Species diversity measures, for example, can be used to better understand complex community structure and to develop practices to make forests resilient to disease, pests, and climate change. Numerical species richness = number of species per specified number of individual ii. Thus, a larger measure of uncertainty is obtained when including plots without trees in calculating the bootstrap estimator. If species have heterogenous dispersion, use PERMANOVA (Anderson 2001) Dissimilarity metrics: If α‐diversity is similar, use Jaccard's or Sørensen's index (Koleff et al. While no method is completely robust to these issues, alternative methods, such as rarefaction, can mitigate problems associated with violations in assumptions. ; Simpson: The probability that two randomly chosen individuals are the same species. Species density = number of species per unit are While species richness, measured or estimated, is a univariate characteristic of the total species pool at a site, the composition of such pools has also been a topic of research interest, for example, in quantifying the effect of forest composition change after disturbances such as logging (Imai et al. 2015). Species diversity is determined not only by the number of species within a biological community—i.e., species richness—but also by the relative abundance of individuals in that community. 2016). Groffman et al. Still, questions remain about how forest dynamics in rural contexts compare to those of urban environments (Blood et al. 0000005125 00000 n Using permanent plot data from the southeastern United States, we present a case study comparing urban and peri‐urban forests along a north–south gradient, and assessing species richness and the ecological homogenization hypothesis. 2008). Accordingly, rarefaction curves have allowed researchers to compare samples of different sizes through the calculation of expected richness at a standardized size (Heck et al. Observed and estimated peri‐urban (PF; FIA) and urban (UF; i‐Tree Eco) forest species richness by location including plots with zero tree counts (in urban areas only), utilizing (A) Chao estimator, (B) Bootstrap estimator, and (C) Jackknife estimator. We assess commonly used methods for comparing tree diversity in peri‐urban and urban forests when available data have different sample sizes, plot sizes, and sampling intensities. Nonetheless, Anderson and Walsh's (2013) simulation study showed that PERMANOVA was much less sensitive to heterogeneity in dispersions than ANOSIM and the Mantel test for balanced designs. 2016). We present methods for appropriately evaluating species richness, as well as methods for comparing species distributions via community data matrices. 2017). Only the UF of other Virginia cities was similar to Winchester's UF. 0000001346 00000 n (R code and sample data are available in Data S1.). How important are large vs. small forest remnants for the conservation of the woodland flora in an urban context? Blood et al. For example, in the species of human beings, each human shows a lot of diversity in comparison to another human. 0000003062 00000 n 2011). Since analyses were performed at a community level, analyses are identical with and without the inclusion of un‐treed plots. 0000009906 00000 n 1999, Hubbell 1999). Common alpha diversity statistics include: Shannon: How difficult it is to predict the identity of a randomly chosen individual. Although the conclusion that more sampling is necessary in order to encounter all species present in an area is reached in most urban locations, the implied sample area is more realistic when including these un‐treed plots. A uniform population of a single species of plants adapted to a particular environment is more at … 0000008804 00000 n If we have two sites with equal species richness, yet one site is dominated by a single species whereas a second site has a more even abundance of the species, then clearly we would consider the second as more diverse. By consolidating, formatting, and matching data sampled for different projects with different objectives, regional and international databases and clearing houses could be developed. 2014, Yang et al. Our results suggest that UFs and PFs were very similar within a particular region in the United States. (See Smith and Wilson 1996 and Anderson et al. Species Abundance = Relative abundance of species b. 2017). Species diversity is a term used to define the different number of species in an area (Species richness) and its abundance and the distribution of these species in that ecosystem. Richness is the number of species in each sample. 2015, Speak et al. (2016), we assumed that tree species were uniformly distributed across the 0.0675‐ha FIA plot sample area, but explicitly recognize the higher uncertainty associated with smaller trees not accounted for in this study. Species diversity refers to the diversity at the species level. However, we refer to these data with the name i‐Tree Eco hereafter. Estimates of the numbers of species are often reported without considering unseen species and are therefore underestimates. If you do not receive an email within 10 minutes, your email address may not be registered, We used the function specaccum, which uses as its default method the sample‐based (i.e., plot‐based) exact method to estimate an expected species accumulation curve via sample‐based rarefaction (Chiarucci et al. While a variety of species composition estimators have been used in the urban ecology literature (e.g., ANOSIM and the Mantel test; Oksanen et al. Often studies have used graphical techniques to visualize similarities in the structure of multiple communities (Sitzia et al. and you may need to create a new Wiley Online Library account. 2018). 0000005702 00000 n We can test hypotheses about the homogenization of species composition (Pearse et al. 2016, Yang et al. A community dominated by one or two species is considered to be less diverse than one in which several different species have similar abundance. 2006), If samples are heterogenous among sites, three estimators are recommended: incidence‐based Chao (Chao and Lee 1992), Bootstrap (Smith and van Belle 1984), and Jackknife1 (Burnham and Overton 1979), This study provides one of the first assessments of statistical methods that are being used in an increasing number of studies of woody plant diversity, homogenization, and functionality. However, sampling scheme is an important consideration; for example, convenience sampling was found to result in higher estimates of species diversity and more rare species, when compared to random sampling in an urban forest (Speak et al. Moreover, errors due to multiple stems only occur when splits occur below 0.3 m, and thus, we assume this error to be small. 2015). In our discussion, we then summarize a framework for selecting the most appropriate and available methodologies for analyses using these and other similar datasets. It takes into account both species richness and species evenness. Hunter (2002: 448) defines gamma diversity as "geographic-scale species diversity". While the ecological homogenization hypotheses can be tested under conditions of unequal sampling effort, we suggest robust methods such as PERMANOVA and the Raup‐Crick dissimilarity index. 2A) vs. (2) both treed and un‐treed plots (Fig. NMDS1 and NMDS2 refer to the first and second axes, respectively. (2008). Also, further information is needed on how the increasing use of available plot‐level data in both rural and urban forests can be used to address questions regarding ecological disturbance, functionality, and homogenization (Staudhammer et al. 0000001574 00000 n While further research is needed, we hypothesize that a more nuanced study including land use and the frequency of land‐use change (following Yang et al. For these kinds of studies, which inevitably involve larger areas, species density is a more applicable measure than species richness (Gotelli and Colwell 2010). Diversity is often quantified in terms of richness and evenness, as well as community composition. Within urban and PF (hereafter, forest type), species accumulation curves showed identical patterns when considering (1) only treed plots (Fig. Gotelli and Colwell (2001) recommended that raw richness only be compared if species accumulation curves clearly indicate that an asymptote has been reached in both populations of interest, highlighting the need for estimating total population pools. Corresponding Editor: Debra P. C. Peters. Simple comparisons, such as those concerning average tree size or number of species, are often not straightforward, even if adjustments are made for the amount of area sampled (Gotelli and Colwell 2001). Recently, disparate data sources have been used for regional‐scale and even continental‐scale urban‐to‐rural analyses of woody plant community composition, similarity, species richness, and other questions such as ecological homogenization and ecosystem dynamics (Blood et al. The use of available yet disparate national‐level and local‐level plot data, using different measurement and sampling protocols, would therefore need to assume that species are part of the same regional species pool. Species accumulation curves, rather than raw numbers of species, are necessary to make appropriate comparisons among communities and are commonly used to graphically display the total number of species encountered as the number of sample units is added to a pool of previously encountered species (Colwell and Coddington 1994). While these studies found evidence of homogenization across urban areas in the United States, their studies included a wider array of plant and taxonomic groups, rather than just being focused on trees. Second, we evaluate how these different methods can influence study findings and management implications. In addition to differences between i‐Tree and FIA protocols, there are differences in sampling intensity by tree size within the FIA data itself. Four cities were sampled across the Central Appalachian Broadleaf Forest ecological province, while two cities were sampled in each of the Southeastern Mixed Forest and Outer Coastal Plain Mixed Forest ecological provinces (Bailey 1995). First, our analyses were limited to data collected with two standardized methods. 0000007738 00000 n Regardless of forest type, estimated species richness was much higher than measured when considering the Chao and Jackknife estimators (Table 2). Following Blood et al. 0000009495 00000 n Plot‐based sampling requires different methods from those of individual‐based protocols (sensu Gotelli and Colwell 2001), as plots involve samples of multiple, grouped individuals as replicates, rather than single individuals (Speak et al. However, the axis of accumulation is stretched when considering the latter, and thus, comparisons of UF vs. PF are somewhat different. 0000003865 00000 n This field plot measurement and sampling protocol is increasingly being used in cities outside the United States as model input models to estimate urban forest structure and ecosystem services (Yang et al. 2012, Jenerette et al. (2014) investigated the role of parcel‐scale activities in driving homogenization of urban ecosystems across six metropolitan areas in the United States, with important implications for macroscale ecosystem services. species diversity using data from disparate sources (Blood et al. Similarly, data can be used to study the adequacy of human‐dominated landscapes in providing adequate habitat for native tree species and fauna (Livesley et al. 's (2008) protocol, where each tree or palm with dbh >2.54 cm was measured and its species name recorded within a 0.0404‐ha (0.1 acre) circular plot. They are related to, but not identical with, species–area curves, which are derived from island datasets (i.e., where different areas are associated with independently sampled islands). Since i‐Tree Eco species codes are comprised of the first two letters of the genus and species as well as other regional user‐created codes, the same species code can appear in different regions to represent multiple species. Colder regions support less than the warmer regions for species diversity. With the i‐Tree Eco protocol, multiple stems that originate (or appear to originate) from the same root stock and trees that split below breast height are recorded as single individual trees with multiple diameters. 1975). Figure 1 – Sample Index of Diversity. I described this data set in more detail in a recent paper:S.W. Also, local‐level urban forest inventories are providing plot data and protocols to study tree diversity and ecosystem services in urban forests worldwide. This has often been referred to as an assumption of equal “multivariate spread” among groups, which is a multivariate analog to the assumption of homoscedasticity in univariate ANOVA. 1975). © 2021 Ecological Society of America. For example, unequal sampling intensity of smaller trees in the FIA protocol requires development of a differential measure of uncertainty in richness and composition estimates. Evidence of such urban homogenization has been reported across major cities in the United States and China, with hypothesized continental‐scale consequences, including effects on carbon sequestration, microclimate, and other ecosystem properties (Groffman et al. If the hypothesis of ecological homogenization was supported, we would expect a different outcome for urban forests; species composition across urban communities would not be significantly different by province. Because richness does not in general increase linearly with abundance, simple adjustments, such as scaling the number of species per individual sampled, distort patterns in species richness (Gotelli and Colwell 2001). Species diversity is made up of two factors - the number of different species in an ecosystem and the proportion of each species in the ecosystem. (2018), who found that native and urban tree population realized climatic niches that had substantial overlap; in most cities we analyzed, we found similar species lists, though urban areas almost always contained more species. As species richness and evenness increase, so diversity increases. Main Difference – Genetic Diversity vs Species Diversity. 2016). Any queries (other than missing content) should be directed to the corresponding author for the article. 4). An ecosystem with a high level of biodiversity is more resistant to the environmental change and such ecosystems are rich in a variety of living organisms. Cahill, Jr. 2011. The choice of pool estimator is also important, and using the recommended bootstrap method with these kinds of sample types results in more conservative estimates of species richness, except where sampling intensity was high (e.g., Atlanta; Blood et al. 2016). Species diversity is a more complex measure of how many different types of taxa are present in communities. 0000006369 00000 n Genetic Diversity. 1982). This results in the use of exact equations, without simulations, which would not take into account the unequal efforts in sampling in the two types of data. 2017, respectively), as well as to test for differences among neighborhood species compositions within an urban region (Avolio et al. Species richness, as measure of diversity, has been used by ecologists. More recently, permutational analysis of variance (PERMANOVA; Anderson 2001) has been used to compare urban forests composition across geographic and urbanization gradients (Blood et al. Numerous studies have also sought to assess the performance of richness estimators across differing sites and/or sampling schemes (for a review, see Walther and Morand 1998), with the goal of finding methods to defensibly compare across sites. 2018). Other methods are available, such as the classic random method, which uses random permutations of the data (subsampling without replacement) to estimate species accumulation curves and their associated uncertainties (Gotelli and Colwell 2001), and the Coleman estimate (Coleman et al. If α‐diversity is similar, use Jaccard's or Sørensen's index (Koleff et al. Species Richness = an index based on the number of species i. 2014). (2016) and Nock et al. In the United States, this urban forest inventory and monitoring approach is known as the i‐Tree Eco protocol within the i‐Tree software suite, but is now being incorporated as part of the Urban FIA program (https://www.nrs.fs.fed.us/fia/urban/). Nonmetric multidimensional scaling is an ordination technique that finds the best rank‐order agreement between actual similarities and computed distances, representing a coordinate system in the ordination space (Fasham 1977). 2014, Staudhammer et al. 2016). We may, for example, explore questions about the development of novel ecosystem assemblages in the Anthropocene (Groffman et al. If species exhibit non‐random spatial patterns, such as within‐species clumping and segregation among species, which may occur with planted urban forests, estimates of species pools can be overestimated in small samples, and knowledge about spatial autocorrelation has not been found useful in correcting bias (Collins and Simberloff 2009). 0000003242 00000 n Forest composition and tree species diversity have been recognized as primary drivers of ecosystem resilience and function (Jenerette et al. While specifically studying the effect of grain size (sensu Whittaker et al. 2006), and to compare species composition of forest remnants in urban areas (Godefroid and Koedam 2003). 2014). Also, it’s difficult to transfer terrestrial terminology to marine systems. Measuring diversity: the importance of species similarity Tom Leinster 1,2∗ Christina A. Cobbold 1School of Mathematics and Statistics, University of Glasgow, UK 2Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, UK Abstract Realistic measures of biodiversity should reflect not only the relative abundances of However, species richness increases with sample size. (2006) recommended the use of several widely studied (Chiarucci et al. Studies across the globe are beginning to use available, but disparate datasets to better understand urban ecosystem dynamics and to make analyses and inferences regarding regional‐ to continental‐scale woody vegetation diversity, composition, and ecosystem functionality (Kendal et al. 2015), FIA plots are exclusively installed on forested land as defined by the USDA, and explicitly must include trees. We utilized PERMANOVA via the R function adonis to better understand community similarities and dissimilarities. Nonetheless, comparisons between these datasets will become increasingly important to better understand how anthropogenic impacts affect urban and peri‐urban forest structure, diversity, and even ecosystem services across multiple scales, regions, and continents. Since different sampling strategies are often used to assess species richness across regions, Hortal et al. Having outlined the available methods, we now present a case study as an example of how commonly utilized methods can be applied to disparate data sources addressing urban–rural ecology questions across different scales. But, for most of the sites sampled, urban forests and their peri‐urban counterparts are fairly close, indicating low values of dissimilarity, and therefore indicating a lack of urban homogenization. To further visualize the results, we created a nonmetric multidimensional scaling (NMDS) plot utilizing the Raup‐Crick dissimilarity metric to compare sites. Since FIA plots are measured on a cyclic basis, we obtained data measured in the years 2010–2013 for Virginia and 2009–2013 for Georgia and Florida to obtain the maximum number of tree measurements while excluding re‐measured trees. When plots are of different sizes, these methods are still valid, but weighting schemes may be appropriate in certain situations (Schreuder et al. 2016). Thus, beta diversity allows us to compare diversity between ecosystems. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist, A framework for quantifying the magnitude and variability of community responses to global change drivers, Biodiverse cities: The nursery industry, homeowners, and neighborhood differences drive urban species composition, Description of the ecoregions of the United States, Differences in the impacts of formal and informal recreational trails on urban forest loss and tree structure, Measuring β‐diversity with species abundance data, How do urban forests compare? 2003) “classical” estimators: the Abundance‐based Coverage Estimator (Chao and Lee 1992), the Abundance‐based Chao Estimator (Chao 1984), Bootstrap (Smith and van Belle 1984), Jackknife1 (Burnham and Overton 1979), and Jackknife2 estimators (Smith and van Belle 1984). This data set consists of data on the occurrence of grassland plants at several different sites in Alberta, along with information on their functional traits and phylogenetic relationships. Differences in the structural characteristics of sampling locations can also lead to differences in sampling effectiveness (Hortal et al. 1998, Hou et al. Bottom right inset map shows the study region within the United States. Just remember to compare like with like. 2012). It takes into account both species richness as well as the dominance/evenness of the species. Species diversity is a combination of species richness and species abundance. However, the method is somewhat sensitive to differences in relative dispersion of points among groups. What you want to use very much depends on your interest. 2016), simulation studies recommend the use of PERMANOVA to account for heterogeneity that may be exacerbated by differences among sampling intensities (Anderson and Walsh 2013). Vegetation structure, species diversity, and ecosystem processes have responded rapidly to planting. For example, Chazdon et al. To evaluate this commonly applied guideline, urban forests need to be assessed to test if they contain no more than 10% of any tree species, 20% of any genus, and 30% of any family. But, differences in the sampling methods underlying these disparate protocols and data sources is a non‐trivial concern in formulating comparative analyses. We found, as expected, that estimates of species pools were most variable where the total number of samples and species detected were low. As natural landscapes are altered by urbanization, such comparisons allow us to fill gaps in our scientific understanding of the dynamics of urban‐to‐rural gradients and ecosystems. The function treats the data as binary (presence/absence) regardless of how the matrix is formulated. Using a matrix of comparisons between all pairs of associations, the Raup‐Crick index compares observed numbers of species with the distribution of co‐occurrences generated from 999 Monte Carlo random replicates (Chase et al. But a study across climate and land use revealed that these targets are rarely met at the species level (Kendal et al. 2015). 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