Site-level variation drives the majority of variation in mixing depth in the time series dataset and the (marginally significant) effect of mobility is small in com-parison with site (figure 5.3 and table 5.2). Though species richness was an important determinant of ecosystem function (as found by Godbold & Solan, 2009) in the enrichment gradient dataset, the gradient itself was the predominant driver of the system, and there was little effect of phylogenetic dispersion. That total organic carbon (TOC) was less important than species richness does not im-ply that species richness is a dominant driver to enrichment. Chemical measures of enrichment from fish farms do not perfectly correlate with enrichment levels (Weston, 1990) and so distance from the fish farm may be a better measure of disturbance than TOC, particularly if the fish farm is a source of other kinds of contaminants and damage. The importance of species’ traits is debatable given that species’ predicted reworking ability was negatively correlated with mixing depth (figure 5.7c). This is likely to be a sampling effect; the enrichment gradient filters species according to traits other than reworking ability, and so when species richness increases, so too does the variation in species’ traits, implying that these
weighted abundances are simply another way of measuring species richness.
Productivity in the time series data is known to be driven by the ecosystem engineer Amphiura filiformis (Solan et al., 2004); its abundance is two orders of magnitude greater in the intact site, and so productivity is greater in the intact site. The negative relationship between species richness and mixing depth within the sites could be an artefact of temporal autocorrelation (see the decrease in mixing depth through time in the disturbed site in figure 5.3a), or it could reflect the impact of competition. In particular, sites crowded with filter-feeding species would have reduced bioturbation if those filter-feeders are attached to the sediment and thus hold it in place.
5.6 Conclusion
Quantifying the functional responses of benthic invertebrate assemblages is dif-ficult, because they are such a taxonomically and morphologically diverse group that they are difficult to measure on a common scale. While I have been able to show that benthic assemblages have different phylogenetic compositions, phylo-genetic dispersion (and trait data) fail to explain variation in ecosystem function.
These results suggest that environmental variation and ecosystem engineers, per-haps followed by interspecific competition, control ecosystem productivity.
5.7 Supplementary information
Copepoda Longipedia coronata Myodocopida Philomedes brenda Cylindroleberis mariae Stenothoe marina Ampelisca brevicornis Ampelisca diadema Ampelisca tenuicornis Metaphoxus Phoxocephalus holbolli Iphimedia Atylus falcatus Photis longicaudata Apherusa bispinosa Perioculodes longimanus Leucothoe lilljeborgi Pariambus typicus Parvipalpus capillaceus Phtisica marina Isopoda Sphaeroma serratum Idotea Astacilla longicornis Gnathia maxillaris Paragnathia formica Leptognathia gracilis Diastylis rugosa Bodotria scorpioides Eudorella truncatula Corystes cassivelaunus Carcinus maenas Macropodia deflexa Processa canaliculata Crangon crangon Pagurus bernhardus Eulima glabra Bittium reticulatum Turritella communis Lamellaria latens Buccinum undatum Raphitoma linearis Rissoella diaphana Rissoella opalina Cylichna cylindracea Philine aperta Abra alba Abra nitida Abra prismatica Fabulina fabula Moerella pygmaea Gari costulata Gari fervensis Circomphalus casina Chamelea gallina Mysia undata Myrtea spinifera Thyasira flexuosa Lepton squamosum Mysella bidentata Devonia perrieri Tellimya ferruginosa Acanthocardia echinata Parvicardium scabrum Cerastoderma edule Mactra stultorum Spisula subtruncata Phaxus pellucidus Nucula nitidosa Modiolus modiolus Corbula gibba Mya truncata Thracia phaseolina Phoronidae Echinocardium cordatum Thyone fusus Leptopentacta elongata Leptosynapta Astropecten irregularis Amphiura brachiata Amphiura filiformis Ophiura ophiura Styelidae Actinia equina Edwardsia claparedii Cerianthus lloydii Hydrozoa Virgularia mirabilis Nemertea Priapulus caudatus Sipuncula Ophelina acuminata Polyophthalmus pictus Scalibregma inflatum Owenia fusiformis Amphictene auricoma Lagis koreni Melinna palmata Ampharete grubei Terebellides stroemi Pista cristata Lanice conchilega Polycirrus medusa Euchone rubrocincta Pomatoceros lamarcki Oligochaeta Glycera tridactyla Goniada maculata Kefersteinia cirrata Neanthes fucata Nereis longissima Nereis pelagica Nephtys hombergii Aphrodita aculeata Harmathoe Pholoe inornata Sthenelais limicola Eteone flava Hypereteone foliosa Mysta barbata Mysta picta Anaitides groenlandica Anaitides longipes Anaitides maculata Eulalia viridis Eumida sanguinea Paranaitis kosteriensis Phyllodoce laminosa Pirakia punctifera Lumbrineris fragilis Arabella iricolor Scoloplos armiger Aricidea Spio filicornis Polydora ciliata Prionospio Malacoceros fuliginosus Magelona mirabilis Spiochaetopterus typicus Aphelochaeta marioni Diplocirrus glaucus Clymenella torquata Euclymene lumbricoides Capitellidae Arenicolides Anoplodactylus petiolatus
Figure 5.8: Phylogeny of the time series data, created as described in the text.
Philine aperta Cylichna cylindracea Ododstomia Nucula nitidosa Mytilus edulis Modiolus modiolus Myrtea spinifera Thyasira flexuosa Mysella bidentata Mysia undata Abra alba Abra nitida Abra III Corbula gibba Amphiura chiajei Amphiura filiformis Virgularia mirabilis Pennatula phosphorea Nemertea II Nemertea III Nemertea IV Nemertea V Scalibregma inflatum Travisia forbesii Ampharete lindstroemi Terebellides stroemi Pista lornensis Pista maculata Axionice maculata Polycirrus norvegicus Terebellidae Melinna palmata Sabellidae Hydroides norvegica Oligochaeta I Oligochaeta II Pholoe inornata Phyllodocidae Eteone longa Mysta picta
Pseudomystides limbata Phyllodoce maculata Phyllodoce laminosa Eumida bahusiensis Glycera tridactyla Glycera alba Nereis iorrorata Hesionidae Neanthes irrorrata Nereimyra punctata Ophiodromus flexuosus Eunicidae
Lumbrineris laterilli Lumbrineris tetaura Lumbrineris hibernica Leitoscoloplos squamosus Orbinia latereilli Orbinia sertulata Aonides
Malacoeros fulinginosus Minuspio cirrifera Minuspio I Polydora caeca Laonice sarsi Prionospio fallax SpioSpiophanes bombyx Spiophanes kroyeri Magelona filiformis Aphelochaeta
Aphelochaeta multibranchis Cirratulidae I
Cirratulidae II Cirratulidae III Chaetozone Tharyx marioni Cirratulus cirratus Cirratulus filiformis Diplocirrus glaucus Capitella capitata Heteromastus filiformis Notomastus latericeus Maldane sarsi Praxillella Euclymene Cumacea Caprellidae Eudorella truncatula Mysidacea Ampelisca diadema Westwodilla caecula Leucothoe lilljeborgi Crangon crangon Upogebia Anapagurus laevis
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Figure 5.10: Change in phylogenetic dispersion across the organic enrichment gradient, excluding the most impacted site. Each line is a linear regression; note that the D regression has a greater slope (0.029 vs. 0.078) than in figure 5.6b.