Erosion of phylogenetic diversity in Neotropical bat assemblages: findings from a whole-ecosystem fragmentation experiment

Vol.:(0123456789) Biodiversity and Conservation (2019) 28:4047–4063 https://doi.org/10.1007/s10531-019-01864-y 1 3 ORIGINAL PAPER Erosion ofphylogenetic diversity inNeotropical bat assemblages: findings fromawhole‑ecosystem fragmentation experiment SabhrinaG.Aninta, etal.[full author details at the end of the article] Received: 26 February 2019 / Revised: 1 October 2019 / Accepted: 9 October 2019 / Published online: 14 October 2019 © The Author(s) 2019 Abstract The traditional focus on taxonomic diversity metrics for investigating species responses to habitat loss and fragmentation has limited our understanding of how biodiversity is impacted by habitat modification. This is particularly true for taxonomic groups such as bats which exhibit species-specific responses. Here, we investigate phylogenetic alpha and beta diversity of Neotropical bat assemblages across two environmental gradients, one in habitat quality and one in habitat amount. We surveyed bats in 39 sites located across a whole-ecosystem fragmentation experiment in the Brazilian Amazon, representing a gradient of habitat quality (interior-edge-matrix, hereafter IEM) in both continuous forest and forest fragments of different sizes (1, 10, and 100ha; forest size gradient). For each habitat category, we quantified alpha and beta phylogenetic diversity, then used linear mixedeffects models and cluster analysis to explore how forest area and IEM gradient affect phylogenetic diversity. We found that the secondary forest matrix harboured significantly lower total evolutionary history compared to the fragment interiors, especially the matrix near the 1ha fragments, containing bat assemblages with more closely related species. Forest fragments ≥ 10ha had levels of phylogenetic richness similar to continuous forest, suggesting that large fragments retain considerable levels of evolutionary history. The edge and matrix adjacent to large fragments tend to have closely related lineages nonetheless, suggesting phylogenetic homogenization in these IEM gradient categories. Thus, despite the high mobility of bats, fragmentation still induces considerable levels of erosion of phylogenetic diversity, suggesting that the full amount of evolutionary history might not be able to persist in present-day human-modified landscapes. Communicated by Raphael K. Didham. Our study highlights the erosion of phylogenetic diversity of bat assemblages associated with habitat fragmentation and degradation in the world’s largest and longest-running whole-ecosystem fragmentation experiment. This work advances our understanding of the effects of habitat modification on bats as key ecosystem service providers in tropical ecosystems. Electronic supplementary material The online version of this article (https ://doi.org/10.1007/s1053 1-019-01864 -y) contains supplementary material, which is available to authorized users. 4048 Biodiversity and Conservation (2019) 28:4047–4063 1 3 Keywords Evolutionary history· Environmental gradients· Amazon· Forest fragments· Secondary forests· Chiroptera Introduction Humans have fundamentally changed the face of the Earth, with negative side-effects for biodiversity across all major biomes. Tropical forests are among the biomes impacted most heavily given the large footprint of pervasive land use changes which have resulted in widespread habitat loss and fragmentation (Austin etal. 2017; Barlow etal. 2018). These land use changes have detrimentally affected the richness, abundance, and composition of many tropical taxa (Alroy 2017), leading to a pattern of extensive defaunation, with cascading effects on ecosystem functioning (Young etal. 2016). Idiosyncratic responses of species to fragmentation are ubiquitous, rendering assemblage-level inferences regarding fragmentation effects generally difficult (Ewers and Didham 2006; Fahrig 2017). This is mainly because the treatment of species as equal entities by neglecting their unique evolutionary history, functional roles in the ecosystem, and their association with each other within the community (Pellens and Grandcolas 2016), paints an incomplete picture of the effects of habitat fragmentation. Therefore, recent studies assessing the effect of habitat fragmentation on tropical taxa have started to incorporate evolutionary information using phylogenetic diversity metrics in addition to species richness (Frishkoff etal. 2014; Santos etal. 2014; Cisneros etal. 2015, 2016; Aguirre etal. 2016; Frank etal. 2017). By doing so, these studies were able to uncover patterns previously undetected by studies with a sole focus on the taxonomic dimension of biodiversity. For example, the decrease of distantly-related plant species in a fragmented landscape (Santos etal. 2014) suggests that habitat fragmentation impoverished evolutionary history of the taxa in question. Similar trends were also found in more mobile taxa such as birds and bats, which also showed that closely-related species tend to co-occur more often than expected by chance in various types of disturbed habitats (Riedinger etal. 2013; Frishkoff etal. 2014; Frank etal. 2017). This pattern, often referred to as phylogenetic clustering, indicates a strong effect of habitat filtering (Vamosi etal. 2009). Phylogenetic clustering in fragmented landscapes, however, is not consistently supported by empirical evidence. Several studies have documented the tendency of phylogenetic overdispersion at the edge of fragmented forests (Santos etal. 2010; Peralta et al. 2015), suggesting that different types of habitat within a fragmented landscape differentially affect the evolutionary dimension of biodiversity. Gaining better insights into the extent to which phylogenetic diversity of assemblages is eroded as a result of habitat fragmentation therefore is critical to improve our general understanding of biodiversity persistence in human-modified landscapes. Despite their mobility, bats (Chiroptera) are among the many animal groups that are demonstrably affected by habitat loss and fragmentation (Meyer etal. 2016; Alroy 2017). Notwithstanding increased research effort devoted over recent years to better understand how bats respond to habitat fragmentation, studies at the assemblage level, typically comparing species richness, diversity, and assemblage composition between forest fragments and continuous forest, show inconsistent results and highlight the need for more research focusing on the functional and phylogenetic biodiversity dimensions (Meyer etal. 2016). Bats are a good model group to study the effect of habitat fragmentation on phylogenetic diversity given their high species richness, functional diversity, and key roles in ecosystem 4049 Biodiversity and Conservation (2019) 28:4047–4063 1 3 functioning (Kunz etal. 2011). Studies employing a phylogenetic approach to investigate bat responses towards habitat disturbance (Cisneros etal. 2015; Frank etal. 2017; Presley etal. 2018) have been made possible by the availability of phylogenetic trees of all extant bat species (Jones etal. 2002, 2005; Shi and Rabosky 2015) that can be used to calculate phylogenetic diversity metrics. Of the few studies that have investigated bat phylogenetic diversity in fragmented landscapes, none has assessed responses across the entire gradient in habitat quality typically encountered, formed by the interiors (I) and edges (E) of continuous forest and forest fragments, as well as the intervening matrix (M), or the IEM gradient (Rocha etal. 2017a). Explicit consideration of the full IEM gradient, however, is important to better understand the extent of habitat filtering that usually is regarded as the cause of phylogenetic clustering in disturbed habitats (Riedinger etal. 2013; Frank etal. 2017; Presley etal. 2018) as species persistence in fragmented landscapes may be differentially affected by this gradient in habitat quality (Ferreira etal. 2017). The observed phylogenetic richness and structure in each habitat that comprises the IEM gradient can give an indication about the amount of evolutionary history retained by the constituent habitat elements of a fragmented landscape (Cisneros etal. 2015). Moreover, exploring which habitats share similar evolutionary history or harbour lineages that are more closely related compared to other habitats may give insights into the evolution of habitat preferences (Graham and Fine 2008). To elucidate how habitat fragmentation affects the evolutionary dimension of bat diversity, we investigated the changes in phylogenetic alpha and beta diversity of Amazonian bat assemblages across two environmental gradients, one in habitat quality (IEM gradient) and one in habitat amount (forest size: continuous forest; fragments of 1, 10 and 100ha), in the experimentally fragmented landscape of the Biological Dynamics of Forest Fragments Project (BDFFP), the world’s largest and longest-running experimental study of habitat fragmentation (Haddad etal. 2015), investigating a total of 12 habitat categories (the IEM gradient of the continuous forest and forest fragments). We expected that differences in phylogenetic diversity between forest fragments of different size will depend on the habitat quality therein so that the interaction between IEM gradient and forest size (habitat amount) will affect both phylogenetic alpha and beta diversity. The assemblages in the secondary forest matrix should retain the least total evolutionary history due to selection of bat lineages that are best adapted to different levels of habitat quality (Rocha etal. 2018), followed by edges, while the interiors of continuous forest should harbour the most evolutionary history due to greatest resource availability (Ries and Sisk 2004). Accordingly, phylogenetic clustering should be strongest in the matrix surrounding the smallest forest fragments as habitat filtering would result in each habitat category harbouring lineages that have already been adapted to a specific set of habitat conditions (Farneda etal. 2015; Ferreira etal. 2017). These effects would result in low phylogenetic beta diversity among similar habitat categories as phylogenetic turnover would be low in assemblages containing similar types of lineages. Methods Study area The BDFFP spans ~ 1000km2 and is located approximately 80km north of Manaus, Brazil (S2°30′, W60°; Fig. S1). The area contains different-sized forest fragments separated by 4050 Biodiversity and Conservation (2019) 28:4047–4063 1 3 80–650m from the surrounding continuous forest that serves as experimental control (Laurance etal. 2018). Following abandonment of the cattle pastures which initially surrounded the experimentally isolated fragments after their creation in the early 1980s, Vismiaand Cecropia-dominated secondary forest developed in the matrix (Mesquita etal. 2015). Fragment isolation was maintained by clearing and burning of a 100m-wide strip of secondary forest around each of the forest fragments at intervals of ca. 10years. Prior to this study, the most recent re-isolation occurred between 1999 and 2001 (Rocha etal. 2017b). The forest at the BDFFP is a typical non-flooded forest of the Amazon basin (De Oliveira and Mori 1999), with approximately 280 species of trees (dbh > 10cm) per hectare (Laurance et al. 2010). The area has a relatively flat topography (80–160m), with nutrient-poor soils. Rainfall ranges from 1900 to 3500 mm annually, with a moderately strong dry season from June to October (Laurance etal. 2018). Bat sampling Bats were sampled with ground-level mist nets in eight primary forest fragments—three of 1ha, three of 10ha and two of 100ha—and in nine control sites in three areas of continuous forest (Fig. S1). The eight forest fragments and three of the control sites were sampled in the interior, at the edges, and in the secondary forest matrix, whereas the remaining six control sites were sampled in their interior only, resulting in a total of 39 sites (Fig. S2). Distances between interior and edge sites of continuous forest and fragments were, respectively 1118 ± 488 and 245 ± 208m (mean ± SD). Matrix sites were located ca. 100m away from the border between primary and secondary forest. Edge sites were sampled with mist nets deployed in the contact zone between primary and secondary forest which allowed us to study edges as linear landscape features. In fragments, interior sites were placed in the centre whereas in continuous forest we placed sampling sites in areas previously sampled for different taxa. Selection of field sites was constrained by limitations associated with fieldwork in remote locations (we tried to use well marked trails, especially in continuous forest) and restrictions imposed by the BDFFP which has strict limitations regarding the opening of new trails in their experimental fragments. The placement of the mist nets was therefore limited to pre-existing trails which precluded a study design suitable to investigate edge penetration. Each sampling site was visited eight times over a 2-year period (August 2011–June 2013). Bats were captured using 14 ground-level mist nets (12 × 2.5 m, 16 mm mesh, ECOTONE, Poland) in the interiors of forest fragments and continuous forest, and seven ground-level mist nets at the edge and matrix sites. The nets were exposed for 6h after dusk and visited at intervals of ca. 20min. Total sampling effort was 18,650 mist net hours ([1 mist-net hour (mnh) equals one 12-m net open for 1h]) during which 4210 bats belonging to six families and 55 species were captured. We restricted our analyses to bats of the family Phyllostomidae, the only Neotropical bat family that can be adequately sampled with mist nets (Kalko 1998). Thus, 3494 captures from 43 species were included in our calculations of phylogenetic diversity. Phylogenetic information The phylogenetic information of phyllostomid species present at the BDFFP, hereafter referred to as the local phylogeny, was extracted from the most recent species-level phylogeny of bats (Shi and Rabosky 2015) using R package ‘picante’ (Kembel etal. 2010). 4051 Biodiversity and Conservation (2019) 28:4047–4063 1 3 We chose this particular tree as it covered more of the phyllostomid species that occur at the BDFFP compared to another frequently used bat phylogenetic tree published by Jones etal. (2002, 2005). The supertree was downloaded from TreeBASE and pruned to obtain the local phylogeny. The branch lengths of the local phylogeny represent the divergence time of the species in millions of years. As we used distance-based phylogenetic diversity metrics, the phylogenetic pairwise distance matrix was extracted from the local phylogeny using the ‘cophenetic.phylo()’ function from R package ‘ape’ (Paradis etal. 2004). Species that occur in the study area but were not present in the pruned tree were substituted by their congeners, following Cisneros etal. (2016). Only for two out of 43 captured phyllostomid species was this the case, i.e. Artibeus gnomus and A. cinereus, which hence were both represented by their closest congener, A. glaucus (Redondo etal. 2008). Measuring phylogenetic diversity Alpha diversity We explored variation in phylogenetic richness and structure within assemblages separately across the IEM gradient of 1, 10, and 100ha fragments and continuous forest (CF) using Faith’s phylogenetic diversity (Faith 1992) and mean pairwise distance (Clarke and Warwick 1998; Webb 2000), hereafter referred to as PD and MPD, respectively. To account for different sampling effort across the 12 habitat categories, we performed individual-based rarefaction of the observed PD values of the different assemblages using the R package ‘BAT’ (Cardoso etal. 2015) by randomly (100×) sampling individuals from the regional pool; the sample size was the minimum abundance across all the 12 habitat categories, corresponding to 113 captures at the edges of the 1ha fragments. To assess the effect of phylogenetic information per se on PD, we eliminated any potential effect of species richness by calculating SESPD (standardized effect size of PD) under a ‘richness’ null model (Swenson 2014). Similarly, we quantified phylogenetic structure per se by calculating SESMPD (standardized effect size of MPD) using the tip-shuffling null model (Swenson 2014). However, as our local phylogeny consisted of closely related phyllostomids with quite a balanced topology, MPD could underestimate phylogenetic clustering in the terminal part of the phylogeny (Vamosi etal. 2009). We therefore also calculated the mean nearest taxon distance (MNTD) and computed SESMNTD using the tip-shuffling null model as it is more sensitive than MPD for detecting phylogenetic clustering in the terminal part of the local phylogeny (Tucker et al. 2017). Significant community structure can be inferred if the standardized effect size values lie above or below the 95% and 5% quantiles, respectively, of the null distribution. For SESMPD and SESMNTD, high quantiles (> 95%) indicate a phylogenetically over-dispersed assemblage whereas low quantiles (< 5%) indicate a phylogenetically clustered assemblage (Swenson 2014). Beta diversity To explore between-assemblage variation in phylogenetic richness and structure in relation to the habitat quality (IEM) and amount gradients, we calculated COMDIST and phylogenetic beta diversity ( Pβtotal ), respectively. COMDIST is the mean pairwise phylogenetic distance (MPD) between species from different assemblages (Swenson 2011) which could help reveal which habitats along the gradient contain closely related lineages. To calculate COMDIST, we used R package ‘picante’ (Kembel etal. 2010). Phylogenetic beta 4052 Biodiversity and Conservation (2019) 28:4047–4063 1 3 diversity was partitioned into its richness ( Pβrich ) and replacement ( Pβrepl ) components to capture, respectively, the difference in shared total branch lengths between assemblages and the uniqueness of each assemblage based on the evolutionary lineages present (Cardoso etal. 2014). To calculate Pβtotal and its partitions, we used R package ‘BAT’ (Cardoso etal. 2015). Phylogenetic alpha andbeta diversity acrosstheIEM andforest size gradient Alpha diversity We used linear mixed-effects models to assess how the IEM and forest size gradient affect the evolutionary dimension of biodiversity. For each metric of phylogenetic alpha diversity and its standardized effect size, we evaluated the multivariate relationshipsby incorporating an interaction term of the fixed effects IEM gradient (interior, edge, matrix) and forest size (CF, 100ha, 10ha, or 1ha) as well as a random effect of site nested within location (i.e. sampling camp locations, see Fig. S2) using the ‘lme4’ package (Bates etal. 2015). If the full model was significant compared to the null model with only the intercept (P < 0.05), effects were further evaluated via multiple comparison tests using Tukey contrasts (adjusted P values reported) using the R package ‘multcomp’ (Hothorn etal. 2008). If the multivariate model was non-significant compared to the null model (P > 0.05), the full model was not further evaluated. We note that adding the random effect did not improve the fit of the explanatory variables in the full model (see TableS1). Thus, we tested for spatial structure in the residuals of the significant models using Moran’s I (Moran 1950) calculated with the ‘spdep’ package (Bivand etal. 2008). Beta diversity To detect any implicit spatial structure in Pβtotal , Pβrich , Pβrepl , and COMDIST, we visualized these metrics through UPGMA clustering (Borcard etal. 2011) using the ‘hclust’ function in R (R Core Team 2017). When applied to Pβrich , UPGMA will cluster assemblages with similar amount of phylogenetic richness whereas Pβrepl will cluster assemblages with similar lineages. For COMDIST, UPGMA will cluster closely related assemblages. A Mantel test (Mantel 1967) was conducted using the R package ‘vegan’ (Oksanen etal. 2017) to detect any linear (Pearson correlation) or non-linear (Spearman’s rank correlation) spatial structure in Pβtotal , Pβrich , Pβrepl , and COMDIST. Results Comparison withinassemblages: phylogenetic diversity islowest inthesmallest fragments Rarefied PD showed a decreasing trend from continuous forest and fragment interiors to forest edges and matrix, with the matrix sites adjacent to the 1ha fragments harbouring the lowest PD overall (Fig.1). The likelihood ratio test supports the significance of the interaction between IEM gradient and forest size in explaining PD (L = 59.76, df = 11, P ≤ 0.001). The parameter estimates have a wide confidence interval so that we could 4053 Biodiversity and Conservation (2019) 28:4047–4063 1 3 not exclude the possibility of the effect of IEM gradient and forest size towards PD being much weaker or stronger (TableS2). However, multiple comparison tests showed that the decrease in PD from forest interior towards edge and matrix was significant in 1ha fragments whereas in larger fragments the decrease was only significant in the edge (TableS3). Phylogenetic richness in 1ha fragments was also considerably lower than in larger fragments across the entire IEM gradient (TableS3). When the effect of species richness on PD was accounted for (SESPD), the interaction term did not significantly improve model fit (L = 17.835, df = 11, P = 0.086). After subsequently dropping non-significant terms, we found that a univariate model incorporating the IEM gradient explained SESPD better than the full model (L = 7.341, df = 2, P = 0.026). The simulated null communities for PD further showed that SESPD values were considerably lower in the edges and matrix surrounding forest fragments compared to forest interior although smaller fragments do not exhibit considerably lower SESPD than larger fragments (Fig.2a), further corroborating the strength of IEM gradient in explaining the phylogenetic richness of phyllostomid bats across the BDFFP. The pattern of phylogenetic structure captured by MPD was likely caused by the interaction between IEM gradient and forest size (L = 26.587, df = 11, P = 0.005), even when we standardized the effect of phylogenetic structure (L = 22.201, df = 11, P = 0.023). In line with our full model, the simulated null communities showed that SESMPD values were lower than expected in the interiors of 1ha fragments, fragment edges, and the matrix around the larger (10 and 100 ha) fragments (Fig. 2b). The assemblages in the matrix surrounding 1ha fragments, although not characterised as Fig. 1 Comparison of rarefied phylogenetic richness of bat assemblages across gradients of habitat quality (interior, edge, and matrix) and habitat amount (continuous forest, 100 ha fragment, 10 ha fragment and 1ha fragment) at the Biological Dynamics of Forest Fragments Project, Brazil. The boxplots indicate the median, minimum, lower bound, upper bound, and maximum values of the repeated re-sampling of all pooled individuals, whereas the observed values of the total sum of branch lengths for all sites in each habitat category are overlaid on the boxplot as dots. Data were rarefied to the abundance level of the habitat category with the lowest number of captures (1ha fragment edges, denoted by a line due to constituting the reference sample) 4054 Biodiversity and Conservation (2019) 28:4047–4063 1 3 phylogenetically clustered based on its SESMPD (Fig.2b), showed terminal clustering based on its significantly lower SESMNTD (Fig.2c). Our data could not provide enough evidence to infer the difference in phylogenetic structure between habitat categories, however, multiple comparison tests showed that most pairwise differences among habitat categories were largely caused by chance (see TableS4 for MPD and TableS5 for SESMPD) except between 100ha matrix and 10 ha interiors (P = 0.015 for MPD and P = 0.006 for SESMPD, Tables S4 and S5, respectively). According to the local phylogeny (Fig. S3), most lineages that reside within the matrix surrounding 100ha fragments are different from those in the interiors of 10ha fragments. The distinctiveness of these two habitat categories was also corroborated by the replacement component of phylogenetic beta diversity ( Pβrepl , Fig.3c). The confidence interval was also relatively large for the parameter estimates of the models for MPD and SESMPD, indicating that our models were unreliable in predicting the phylogenetic structure in our study design (TableS2). Our results were unlikely affected by spatial autocorrelation as global Moran’s I tests did not show any spatial dependence of the residuals of the fitted models (TableS6, all P > 0.05). The implicit spatial structure of sampling site nested within location also unlikely contributes to the pattern of phylogenetic diversity metrics, considering the low variance of the random effects (see TableS2). Comparison betweenassemblages: noclear pattern oflineage replacement Dendrograms based on the total evolutionary history shared between assemblages (Pβtotal, Pβrich, and Pβrepl; Fig. 3) were substantially different from the one based on relatedness between lineages within assemblages (COMDIST; Fig.4). UPGMA clustering based on total phylogenetic beta diversity (Pβtotal) suggested that the interiors of continuous forest and forest fragments harbour similar amounts of phylogenetic richness, except for the 1ha fragments (Fig.3a), further confirming the phylogenetic erosion of 1ha fragments. The similarity in total phylogenetic richness between the interiors of continuous forest and larger forest fragments (10 and 100ha) was maintained after Pβtotal was partitioned into Pβrich and Pβrepl. For Pβrich, however, the interior sites of the larger fragments clustered together, unlike Pβtotal which grouped the interior of continuous forest closer together with that of 100ha fragments (Fig.3b). For Pβrepl, the interior sites were over-dispersed (Fig.3c), suggesting that the difference in Pβtotal compared to Pβrich is caused by different lineages contained within the interiors. Although there was a significant relationship between geographic proximity and Pβtotal (Pearson’s Mantel statistic r = 0.134, P = 0.013, TableS7), the relationship did not hold when we partitioned Pβtotal into Pβrepl (Pearson’s Mantel statistic r = 0.031, P = 0.299, Table S7) and Pβrich (Pearson’s Mantel statistic r = 0.059, P = 0.138, TableS7). UPGMA clustering of COMDIST revealed that the investigated assemblages were closely related and were not clustered according to either the same IEM gradient or the same forest size categories (Fig.4). The position of the interior sites of 1ha fragments Fig. 2 Standardized effect size (dots) of a Faith’s phylogenetic diversity (PD), b mean pairwise distance (MPD), and c mean nearest taxon distance (MNTD) along with 5% and 95% quantiles (dashed lines) of the simulated null communities (box and whisker plots). For SESMPD and SESMNTD, high quantiles (> 95%) indicate a phylogenetically over-dispersed assemblage whereas low quantiles (< 5%) indicate a phylogenetically clustered assemblage. In the box plots, values of observed PD, MPD, and MNTD overlaid on the simulated null communities are indicated by a black diamond ▸ 4055 Biodiversity and Conservation (2019) 28:4047–4063 1 3 4062 Biodiversity and Conservation (2019) 28:4047–4063 1 3 Moreno CE, Halffter G (2001) Spatial and temporal analysis of α, β and γ diversities of bats in a fragmented landscape. Biodivers Conserv 10:367–382 Morlon H, Schwilk DW, Bryant JA et al (2011) Spatial patterns of phylogenetic diversity. 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Aninta [email protected] 1 Munich Graduate School forEvolution, Ecology andSystematics (EES), Faculty ofBiology, Ludwig-Maximilians-Universität München, Munich, Germany 2 Tambora Muda Indonesia, Jalan Samiaji 3 Nomor 10 Bantarjati, Perumahan Indraprasta Bogor Utara, Bogor16153, Indonesia 3 Centre forEcology, Evolution andEnvironmental Changes–cE3c, Faculty ofSciences, University ofLisbon, 1749-016Lisbon, Portugal 4 Biological Dynamics ofForest Fragments Project, National Institute forAmazonian Research andSmithsonian Tropical Research Institute, Manaus69011-970, Brazil 5 Conservation Science Group, Department ofZoology, University ofCambridge, CambridgeCB23EJ, UK 6 Granollers Museum ofNatural Sciences, 08402Granollers, Catalonia, Spain 7 Ecosystems andEnvironment Research Centre (EERC), School ofScience, Engineering andEnvironment, University ofSalford, SalfordM54WT, UK