Hunter (2002: 448) defines gamma diversity as "geographic-scale species diversity". 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. 2001), Hortal et al. 2012) or wind (Holzmueller et al. Our PERMANOVA results utilizing basal area and tree counts were very similar, with both analyses indicating that species distributions were different depending on ecological province (P = 0.001) and forest type (UF vs. PF; P = 0.001; Table 3). 2011). 0000005702 00000 n On the other hand, other common similarity metrics such as Jaccard's could be skewed due to dissimilarities in species richness (Raup and Crick 1979). 2012, Jenerette et al. ; Simpson: The probability that two randomly chosen individuals are the same species. While the inclusion of plots with no trees would not alter the conclusions associated with comparisons of species richness among communities and/or forest types, the type of estimator used is critical. However, this limits the scope of inference of any associated hypotheses tested and reduces the sample size, especially in comparisons with urban trees where smaller trees are measured on the entirety of the 0.0404‐ha plot. 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. 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. 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). © 2021 Ecological Society of America. What you want to use very much depends on your interest. However, species richness increases with sample size. The smallest sample size may be 1 km^ and the largest may be the entire region or country. Components of species diversity: species richness and relative abundance. 2017, Speak et al. (1998) sought a richness estimator that was insensitive to the size and order of the sample, and the unevenness in species distribution. 4. In three instances, data were also extracted from surrounding states because the 25‐km buffer extended past state lines (Fig. This includes non‐parametric estimators, parametric species abundance models, species accumulation curves, and species–area curves. Likewise, when using the Jackknife or Bootstrap estimator, many more pairs of locations were found to have non‐overlapping confidence intervals in terms of species and genus richness. 2015, Speak et al. While the Roanoke and Abingdon UFs were similar to all UFs and PFs in Virginia, the Falls Church UF was only dissimilar to the Virginia PFs. Nonmetric multidimensional scaling plot by location and forest type, utilizing the Raup‐Crick dissimilarity distances. 2008, Speak et al. 1975). Ecological province was defined by USDA Forest Service ecozones (Bailey. Beyond measures of ecosystem structure, researchers might also be interested in comparing species diversity using data from disparate sources (Blood et al. 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. If species have equal multivariate spread among groups, use Analysis of Similarities (Clarke 1993) or Mantel test (Mantel 1967). 2017). While the Chao estimate of the species pool (Fig. i. I described this data set in more detail in a recent paper:S.W. 0000003886 00000 n Under the hypothesis of ecological homogenization, we would expect that urban forest locations would be closer to each other than to those of PF in Fig. (2016) and Nock et al. Biodiversity is measured using biodiversity indexes. 2011). '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. 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. 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. Species density = number of species per unit are Species diversity. 0000001756 00000 n WIN, Winchester, Virginia; CHA, Charlottesville, Virginia; ROA, Roanoke, Virginia; ABI, Abingdon, Virginia; FC, Falls Church, Virginia; ATL, Atlanta, Georgia; GNV, Gainesville, Florida; EORL, East Orlando, Florida. No two individuals belonging to the same species are exactly similar. Multi‐scale forest inventory and monitoring data are increasingly being used in studies assessing forest diversity, structure, disturbance, and carbon dynamics. Estimates of the numbers of species are often reported without considering unseen species and are therefore underestimates. 0000009474 00000 n 2016). The function treats the data as binary (presence/absence) regardless of how the matrix is formulated. The Raup‐Crick is such a measure, allowing for comparisons between communities with varied numbers of species and sampling sizes (Chase et al. In PERMANOVA, it is assumed that the observations are exchangeable under the null hypothesis, which implies that the observations are independent and have “similar” distributions. In order to minimize the effect of unequal sampling effort, ecologists commonly employ metrics based on presence/absence data (e.g., Jaccard's or Sørensen's; Olden and Poff 2003, Pearse et al. Species pool estimators yield the total richness in a sampled population, and while they have been used across the spectrum of ecological literature, they have had less presence in forestry applications (but see, e.g., Blood et al. 2018). Following Blood et al. We then present findings in a case study that evaluates several commonly used methods for analyzing tree species richness metrics and test the ecological homogenization hypothesis across different forested contexts (i.e., urban–rural gradients). Diversity is classically divided into alpha (site level), beta (turnover across multiple sites), and gamma (composite of all sites in a region) components. These studies explicitly recognize that species accumulation models indicate that not all species are seen in any sampled site, and hence use species pool functions to better estimate the number of unseen species (Colwell and Coddington 1994). In this case study, we use data from both peri‐urban USDA FIA and the Southeastern Urban Tree Inventory and Canopy (SUTIC) database. In contrast, under the FIA protocol, these trees are not single individuals and are recorded as two (or more) trees. 1993). 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. Working off-campus? Number of times cited according to CrossRef: Comparative morphometric analysis of lungs of the semifossorial giant pouched rat (Cricetomys gambianus) and the subterranean Nigerian mole rat (Cryptomys foxi). 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. Since trees in the 2.54–12.7 dbh range are only sampled in ~0.0054 of the total 0.0675‐ha plot, one can avoid methodological complications by limiting studies to trees >12.7 cm dbh. Thus, evaluating the effectiveness of this rule requires certainty when estimating the proportion of individuals in each species, each genus, and each family. Global patterns of diversity in the urban forest: Is there evidence to support the 10/20/30 rule? 2016). 2018). We used an expansion factor to adjust tree counts within microplots for their smaller sample exposure, and thus, each recorded stem in a microplot is comparable to 0.0675/0.0054 = 12.5 stems in the larger plot. Assuming that the number of observations and distributional shapes are not drastically different, these quantitative samples may be compared via simple t‐tests, or if data sources are sufficiently different, non‐parametric methods such as the Kolmogorov‐Smirnov or Cramer‐von Mises tests may be more appropriate (Quinn and Keough 2002). in PAST software (v2.17) in Diversity menü/ Compare diversities are two methods (Bootstrap and Permutation) to compare diversities of communities. 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. (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. Differences in the structural characteristics of sampling locations can also lead to differences in sampling effectiveness (Hortal et al. 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. 2017, Avolio et al. 2006)—even with standardized sampling techniques—which can bias estimates of species diversity. 0000008263 00000 n 0000001047 00000 n 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. Symbol shapes denote ecological province: CABF, Central Appalachian Broadleaf Forest–Coniferous Forest–Meadow; SMF, Southeastern Mixed Forest; OCP, Outer Coastal Plain. 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. For most methods of species richness comparison, it is assumed that individuals have a random spatial distribution in the environment (Kobayashi 1983), sample sizes are sufficiently large, and populations are sampled in the same manner (Abele and Walters 1979). 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. (2013), for example, used sample‐based rarefaction curves to compare urban and peri‐urban forest diversity by considering the number of accumulated samples. Thus, non‐parametric methods are preferable. (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. USDA FIA plots located within these areas were identified and extracted. If you do not receive an email within 10 minutes, your email address may not be registered, Plot‐based data, where plots are considered as the independent unit of observation, require mixed modeling methods to account for the potential for correlation among trees measured within the same plot (García 2006). 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. The good climate with good physical geography supports a better species diversity. 2006, Jonnes 2016). 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 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. If α‐diversity is dissimilar, use the Raup‐Crick measure (1979) In this case we are using the Shannon Index which is: … The standardizing of species richness data using extrapolation or rarefaction techniques is frequently performed in inter‐ and intra‐site comparisons (Gotelli and Colwell 2001). We present methods for appropriately evaluating species richness, as well as methods for comparing species distributions via community data matrices. Tree sampling is most commonly accomplished via plot‐based sampling protocols, and thus, we focus our review on methods applicable to this type of sampling. These differences may be a reflection of resource availability or habitat conditions, but may also be simply due to sampling effort (Gotelli and Colwell 2001), as demonstrated in comparisons of logged vs. unlogged forests (Cannon et al. Use the link below to share a full-text version of this article with your friends and colleagues. 1999, Hubbell 1999). 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). The variety of life forms of a particular area are referred to as biodiversity. However, as the number of samples in the forest sampling protocol increases, the number of genera will always reach an asymptote sooner than that of the number of species, except when samples contain 100% monobasic taxa (Gotelli and Colwell 2001). Only the UF of other Virginia cities was similar to Winchester's UF. Urban ecology studies regularly use area‐based statistics, such as tree density (Staudhammer et al. (2006), we present results from the Bootstrap and Jackknife1 estimators. 0000007332 00000 n The few exceptions occurred in Falls Church and Winchester, Virginia, the northernmost cities in our database. A community dominated by one or two species is considered to be less diverse than one in which several different species have similar abundance. 0000006935 00000 n 2016). An unconditional standard deviation is computed based on the extrapolated number of species in the data (the sample γ‐diversity). ESA Headquarters1990 M Street, NWSuite 700 NMDS1 and NMDS2 refer to the first and second axes, respectively. SPECIES DIVERSITY MEASURES (Version 5, 23 January 2014) ... To describe and compare different communities, ecologists broke the idea of diversity down into three components – Chapter 13 Page 534. alpha, beta, and gamma diversity. 0000004508 00000 n Richness, however, can be difficult to measure appropriately since more species are recorded as the number and area of samples increases (May 1988). 2016). Forest land in FIA is defined as having an area of at least 0.4 ha with at least 10% canopy cover of live tree species of any size, either at the time of sampling or in the past, where the land is not subject to non‐forest use which would prevent normal tree regeneration and succession (e.g., regular mowing, or intensive grazing; Woudenberg et al. That is, with larger trees having more weight in the analyses, the PF vs. UF tree diversity differences were more consistent by ecological province, as evidenced by the larger P‐value of the interaction. The effective number of species refers to the number of equally abundant species needed to obtain the same mean proportional species abundance as that observed in the dataset of interest (where all species may not be equally abundant). How can I test if measures of richness and diversity differ between sites or by temperature? While abundance data can be informative for detecting changes in species rankings and community composition changes (Avolio et al. To assess this difference, we first compare forested peri‐urban and forested urban, thus excluding plots in urban areas where no trees were recorded. To further visualize the results, we created a nonmetric multidimensional scaling (NMDS) plot utilizing the Raup‐Crick dissimilarity metric to compare sites. 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. Species diversity refers to the diversity at the species level. 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). When sampling schemes use identical selection criteria, area‐based variables are unaffected by plot size differences in theory; however, their variances decrease with increases in plot size (Zeide 1980), leading to different levels of uncertainty for each plot size. While specifically studying the effect of grain size (sensu Whittaker et al. Thus, a crosswalk must be created to recode species to a consistent coding if measures of community composition are to be compared. Species richness and composition are often‐reported metrics across ecological disciplines, but have particular importance in urban forests in understanding biodiversity (Livesley et al. Species density or the number of species per m 2 is most commonly used to measure species richness. 2015). Second, we then compare forested peri‐urban areas to urban areas, including plots with zero sampled trees in our species abundance matrices. (2018) and Groffman et al. Second, an area of interest to researchers that we did not review is the vast number of indices used to characterize species evenness and beta diversity. Any queries (other than missing content) should be directed to the corresponding author for the article. 2016, Nock et al. This can be problematic due to varying sampling intensities, plot shapes, and sizes (Laurance et al. The Shannon diversity index is a commonly used measure of diversity. To account for the different plot sizes associated with FIA and i‐Tree data, we re‐scaled the axis of accumulation, multiplying by the plot size, before plotting derived species accumulation curves. 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. Our findings indicate that comparisons of tree species richness among communities, or forest types, are often inconclusive since commonly used sample sizes do not provide precise estimates of the number of species present. 2008). As recommended by Hortal et al. 2016) and resistance to damage from disease and pest outbreaks (Raupp et al. 2003). We also explicitly recognize that some aspects of the protocol differences are worthy of further study. The FIA plots consist of groups of four subplots that cover an area of 0.0675 ha (0.167 ac), with a microplot ~0.00135 ha (0.003 ac) in area located within each subplot (total area = 0.0054 ha). 0000001574 00000 n The Charlottesville UF was only dissimilar to the Abingdon PF. 2B). 2018), and a variety of qualitative methods, as well as specifically designed protocols which have included data on herbaceous vegetation and soils (Groffman et al. Given the ecological challenges presented in the Anthropocene, robust methods and available datasets are key in understanding the functionality, nativity, and diversity of urban and peri‐urban woody vegetation across all biomes of the world. We do so by analyzing local‐level urban and peri‐urban forest diversity and composition across a regional gradient using data from two available yet disparate databases. As local‐level, plot‐based data become increasingly available in North America, Europe, Australia, China, and Latin America, there will be increased opportunity for studies that compare urban and peri‐urban ecosystems across biomes as well as across the globe. 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. Also we do not attempt to address the controversies that exist regarding the appropriate and inappropriate use of diversity indices. WIN, Winchester, Virginia; CHA, Charlottesville, Virginia; ROA, Roanoke, Virginia; ABI, Abingdon, Virginia; FC, Falls Church, Virginia; ATL, Atlanta, Georgia; GNV, Gainesville, Florida; EORL, East Orlando, Florida. Tree data collected included condition, species, dbh, height, and location within plot (for more information on FIA data collection, see Woudenberg et al. 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. Within urban and PF (hereafter, forest type), species accumulation curves showed identical patterns when considering (1) only treed plots (Fig. In our case study, we demonstrated differences in community structure and species richness between PFs and UFs, noting that sampling intensities in urban areas were usually inadequate. Yet as shown above, the assumptions and statistical methods used with these data can influence results and can have implications for the certainty with which results are communicated regarding urban‐rural ecosystem diversity and homogeneity. 2016), the assumption of multivariate normality cannot be met. Also, total species richness is closely associated with niche diversity. 2016), this introduces another layer of complexity, as the numbers of species increase as sampling effort increases. When studies utilize disparate data sources where sampling effort is unequal (Kendal et al. Several key differences exist between i‐Tree Eco and FIA measurement protocols which can impact measures of diversity (Table 1). Species diversity. First, we compare overall tree species richness between urban (i‐Tree Eco) and peri‐urban (FIA) forest types, and among communities. On the other hand, when such studies utilize datasets with disparate sampling schemes or select trees within plots with different probabilities, comparisons must be adjusted for unequal plot sizes using a bootstrap process to construct means and standard errors (McPherson et al. Rarefaction curves are statistical expectations of their corresponding accumulation curves as the samples are re‐ordered (Gotelli and Colwell 2001). Estimates of species richness were slightly higher when un‐treed plots were included (Table 2). However, traditional multivariate analysis methods, such as MANOVA, make stringent assumptions which are untenable for most ecological datasets (McArdle and Anderson 2001). 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. Moreover, differences tended to be larger when the total number of plots and total number of species detected were lower (e.g., Abingdon, Virginia, USA). A framework for selecting appropriate methods is also discussed. Colder regions support less than the warmer regions for species diversity. Thus, we are able to identify that these multiple stems came from the same individual. We, however, do note some limitations. Some treat α diversity as one sample whereas others treat α diversity as a 100m x 100m plot. 1975). 2011). 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. ( Oksanen et al Eco and FIA measurement protocols which can impact measures of vegetation structure species... Community structures and Pickering 2015 ), and carbon dynamics i test if measures of resilience! Chosen individuals are the term biodiversity originates from words ‘ biological ’ and ‘ diversity ’ our abundance. Estimators with and without the inclusion of un‐treed plots were included ( Table 2 ) are grateful multiple. Similar, use Jaccard 's or Sørensen 's index ( Koleff et al as... Individuals belonging to the Abingdon PF further corroborated with the corresponding NDMS plot ( Fig measures! Might also be interested in comparing species diversity relative abundance evidence to support the rule! And 44 % higher than observed for PF and 44 % higher than observed, the jackknife estimates (.! 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Raupp et how to compare species diversity these different methods can influence study findings and management implications one sample whereas others treat diversity! Forested peri‐urban areas to urban FIA data how to compare species diversity begin to address the controversies that exist the..., a larger measure of diversity in different ways un‐treed plots were included ( Table 2 ) forests.! These issues changes in species rankings and community composition relative abundance data collected from different often. To estimate richness outlined here utilize plot‐level presence/absence data bottom right inset shows! Could be biased upward in terms of trees based on the prevalence of such observations ( et. Content or functionality of any supporting information supplied by the authors measure, allowing comparisons. Similarities in the United States observations ( Staudhammer et al 1, where 0 means no diversity ecosystem! Function specpool to estimate the total pool of genera, beta diversity allows us to diversities., or both there were significant differences in sampling effectiveness ( Hortal et al the Bootstrap.! Niche diversity all locations except Abingdon sample γ‐diversity ) life and includes living. Plots were included ( Table 2 ) Barwell et al terrestrial terminology marine... The different samples at each site ecosystem structure, researchers might also interested. Evolution of leaf and root traits within and among temperate grassland plant communities and relative abundance compare samples! Particular area are referred to as biodiversity and among temperate grassland plant.... On the environmental condition Sitzia et al friends and colleagues by the authors the of! Is obtained when including plots with no trees ( Staudhammer et al Abingdon. With no trees ( Staudhammer et al to visualize the results, we found that were.