Estimating the potential biodiversity impact of redeveloping small urban spaces: the Natural History Museum’s grounds

Introduction

Urbanisation has increased globally and will continue to do so (Heilig, 2012). Urban expansion has resulted in the widespread loss, both directly and indirectly, of natural and semi-natural habitats which are important as refuges and corridors for biodiversity (Goulson et al., 2002; Osborne et al., 2008) and for human well-being (Fuller et al., 2007; Dallimer et al., 2012; Bratman et al., 2015; Shanahan et al., 2016). Any retention or creation of green-spaces within urban areas is therefore considered important (Alvey, 2006, but see Deaborn & Kark, 2010).

Urban ecology has become increasingly popular over the last decade (McPhearson et al., 2016). Several UK-based projects have assessed urban biodiversity (Gaston et al., 2004; Angold et al., 2006), investigating how it can be maintained and improved. Communicating the benefits of urban gardens and public spaces can result in enhanced biodiversity potential (e.g., Thompson, 2007).

The Natural History Museum, London, is a popular attraction, with around five million visitors per year—a number that is expected to increase. In part to alleviate the pressure of such large visitor numbers on the two current entrances, a third entrance through the Darwin Centre, at the west of the building, has been proposed. In order to comply with local council requirements for a unified theme between the museum building and the grounds (See Text S1 for further information), the proposed plans contained an overarching continuous theme similar to that of the museum building itself, moving from “extinct” habitats in the east to current British habitats in the west (Fig. 1B). The plans as proposed will result in the loss and reduction of some habitats within the grounds, gain and expansion of others, and disturbance particularly in the eastern part of the grounds. The proposed changes prompted concerns for the wildlife currently inhabiting the grounds, especially in the Wildlife Garden (henceforth WLG) in the southwestern corner of the site (Knapton, 2015; Prospect, 2015; Doward, 2015; Duell, 2015; Marren, 2015): a petition to stop the redevelopment of the grounds attracted over 37,000 signatures as of 1 June 2016 (Weiler, 2015).

Among the arguments used by critics of the proposals is that the grounds harbour unusually high levels of biodiversity (Weiler, 2015), which would be jeopardised by the proposed changes to the grounds (Marren, 2015). However, few quantitative tools exist to assess the levels of biodiversity within the grounds currently, and how it might change as a result of the redevelopment. Over 2,800 species have been recorded from the WLG in the 21 years since its creation, in occasional structured surveys and more haphazard observations (Ware et al., 2016). Despite species having been recorded since 1995 when the WLG was created, new species continue to be added to the cumulative list of taxa recorded (see Text S1 for additional information). However, lengths of lists of recorded species can only be compared meaningfully across sites if sampling effort has itself been recorded or, better yet, been equal at each site; otherwise, lengths of lists typically conflate differences in sampling effort with true diversity differences (Gotelli & Colwell, 2001; Crawley, 2005). For example, assiduous sampling led to 2,204 species of plant and animals from selected groups being recorded over 15 years from a domestic garden in Leicester (Owen, 1991). Because species in many high-diversity taxonomic groups, such as insects or other invertebrates, can often be differentiated only by taxon specialists, taxonomic expertise can also influence lengths of species lists (Crawley, 2005). The Natural History Museum provides one of the greatest concentrations of such expertise in the world, meaning the list of species from the WLG is likely to be more comprehensive than those from almost anywhere else on earth. In addition, it is not possible to determine how lengths of species lists will change over time.

The most accurate prediction possible of the effects of a redevelopment such as this would be obtained by extensive standardised ecological sampling of the site to provide a precise estimate of current biodiversity, together with similar sampling of nearby patches of any habitat types that would be added as a result of the redevelopment. However, planning decisions are usually based on much less detailed information than this.

An independent ecological assessment of the biodiversity value of the WLG, done as part of a planning application, suggested that, apart from breeding birds, a number of invertebrates and the accidental introduction of a slow worm, “No other protected or noteworthy species were considered likely to be supported within the site” (The Ecology Consultancy, 2015a; The Ecology Consultancy, 2015b), although some protected species (common and soprano pipistrelle bats) had been seen foraging in the garden. These findings are in line with expectations for young anthropogenic habitat patches in an urban setting. However, as with the lists of recorded species, this assessment did not provide any quantitative estimates of diversity that could provide the basis of a comparison between the biodiversity of the current grounds and that expected or (in future) found under the new proposal.

Few robust tools are available to estimate potential impacts to biodiversity from development and land-use change, especially at such small spatial scales. For planning applications it is advised, although not always a necessity, that ecological surveys (desk-based or field-based surveys as part of a Preliminary Ecological Assessment and/or an Ecological Impact Assessment) be conducted prior to submission to determine, amongst other things, how species and habitats at the site might be impacted by the proposed works (CIEEM, 2016). However, especially with desk-based surveys, these methods would be unable to estimate the likely gains or losses of biodiversity until after the fact. DEFRA’s Biodiversity Offsetting model (DEFRA, 2012) offers a potential way of assessing potential impact on biodiversity via the habitat types that are to be displaced: briefly, each habitat type carries a distinctiveness score (2, 4 or 6), each patch is assigned a condition score (1, 2 or 3), and these are multiplied together to calculate a per-hectare biodiversity score which is multiplied by the area of the habitat patch and summed across all patches to give an overall biodiversity score. For increased or new areas of biodiversity-rich habitat, scores are moderated to reflect the time needed to achieve the target level of biodiversity and the risk that it will never be reached. In order to prevent net loss of biodiversity, the score of the proposed habitat types would need to match or exceed the score of the habitats being displaced. Although operational, this offsetting method falls short in urban environments (habitats are presumed to be in a natural setting), and the scores are not strongly grounded in relevant biodiversity data (see Baker et al., 2014).

A common approach in conservation ecology to the problem of estimating the effects of land-use change on biodiversity is to undertake comparable ecological surveys at nearby sites in different land uses, under the assumption that such spatial comparisons can be used in lieu of time-series data tracking biodiversity through land-use changes. Although no such data have been published from within the WLG itself, such comparisons are sufficiently common to permit powerful global syntheses (e.g., Alkemade et al., 2009; Gibson et al., 2011; Gerstner et al., 2014). In particular, the PREDICTS project has modelled data from surveys worldwide to estimate how land-use change and related pressures affect occurrences and abundances of many species (Newbold et al., 2014; De Palma et al., 2015) and broader site-level measures of biodiversity (Newbold et al., 2015; Newbold et al., 2016; De Palma et al., 2016). By focusing on surveys that have included sites in different land uses, this approach is able to estimate relative levels of biodiversity for each land use type, even if no single survey represents the full range of land uses. By empirically describing the relationship between pressure data and the response of biodiversity, (i.e., using a dose–response modelling framework: Pereira et al., 2010), the model can be combined with projections of future pressures (e.g., land use) to estimate average levels of site-level biodiversity in the future, enabling comparison with the present (Newbold et al., 2015). The PREDICTS framework is therefore designed to tackle similar kinds of question to those posed by the museum’s grounds redevelopment, such as, will the development cause a negative effect on biodiversity over the long term?

Given this conceptual similarity, aware of the controversy surrounding the biodiversity costs and benefits of the proposed development, and having no involvement in either the conception of the proposal or the opposition to it, two of us (HRPP and AP) offered to undertake an analysis for the Natural History Museum, conceptually derived from that of Newbold et al. (2015), to estimate the net effects of the proposal on biodiversity and to make the resulting estimate public. The proposal was accepted by the Natural History Museum, on a short three-month timescale. SK, already involved in the Grounds Transformation Project, joined the analysis and provided detailed information about the current and proposed layouts of the grounds, as well as facilitating access to the dataset of species recorded from the various habitats within the WLG.

Our aim was to provide quantitative estimates of biodiversity metrics in the current NHM grounds and the corresponding values following the redevelopment. In estimating the biodiversity consequences of the proposed redevelopment, we are also aiming to develop a decision-support approach that, while undoubtedly less accurate than extensive bespoke ecological surveys, provides estimates that are quantitative, transparent and data-based in a reasonable time and at a reasonable cost. We extended the analytical framework developed by Newbold et al. (2015) to allow for the fact that the spatial extent of a habitat, as well as its type, is likely to affect its biodiversity value. Larger habitat patches are expected to contain not only more species overall than smaller patches (in line with the species–area relationship: e.g., Rosenzweig, 1995; McKinney, 2008), but also—though less strongly—more species per unit area (i.e., the species density-area relationship: Phillips et al., in press). Our analysis aims to take such area-dependency into account. Many other factors can also affect site-level diversity, notably habitat age (Sattler et al., 2010), edge effects (Murcia, 1995), vegetation structure (Threlfall et al., 2017), and habitat connectivity (Shanahan et al., 2011). We return to these in the discussion, but time constraints (in order to report in time to feed into the planning application) and limited data availability precluded their consideration in this study.

Methods

Results

Meta-analysis

The first literature search returned 101 articles and the second found 1,158 articles. Further targeted searches acquired data from an additional five articles. Based on the data criteria, only data presented in 11 papers were suitable for modelling; these were collated into 14 studies based on methodology. These studies contained sampled sites from across the UK (Fig. 2), as well as two studies in Canada (to allow a comparison to green roofs: MacIvor & Lundholm, 2011), and included suitable data we were able to access from the WLG database.

The fixed effects of the mixed-effects model of species density (per 10 m²) were simplified by the removal of the additive effect of taxon (χ² = 0.90, d.f. = 1, p-value = 0.34). Species density (per 10 m²) varied significantly between habitat types (χ² = 353.18, d.f. = 12, p < 0.01; Fig. 3). Chalk grassland had the highest species density (per 10 m²), whilst pond and fen had the lowest among habitats for which sample-based data were available.

Similar to the species density model, the model of within-sample species richness was also simplified with the removal of the additive effect of taxon (χ² = 3.29, d.f. = 1, p-value = 0.07). Species richness significantly varied among habitat types (χ² = 468.01, d.f. = 12, p < 0.01; Fig. 3). The relative diversity of each of the habitats was largely consistent among the two models.

Calculations for all three assumptions indicate an overall net increase in local biodiversity with the proposed plans for the museum’s grounds. Assumption 1 yields an increase of 11.17%. Under Assumption 2, the increase is estimated to be 13.20%. Assumption 3 gave the greatest increase (14.05%) in overall net biodiversity under the proposed plans.

Sensitivity analysis

When the analysis was repeated 1,000 times, taking the habitat coefficients from a distribution, the proposed plans only resulted in a net loss of biodiversity in 0.4% of the trials under Assumption 1 (Fig. 4) and never did so under Assumptions 2 and 3 (Fig. S5).

WLG species similarity

Most habitats had very similar plant species composition (Fig. 5), though there were exceptions. For example, very few species from other habitats were found in amenity grass/turf but nearly all species in amenity grass/turf were in most other habitats. Unsurprisingly, ponds had a highly dissimilar collection of species to every other habitat.

Discussion

The findings of this meta-analysis indicate that the proposed plans for the museum grounds are expected to result in a net gain of local biodiversity. This increase in biodiversity is beneficial, not only to ease concerns of those that suspect diversity to be lost with the proposed grounds renovations (Weiler, 2015; Marren, 2015), but also as even a small increase in species richness in urban greenspaces has the potential to increase human wellbeing (Fuller et al., 2007; Shanahan et al., 2016). This increase in biodiversity arises because habitats with the highest modelled species density, such as chalk and neutral grassland, will increase in area under the new plans; and because new habitats will be introduced. These findings are similar to those of earlier studies; for instance, a previous synthesis of findings from studies worldwide investigating biodiversity in urban parks found that increasing the habitat area and habitat diversity usually increased species richness (Nielsen et al., 2014). Both area and number of habitats are likely to be important determinants of biodiversity, and potentially it would be more appropriate to incorporate them within a single model (e.g., the Choros model: Triantis et al., 2003).

Broadleaved woodlands and neutral grassland contribute greatly to the grounds’ current biodiversity value, and will increase in extent under the proposed plans. As broadleaved woodland will be among the least disturbed habitats during the renovation process, this high-biodiversity-value area may harbour source populations for some of the other habitats, especially considering the relatively high proportion of shared plant species in all the other terrestrial habitats.

The statistical methods used in the analysis rely on species diversity modelled as comparisons between habitats that are present in the grounds currently or under the proposed plans. In this case it resulted in a relatively small sample size (14 studies from 11 papers), which was adequate for the model structure employed (i.e., models converged with acceptably narrow confidence intervals). This facilitates comparisons among the fully terrestrial habitats, where sampling methodologies are more likely to be consistent, but there are unsurprisingly few studies that use a consistent methodology between any fully terrestrial habitat and an aquatic habitat. Thus, the modelled coefficients for ponds are likely to be the least reliable in our analysis, as they are estimated from one comparison against reeds (Williams, Whitfield & Biggs, 2008). However, as ponds make up only a small area of both the current and the proposed grounds (see Fig. 1), this will have little impact on the grounds’ overall biodiversity value. Previous work has shown that diversity often increases with pond area (Oertli et al., 2002; Parris, 2006) and pond perimeter (Gagné & Fahrig, 2007; Gagné & Fahrig, 2010). With the ponds increasing in area under the proposed plans this may result in a relative increase in species richness compared to the current grounds. However, the proposed plans will reduce the extent of the pond’s hard edges. Therefore, additional planting of marginal vegetation could increase the perimeter, whilst also increasing diversity (Williams, Whitfield & Biggs, 2008; Gioria et al., 2010).

The measures of biodiversity that we have modelled—species density and within-sample species richness—are pragmatic choices given the data available, but may not fully reflect desired features, such as the diversity of rare or charismatic species. Additionally, it is not possible to assess how communities within, and between, habitats might change (e.g., changes in the abundance distribution, or a shift to communities dominated by more widespread species). Capturing changes in beta diversity (i.e., spatial turnover) would allow the assessment of whether additional habitats are increasing the diversity of the grounds as a whole. Adding new habitats may not add species that are not already present in other habitats within the grounds, especially within an urban environment where habitats may not be as high-quality as in rural areas, (Crooks, Suarez & Bolger, 2004). Methods exist that analyse changes in community composition (such as Sørensen’s similarity index; Magurran, 2004), which are much more sensitive than species richness to compositional change (Hillebrand et al., 2017); however, data extracted from papers suitable for this study often lacked diversity measures at the species level, therefore the use of such methods was not possible. In addition, we were unable to use rarefaction or abundance based metrics, as the numbers of individuals of each species were not known. However, with more detailed data, these metrics would provide an interesting avenue for future studies.

Other limitations and assumptions made in the analysis might also impact the results. In the calculations for the area-scaling of species density, habitat is assumed to be contiguous. Habitats are more contiguous in the proposed plans than in the current grounds, meaning that the proposed plans are disadvantaged in our comparisons. We focused on invertebrates and plants; although these are potentially the most appropriate taxa given the small size of the museum grounds, we would have liked to be able to also infer the response of vertebrates.

One of the main objections to the proposed renovation plans voiced by members of the public and other stakeholders is the level of disturbance that will be caused across much of the grounds and the potentially negative impact this will have on biodiversity. We had aimed to address this point by modelling how habitat age influences biodiversity but there were insufficient data for this analysis. In more natural settings, previous work has established that it can take many decades (Hirst et al., 2005)—even a century or more (Vellend et al., 2006)—for biodiversity to reach pre-disturbance levels. In urban settings, biodiversity is known to increase with habitat age (Yamaguchi, 2004; Sattler et al., 2010) and age of the surrounding city (Aronson et al., 2014). However, as diversity levels are typically lower than those of natural habitats (Öckinger, Dannestam & Smith, 2009; Bates et al., 2011), the time needed to recover could be considerably shorter. Considering that the WLG is only 20 years old, it is unlikely the current biodiversity levels have reached equilibrium. Even if they have, the community composition is likely to be different from that of habitats in more natural settings (Angold et al., 2006).

Post-disturbance natural colonisation may be the main source for biodiversity recovery, and thus an important determinant of dynamics will be the connectivity of the museum grounds to potential source pools. Many studies have suggested that connectivity within an urban environment is important in maintaining biodiversity (Öckinger, Dannestam & Smith, 2009; Goddard, Dougill & Benton, 2010; Kong et al., 2010; Vergnes, Le Viol & Clergeau, 2012). However, an earlier study (Angold et al., 2006) reported that landscape variables, such as habitat connectivity, were less important than local site-level variables, such as site age or habitat size, for invertebrate communities in urban environments. This dichotomy of results could be due to the mobility of the studied taxa (Braaker et al., 2014), with highly mobile species benefiting from connectivity in the landscape more than less mobile species. Trait-based statistical models provide a possible approach to testing this possibility (e.g., Öckinger et al., 2010; Lizée et al., 2011).

Given the fragmented nature of urban landscapes, expectations of additional factors that could impact site-level diversity can be drawn from fragmented natural systems. In natural systems among the best-studied pressures associated with fragmentation are edge effects (disturbance from the surrounding matrix penetrating the habitat fragment; Murcia, 1995). Depending on the taxa studied, the impact from fragment edges can extend into the habitat fragment between 10 m and 2 km (Broadbent et al., 2008), potentially reducing the diversity (Soga et al., 2013) or increasing diversity with the movement of matrix species into the habitat fragment (Ewers & Didham, 2006). The lack of fragmentation data (e.g., data on the distance to the edge of the fragment) in the primary literature meant that we were unable to analyse this aspect. However, as the habitat areas within our studies from the primary literature were small (range = 7–6,250,000 m², median = 1,497 m²; a range that largely overlaps the habitat areas in the current and proposed grounds), our sampled diversity estimates are already likely to have been impacted by edge effects (Soga et al., 2013). Therefore, although potential effects from habitat edges should ideally be tested and if appropriate incorporated into future modelling frameworks, in the context of this study the effects on the comparison between current and proposed grounds may be small.

Other factors that could impact site-level diversity relate to the landscape context, such as the similarity of the matrix habitat to that of the fragment (Ruffell, Clout & Didham, 2017) and the amount of similar habitat within the surrounding landscape (increasing the area from which colonists can arrive: Shanahan et al., 2011). The effects of these two factors, as well as the impact of edge effects, will differ between species. Meta-analytical studies, such as ours however, rely on the data presented within the original articles. In this study, none of the original studies provided quantitative data on these aspects of landscape context that could be meaningfully compared across different studies.

Although our results are unlikely to be directly transferable to other case studies, the broad methodology could be useful in many other similar situations. Depending on available data, it may be possible to incorporate into models more of the factors detailed above. Doing so will be especially important if the landscape is becoming more fragmented following disturbance, such that area and edge effects (amongst others) might be reducing biodiversity more than expected in our study. By extending the methods of previous biodiversity models that investigate the impact of land use change on biodiversity (e.g., Newbold et al., 2015), the site-level results can be useful to a single decision-maker for a smaller-scale project, especially in relation to planning outcomes. Estimating the long-term impact that disturbance and renovations might have on biodiversity prior to any undertaking can be valuable, especially when results can directly feed into plans and actions to prevent or offset declines in biodiversity. Although other models exist that assess the potential impact on biodiversity of habitat change and loss (e.g., DEFRA, 2012), meta-analytical methods, such as these, provide empirical and transparent results.

The redevelopment of the Natural History Museum’s grounds provides the opportunity to monitor aspects of biodiversity recovery within an urban environment that have previously been little studied, whilst validating the results found in this study. Establishing long-term ecological sampling within each of the grounds’ habitat types would allow more detailed assessment of the recovery of the disturbed habitats as well as the colonisation of the newly created habitats. Standardising the sampling, in conjunction with other projects, would also allow the further comparison of the results with other areas within London (e.g., Smith, Chapman & Eggleton, 2006) or the UK more broadly (e.g., BUGS2 project: Loram et al., 2007). Long-term regular sampling would also provide the opportunity for other hypotheses to be rigorously tested, for example, whether reduced connectivity in urban areas increases genetic differentiation between populations (Johnson, Thompson & Saini, 2015). Of course, with the grounds being an integral part of the Natural History Museum they provide unique opportunities for the monitoring to be undertaken not only by the taxon experts on museum staff but also by members of the public (Silvertown, 2009; Roy et al., 2012), not only reducing costs but also increasing public engagement in and participation in science and awareness of the new grounds and urban biodiversity in general.

Urban green areas face many threats worldwide. Without robust methods for estimating the consequences for biodiversity, planning decisions run the risk of being uninformed or misinformed. We show how a global modelling approach can be downscaled to inform local decision-makers about the likely impact of habitat change on species richness and species density. In the case of the Natural History Museum, London, the proposed changes to the grounds are predicted to result in a net gain of biodiversity, due to increases in the number and areas of habitat types. The size of the gain depends on the assumptions made about the relationship between within-sample species diversity and habitat area—a relationship that has hitherto largely been ignored in global models. The grounds redevelopment program provides an opportunity for systematic ecological surveys to quantify the effects of habitat creation, expansion, reduction and disturbance in the future, adding useful knowledge about this culturally important urban green space at the same time as allowing improvement of biodiversity models to support planning decisions.

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