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7c. Shelduck, Pochard and Brent Goose

The density distribution of Shelduck, Pochard and Brent Goose was analysed in the Humber estuary. A summary of the resulting models obtained for these species is reported in Table 7 and the shape of the effect of each selected continuous predictor variable on the model response is shown in Figure 9.

Shelduck is a large duck which is present throughout much of the Humber estuary, where it feeds on mudflats. Six environmental variables have been selected in the final model as best predictors of its density distribution in the estuarine areas, explaining 83% of the density data variability. The most important predictors of the density of this species are the subtidal and the intertidal area, both variables showing an almost linear positive relationship with this species. The species density is also expected to increase with the supratidal area in the estuarine sectors, particularly with areas >0.5 km2.  However, the type of intertidal habitat is also relevant in affecting the species distribution, with higher density expected where littoral mud substratum dominates. Similarly to that observed for other species, an increase in Shelduck density is predicted in sectors where a higher disturbance index is measured.  However, it is emphasised that rather than this being a reflection of a real preference of the species for more disturbed areas, this result is likely to be an artefact of the analysis, due to the possible inadequacy of the measured index as a proxy for disturbance (see Discussion for a detailed explanation). A relevant effect of temporal trends (measured by year) on the local estuarine population is also present, although this variable, together with the disturbance index, are the least important predictors of Shelduck density among those considered in the analysis.

Pochard is a largely freshwater duck that can be found in the estuary during winter, although its frequency of occurrence in the studied dataset is relatively low (23%), due to the distribution of the species mostly in the upper estuary sectors (oligohaline and upper mesohaline areas). The probability of occurrence was modelled for the species in the Humber and six environmental variables have been selected in the final model as best predictors of its distribution in the estuarine areas, explaining 74% of the data variability. Although most of the habitat areas (except for supralittoral area) are included as important predictors of the occurrence of the species in the estuary, it is the relationship with intertidal and marsh areas that show the most marked patterns, with a higher probability of finding Pochard in sectors where the intertidal area is <10 km2, but there is a wider marsh area (>0.84 km2) compared to other sectors. The type of intertidal habitat also seems to be a relevant predictor of the species occurrence, although the relationship with this factor is not clear, due to the similar contribution of the different types to the probability of presence but with a wider variability of the data where mixed substrata dominated by littoral mud occur. Also for this species, the potential degree of disturbance index (in this case showing a negative linear effect on the species, although the rate of decrease of the probability of occurrence is very low) and the effect of temporal trends (measured by year) on the local estuarine population is present, these variables being the least important predictors of the species presence among those considered in the analysis.

Brent Goose is a migrating species found during winter months in estuaries and saltmarshes, grazing upon surface plants and green algae on mudflats. For this species, the probability of occurrence was modelled in the Humber due to the limited frequency of presence (44%). Six environmental variables have been selected in the final model as best predictors of its distribution in the estuarine areas, explaining 79% of the data variability. All the variables accounting for habitats area within the sectors are included as predictors of the occurrence of the species in the estuary, with intertidal area being the most important one. In particular, based on the obtained model, a higher probability of occurrence of the species is expected where the intertidal area is maximised in the sector (in particular when >10 km2), in combination with small marsh area (<0.5 km2), intermediate supralittoral area (between 0.1 and 0.6 km2) and either smaller (<7 km2) or larger (>27 km2) subtidal area. An increase in Brent Goose occurrence is also predicted in sectors where a higher disturbance index is measured, but, as highlighted before, this is likely to be an artefact of the analysis rather than being a reflection of a real preference of the species for more disturbed areas (see Discussion for a detailed explanation). A relevant effect of temporal trends (measured by year) on the local estuarine population is also present, although, as observed for other species, this variable, together with the disturbance index, are the least important predictors of the species presence among those considered in the analysis.

Table 7. Summary of the habitat distribution models applied to selected wildfowl species in the Humber Estuary. Single predictor models are also reported as a means to rank the importance of the single variables in affecting the species distribution. The variables highlighted in grey are those variables that were excluded from the analysis because of collinearity (their relationship with the other variables included in the analysis is indicated in parenthesis). The variables in bold (and with the asterisk) are those variables that were selected as relevant predictors of the species distribution in the final (best) model.

Figure 9. Effect of each explanatory continuous variable on the mean density of Shelduck (A), and on the probability of presence of Pochard (B) and Brent Goose (C), measured as contribution on the linear term of the best selected species models for the Humber Estuary. The fitted values are adjusted to average zero and the dotted bands indicate 95% pointwise confidence intervals. Tick marks along the x-axis show the location of observations along the variable range. The transformations of explanatory variables are abbreviated as follows: Sqrt, square root, Sqrt2, forth-root, Log, logarithmic transformation.