinct ecological niches.

Additionally, this study has provided baseline information on how foraminiferal diversity and overall assemblage composition changes seasonally. This understanding is crucial, as it is a prerequisite for downstream studies that assess how biodiversity and species ranges change in response to abrupt climate change. In total 52 species were identified at this site and the assemblage was dominated by three species: Nonionella turgida, Ammonia genotype S5a and

Ammonia genotype S6. No clear seasonal trends in biodiversity nor standing crops were identified over the period of investigation. However, the results have identified a clear temporal trend in changes to the overall assemblage composition. For example, the abundance of

Nonionella turgida shifts over the course of the year, i.e. it is dominant in spring-summer, whilst less prevalent in winter. However, no clear causal relationship was identified between the abundance of the five dominant taxa and temperature and salinity measured at this site. Interpreting the controls on this temporal variability is difficult due the paucity of environmental data available. However, the results reveal that species occurrences may be driven by the source and input of food supply at this site (e.g. seasonal phytoplankton blooms, Murray, 1983; Scott et al., 2003).

Future investigation should focus on conducting extended sampling, coupled with detailed environmental surveys to analyse if these temporal trends are repeated inter-annually and to elucidate the environmental controls on the assemblage structure. Additionally, further investigation is needed to clarify the ecology, biology and geochemistry of the newly delineated

Ammonia genotypes so that species-specific proxies can be refined, this in turn can help to inform our understanding of past and future climate change.

5