Editorial: Last Post

This is the last post (for the foreseeable future) for the "Science Corner" Coral Reef Review. This blog will remain up as an archive to articles reviewed already. I chose to conclude these reviews because I think they've served their purpose: getting a couple semesters worth of reviews of [mostly] coral reef literature in a manner accessible to educated laypersons but technical enough for graduate students. I hope that everyone who's stumbled across this blog has enjoyed their time here. Thank you for reading.

For those looking to further their coral reef biogeography expertise, I recommend the following papers in addition to the ones reviewed over the last few months.

DOWNLOAD * Fredericq, Phillips, Gavio (2000) Observations on the macroalgae communities inhabiting in the northwestern deep-water hard bank Gulf of Mexico. Gulf of Mexico Science, 2:88-96.

DOWNLOAD * Hommersand (1986) The biogeography of the South African marine red algae: a model. Botanica Marina, 29:257-270.

DOWNLOAD * Santelices, Bolton, Meneses (3007) Marine algal communities. In: Witman, Roy (Eds.) Marine Macroecology. Chicago University Press, Chicago IL USA.

DOWNLOAD * Kerswell (2006) Global biodiversity patterns of benthic marine algae. Ecology, 87(10):2479-2488.

DOWNLOAD * Pielou (1977) The latitudinal spans of seaweed species and their patterns of overlap. Journal of Biogeography, 4(4):299-311.

DOWNLOAD * La Ferla, Taplin, Ockwell, Lovett (2002) Continental scale patterns of biodiversity: can higher taxa accurately predict African plant distributions? Botanical Journal of the Linnean Society,138:225-235.

DOWNLOAD * Santos, Cavalcanti, da Silva, Tabarelli (2006) Biogeographical relationships among tropical forests in north-eastern Brazil. Journal of Biogeography, 34(3):1-10.

DOWNLOAD * Grehan (1993) Conservation biogeography and the biodiversity crisis: a global problem in space / time. Biodiversity Letters, 1(5):134-140.

DOWNLOAD * Grehan (1992) Biogeography and conservation in the real world. Global Ecology and Biogeography Letters, 2(3):96-97.

DOWNLOAD * Price (2002) Simultaneous 'hotspots' and 'coldspots' of marine biodiversity and implications for global conservation. Marine Ecology Progress Series, 241:23-27.

Review: Price, Vincent, Venkatachalam, Bolton, Basson (2006) Concordance between different measures of biodiversity in Indian Ocean macroalgae. Marine Ecology Progress Series, 319:85-91.

Feature Paper: DOWNLOAD * Price, Vincent, Venkatachalam, Bolton, Basson (2006) Concordance between different measures of biodiversity in Indian Ocean macroalgae. Marine Ecology Progress Series, 319:85-91.

Author Abstract: We examine relationships between species richness (S), rarity (R) and average taxonomic distinctness (Δ+) from analysis of a comprehensive dataset for benthic marine algae (including Cyanophyta). This comprises 2894 species from 66 sites across the Indian Ocean. Ranked values for the sites, determined according to the 3 metrics, show significant positive correlation (p ≤ 0.01); Mauritius, India and Aldabra emerge as biodiversity ‘hotspots’, while Indonesia (Nias Island), Maldives (Male Atoll) and the Gulf of Aden are ‘coldspots’. Concordance between metrics was unexpected, given their disparity in robustness to sampling rigour and particularly since Δ+ is conceptually unrelated to S and R. Lack of significant latitudinal correlations was also evident except for Δ+, which increased towards temperate waters in the southern hemisphere. This contrasts with the variable patterns observed with longitude, for which significant correlations (negative, i.e. towards the west) were prevalent only for S (algae overall and separate categories except Phaeophyta), evident for R (Cyanophyta only) and absent for Δ+. Hence, use of one floral category as a surrogate for biodiversity in another is not guaranteed. Aquatic biodiversity patterns are complex, in accordance with recent findings derived mainly from faunal datasets. Relationships between different metrics can depend on both the group(s) selected and the environmental or geographical factor(s) examined. Our study is based on analysis of extensive but low resolution (presence/absence) data (Silva et al. 1996) collected from sites of variable size that were not sampled evenly. We address these constraints, but acknowledge the possibility that some patterns may prove to be artefacts, pending analysis of data from recent and ongoing studies. However, we do not expect this to significantly affect our overall conclusions.
 

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Today's paper is the last of this week's survey of marine algae. Like the previous two papers, it looks at taxonomic diversity other than mere species richness, which is most common. This paper looked at 66 sampling locations throughout the Indian Ocean and examined 2894 species of marine algae among five major taxonomic groups. 

The authors examined species richness, rarity (as a function of range size and not abundance), and average taxonomic distinctness. The authors chose rarity because "unlike endemism it is relatively unaffected by spatial scale." The authors ranked values in each metric and determined "hotspots and coldspots of marine algal biodiversity," revealing "Mauritius, India and Aldabra as the sites of highest diversity [with] Indonesia (Nias Island), Maldives (Male Atoll) and the Gulf of Aden as the sites of lowest diversity." Look to the full paper for the complete list of rankings though some obvious disparities (from sampling effort) are apparent, with for example Kuwait and Iraq having widely varying values even though their coastlines are relatively the same and they are geographically adjacent.

The authors also examined latitudinal and longitudinal diversity patterns, noting that "significant negative correlation with longitude was evident for algae as a whole as well as for Cyanophyta, Rhodophyta and Chlorophyta [corresponding] with generally higher values of species richness in regions within 30 to 80ºE, and with lower values further east within 80 to 120ºE. Only Cyanophyta showed significant correlation (negative) with longitude [for rarity]. Average taxonomic distinctness showed significant correlation (negative) with latitude only for Phaeophyta, equating to an increase towards temperate waters in the southern hemisphere while for longitude no significant association was evident."

One problem the authors found was that for algal data, uniform geographical data are seldom available, with many sites at political levels and they had to log-transform site coastline lengths because of large variation. As a result, species richness was "highly sensitive to uneven sampling areas and effort, even though our computations of species richness attempted to standardize for area disparities."

The authors found that all three metrics "showed strong concurrence in terms of ranking sites as biodiversity hotspots and coldspots." Unlike corals and reef fishes, which we examined last week, there was a "virtual absence of significant latitudinal correlation for all 3 metrics, in contrast to the variable patterns observed with longitude, suggesting that relationships between different biodiversity measures in marine floras may not be straightforward."

One significant conclusion (echoed by the previous two papers) is that algae should probably not be grouped together as a whole, as the authors note that "algae and seaweed are ecological and not taxonomic terms," with the wide differences in seaweeds discussed previously this week. The authors did find stronger longitudinal correlations than latitudinal ones though, with the western Indian Ocean perhaps more diverse than the eastern Indian Ocean (the opposite is generally true for fishes and corals, with the exception of a minor peak in diversity in the Red Sea for those groups). 

Hopefully these three papers enlighten a bit more about algae and consider them as a unique and interesting grouping of diverse and unrelated organisms that doesn't always behave like corals and fishes, while sharing the same ecological place in space and time.

Review: Preskitt, Vroom, Smith (2004) A Rapid Ecological Assessment (REA) quantitative survey method for benthic algae using photoquadrats with scuba. Pacific Science, 58(2):201-209.

Feature Paper: DOWNLOAD * Preskitt, Vroom, Smith (2004) A Rapid Ecological Assessment (REA) quantitative survey method for benthic algae using photoquadrats with scuba. Pacific Science, 58(2):201-209.

Author Abstract: The challenge of assessing seldom-visited, benthic substrates has created the need for a method to describe benthic communities quickly and efficiently. Macroscale rapid ecological assessments (REAs) of algal assemblages provide managers of coral reefs and other benthic ecosystems with the fundamental descriptive data necessary for continued yearly monitoring studies. The high cost of monitoring marine communities, especially remote sites, coupled with the time limitations imposed by scuba, require that statistically valid data be collected as quickly as possible. A photoquadrat method using a digital camera, computer software for photographic analysis, and minimal data collection in the field was compared with the conventional method of point-intersect (grid) quadrats in estimating percentage cover in subtidal benthic communities. In timed studies, photoquadrats yielded twice the number of quadrats (and an almost infinite number of data points) as conventional methods, provided permanent historical records of each site, and minimized observer bias by having only one observer identifying algae in the field. However, photoquadrats required more post-collection computer analyses of digital photographs than conventional methods. In the manual method, observer bias in algal identification can occur depending on the degree of experience of individual divers. On the other hand, photoquadrats rely on one observer in the field and one observer in the laboratory, standardizing algal identification. Overall, photoquadrats do not yield the finer resolution in diversity that was found using point-intersect quadrats but do provide a more precise estimate of percentage cover of the abundant species, as well as establishing a permanent visual record in the time allowed by work with other teams.
 

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Since algae are often considered capable of overgrowing corals and precipitating phase shifts on coral reefs that are under nutrient or other environmental stress, it is important to know how to survey them in the field. This week's paper compares various methods used to collect algal field data with the aim at discovering a rapid, scientifically valid method. Yet while algae are the focus of this week's paper, the authors describe photoquadrat techniques that are applicable towards many benthic organisms, including corals. 

Photoquadrats are uniform-sized rectangles or squares (often made of PVC) that are placed over the substrate with a camera attached to them through a frame meant to keep the camera at a set height and angle above the bottom.

The authors designed the protocol as part of remote US-territorial Pacific island surveys conducted regularly by the National Oceanic and Atmospheric Administration (NOAA). The surveys had to "describe community structure and prepare a comprehensive species list for each site [surveyed]." 

The authors compared "conventional methods using point grid, point-intersect methods, or visual estimation" with "photographic and video quadrates." Yet while there were benefits of conventional methods (typically more taxa identified and canopy effects able to be assessed), the negatives (higher training required, more field time required) were enough to veto their use for algal data, which were considered of lower value than coral or fish data. As a result of these constraints, the authors developed a rapid field method that would still allow high-quality data to be collected.

In summary, the method involved laying a transect using fiberglass tape measures, and then placing photoquadrats at pre-determined random places along each transect, taking a high-resolution photograph and then having a second diver identifying "algae within the photoquadrat, recording the relative abundance of the five most abundant algae on a scale of 1 to 5 (with 1 being most abundant), and collecting representative samples of the algal species in the quadrates from outside the framer for later identification in the laboratory."

In the field, researchers were able to collect nearly three times as many photoquadrats as conventional measurements and statistical analyses showed that photoquadrat data were more consistent (in terms of data quality and quantity) than conventional methods. As the authors point out, "photoquadrats are not new; they have been compared with a myriad of point-intersect, visual estimation, and grid quadrate methods and have often been found wanting in scale and in diversity measurements." Their purpose was not to reinvent the wheel, so to speak, but rather to "refine the standard photoquadrat method by adding a two-observer team, note taking, collection of samples, and quadrate mapping to address known concerns with cryptic species."

The authors also found that photoquadrats helped produce more flexible statistical data. "Grid quadrates are static: the number of random points are fixed, usually with too few points due to time limitations, and sometimes the observer must quickly identify algae underwater in less than ideal conditions. In comparison, the photoquadrat method is more flexible in laboratory analysis."

Finally, while photoquadrats may not be appropriate where finer-resolution of taxonomic data and canopy effects are desired, they are appropriate for "quantitatively describing an ecosystem at a macro-community level. The photoquadrat method provides adequate quantitative data, analysis flexibility, and permanent specimens that enable the investigators to determine the patterns in distribution and abundance [of taxa] in remote, inaccessible regions. A standardized rapid ecological assessment protocol not only provides the quantitative data needed to establish baselines for these communities but also ensures that comparable data are collected during the ongoing monitoring needed for management decisions."

Next we'll look at algae in the Indian Ocean and how they differ to the better-surveyed Pacific and Caribbean.

Review: Bates, Saunders, Chopin (2005) An assessment of two taxonomic distinctness indices for detecting seaweed assemblage responses to environmental stress. Botanica Marina, 48:231-243.

Feature Paper: DOWNLOAD * Bates, Saunders, Chopin (2005) An assessment of two taxonomic distinctness indices for detecting seaweed assemblage responses to environmental stress. Botanica Marina, 48:231-243.

 

Author Abstract: We tested the efficacy of two biodiversity indices, average taxonomic distinctness and variation in average taxonomic distinctness, for indicating environmental stress in seaweed assemblages from the Bay of Fundy, New Brunswick, Canada. These indices, which measure the average number of taxonomic levels between species in a sample, offer a potential panacea for biomonitoring because their calculation requires only a species list and a regional taxonomic hierarchy, they offer a statistical framework for testing whether assemblages deviate from an expected taxonomic breadth, and previous studies involving animal assemblages have demonstrated an independence from sampling effort. However, our results were not consistent with previously published studies or with our perception of site conditions. Specifically, putatively impacted sites scored above-average taxonomic distinctness values, while sites otherwise regarded as healthy were indicated as environmentally degraded. We also demonstrate that average taxonomic distinctness values can be negatively correlated with species richness, Shannon diversity and with functional diversity. Further, increasing the breadth of the regional species list to which specific sites were compared resulted in a more conservative test of impact. We recommend that a qualitative understanding of how specific biotic assemblages respond to stress is a necessary prerequisite to use the taxonomic distinctness indices for environmental stress assessments.

 

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: This week we turn our attention to algae, an oft-maligned group of organisms in the marine environment. For those regular readers of Science Corner I have discussed algae at multiple times in the past, both from the perspective of phase shifts (whereby algae opportunistically overgrow corals and other sessile reef organisms when environmental conditions favor their growth, usually through higher nutrient inputs or physical disturbances) as well as through being a group that doesn't have the typical biodiversity patterns that corals and reef fishes do. 

This week's first paper continues the examination of taxonomic similarity that we've covered in past weeks, but applies analyses towards determining whether algae are responding to environmental stress, and therefore whether a phase shift in a reef environment may be occurring.

For those who missed the previous discussions on taxonomic diversity indices, the authors provide a good summary: "Taxonomic distinctness (TD) indices are biodiversity measures that provide a summary of the relatedness between organisms within samples from biological assemblages."

How the authors addressed assessing environmental stress was a two-part process. 

1. First, they developed an index that "incorporates the identity of species within a sample by calculating the average path length between all pairs of species, measured through a cladogram of phylogenetic relationships or a Linnaean classification."

2. Second, the authors "inferred" environmental stress "by testing for departure from an expected range of average taxonomic distinctness values calculated by resampling from a broader ‘‘master list’’ of species that could potentially inhabit the sampling region."

The authors note that their "approach is predicated on the observation that, in several types of marine invertebrate assemblages, disturbance can shift structure from a relatively diverse array of taxa to a suite of closely related species that are not representative of the potential taxonomic structure for an unimpacted site."

In other words, certain organisms are opportunistic and able to rapidly increase in numbers to the point where they overgrow other organisms and shift community compositions. When such a composition is found where a site is known to have high diversity, it could be an indicator that the system is out of balance, particularly if one knows that the environmental surveys leading to such conclusions were an accurate representation of the environmental site at the time of survey.

The authors also examined "variation in taxonomic distinctness," which relates to "the evenness of the taxonomic or phylogenetic relationships between taxa."

The authors then combined analyses of average taxonomic distinctness with variation in taxonomic distinctness to generate a "bivariate scatter plot" and then determine deviation from 95% probability contours within the scatter plots generated for each pairwise analysis.

The authors then applied their approach to surveys of algal assemblages in New Brunswick Canada because "extensive and multiple human impacts have been reported in this area." 

When the authors examined algae as an entire group rather than individual taxonomic clades, they didn't find any sites that appeared to be impacted, which went counter to their hypothesis. They then performed individual analyses on each algal clade separately: Rhodophyta, or red algae; Chlorophyta, or green algae; and Phaeophyceae, or brown algae. 

What many people don't realize is that each algal group evolved separately and independently and that each group is more distinct from each other than frogs are from fish. The brown algae are more related to bacteria, while the green algae are closer to true plants (i.e., land plants, sea grass), and red algae are actually two groups of ancient distinct organisms. All algal groups have different and distinct life histories and reproductive cycles. 

When examining individual algal groups, the authors found that the red algae exhibited deviation from 95% confidence intervals for multiple sites examined. 

While one must be careful of which taxa are grouped, since the authors note that their "results indicate that taxonomic distinctness indices may not perform equally well for all types of bioindicator groups," nevertheless the authors conclude that "average taxonomic distinctness and variation in average taxonomic distinctness offer potentially powerful tools for assessing environmental stress in situations where historical data do not exist, or exist only as species lists collected with unknown sampling effort."

Next we'll look at a good method for conducting algal surveys (which can be expanded to other benthic groups like corals, sponges, bryozoans, etc.) so that uniform sampling effort does occur.

Review: Mora, Chittaro, Sale, Kritzer, Ludsin (2003) Patterns and processes in reef fish diversity. Nature, 421:933-936.

Feature Paper: DOWNLOAD * Mora, Chittaro, Sale, Kritzer, Ludsin (2003) Patterns and processes in reef fish diversity. Nature, 421:933-936.

Author Abstract: A central aim of ecology is to explain the heterogeneous distribution of biodiversity on earth. As expectations of diversity loss grow, this understanding is also critical for effective management and conservation. Although explanations for biodiversity patterns are still a matter for intense debate, they have often been considered to be scale-dependent. At large geographical scales, biogeographers have suggested that variation in species richness results from factors such as area, temperature, environmental stability, and geological processes, among many others. From the species pools generated by these large-scale processes, community ecologists have suggested that local-scale assembly of communities is achieved through processes such as competition, predation, recruitment, disturbances and immigration. Here we analyse hypotheses on speciation and dispersal for reef fish from the Indian and Pacific oceans and show how dispersal from a major centre of origination can simultaneously account for both large-scale gradients in species richness and the structure of local communities.

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Today we look at a good paper from the eminent journal Nature about the near-global (Indian and Pacific Oceans only) biogeography of reef fishes. The authors examined latitudinal and longitudinal diversity gradients, which for reef fishes and corals are known to peak in diversity within the "coral triangle" area centered between the Philippines and eastern Indonesia through Papua New Guinea to the Solomon Islands, summarized in the figure below.

The authors go on to determine which of "three major, yet different, hypotheses invoking speciation and dispersal [that] have been suggested to explain these large-scale patterns" seems the most plausible given their analyses. The three hypotheses are:

1. "The Centre-of-Origin hypothesis suggests that the IPR [Indo-Pacific Region] is a major centre of speciation from which species disperse to marginal locations."
2. "The Centre-of-Overlap hypothesis proposes that the high diversity in the IPR is due to the overlapping of faunas from several biogeographic provinces."
3. "the Centre-of-Accumulation hypothesis states that speciation occurs in several areas peripheral to the IPR and that species extend their ranges to the IPR by prevailing currents. A variant to the Centre-of-Accumulation hypothesis holds that after extending into the IPR, many species have suffered range reductions through the loss of populations marginal to the IPR."
4. To test the last two hypotheses, the authors note that those hypotheses "state that only the tails of species’ ranges extend into the IPR. Consequently, most species should have their range midpoints marginal to the IPR, resulting in bimodal or multi-modal distributions."
5. The authors' examination of their data revealed "plots of species mid-ranges (both longitudinal and latitudinal) show nonrandom unimodal distributions with peaks coinciding with the geographical position of the IPR (Fig. 1c, d). These distributions rule out these two hypotheses and provide support for the Centre-of-Origin hypothesis. They also support, to some extent, the variant of the Centre-of-Accumulation hypothesis because range reductions through loss of peripheral populations would shift mid-ranges towards the IPR, and, if extensive, this could result in a unimodal distribution of midranges in the vicinity of the IPR."
6. The next task of the authors was to determine whether the Centre-of-Origin hypothesis was more reasonable than the variation of the Centre-of-Accumulation hypothesis, or vice-versa. To answer this question, the authors note that while the former hypothesis predicts "speciation within the IPR" the latter hypothesis predicts "speciation in locations marginal to the IPR."
7. Rather than examining the fossil records to determine zones of speciation, the authors look at patterns of endemism. The authors "assume that centers of endemism contain a preponderance of recently derived species that are yet to expand their ranges (neo-endemics) and thus provide insights into areas where species are most likely to originate."
8. The authors mapped endemism of reef fish in the figure below.

The authors note that the IPR has the highest concentration of endemism in the Indian and Pacific oceans. Therefore, the authors conclude that "this result supports the IPR as a major centre of speciation and confirms the expectation of the Centre-of-Origin hypothesis."

Another cause for high levels of endemism might be that the IPR has "among the highest number of islands per unit of geographical area makes it a place where allopatric speciation might be frequent, especially when considering patterns of recent geological sea level change."

The authors tested various other predictions about the Centre-of-Origin hypothesis specifically and while I'll leave it to readers to look up the original paper, I'll summarize by saying that the authors found additional support for the Centre-of-Origin hypothesis.

The authors' take-home message is that "no location contributes as much to the overall alpha diversity of the Indian and Pacific oceans as does the IPR." However, I should note that certain organisms (such as algae) do not share the same diversity patterns as reef fish and corals, but considering how integral both corals and fishes are to coral reefs, obviously conservation priority should be placed on areas of high diversity (e.g., the Indo-West Pacific "coral triangle") and areas of particular uniqueness (e.g., the noted high-endemism regions in Figure 2 above). 

Next we'll examine the diversity patterns of algae since it is important to review organisms that don't share common diversity patterns since they too are integral to determining any underlying processes that may affect the distribution of algae as well as corals and fishes.

Review: Dethier, McDonald, Strathmann (2003) Colonization and connectivity of habitat patches for coastal marine species distant from source populations. Conservation Biology, 17(4):1024-1035.

Feature Paper: DOWNLOAD * Dethier, McDonald, Strathmann (2003) Colonization and connectivity of habitat patches for coastal marine species distant from source populations. Conservation Biology, 17(4):1024-1035.

Author Abstract: The exchange of propagules or mobile adults between isolated habitat patches is of critical importance for some types of preserves, especially for species that cannot propagate locally. In the marine realm, the role of planktonic dispersal in maintaining viable local populations can be tested by examining life-history traits of species that colonize (or do not colonize) isolated habitat patches. We compared the abundances of benthic species on an exposed rocky jetty surrounded by dissimilar habitats on the coast of Washington (U.S.A.) with those of species at distant bedrock sites within potential source areas. Despite its isolation, the jetty lacked only a small proportion of the potential algal species; these absences could result from the 40- to 100-km distances to larger source areas or from subtle habitat differences at the jetty. Coralline algae are expected to be poor dispersers, both because propagules are short-lived and because adults are unlikely to float. These algae were absent on the study jetty, although they occur on other isolated jetties on this coast. Short-term transplant experiments indicated that corallines can survive locally once they colonize. Few animals were absent; one was a chiton that settles and feeds on coralline algae. Animals with obligate dispersal of offspring were abundant on the jetty despite their inability to propagate locally and despite dilution of larvae dispersing in the plankton from distant sources. Conversely, some animal species with no planktonic phase were also present; thus, organisms with a wide range of life-history traits can persist at this distant and small patch of suitable habitat. Isolation along this shoreline did not eliminate either poor dispersers or obligate dispersers.

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Today we'll look at an important topic in conservation biology… the connectivity of organisms within an aquatic region. The authors point out that connectivity is more well-known for organisms with short dispersal capacities compared to organisms with long dispersal ranges. 

As the authors point out, "the extreme variation in dispersal of marine plants and animals presents a problem for the design of systems of marine preserves. How well can any single combination of size and spacing of protected areas serve all the target species?"

The whole purpose of the paper is summarized by the authors below: 

"For terrestrial organisms, conservation practices have been informed by island biogeography, metapopulation models, and landscape analyses (Hanski & Gilpin 1997). In the marine realm, however, application of terrestrial models is problematic because most benthic organisms live in two landscapes at different stages in their life histories, one the sea bed and the other the overlying water; the water moves constantly and variably (Sammarco & Heron 1994; McEdward 1995). This connectivity via water ( and planktonic propagules ) constitutes a proposed advantage of marine reserves—their potential for extensive dispersal out into surrounding sites (e.g., Allison et al. 1998; Gerber et al. 2002)—but the connectivity over long distances is subject to debate (e.g., Roberts 1997; Cowen et al. 2000)."

To address their question of how to address connectivity of patchy or isolated marine ecosystems, the authors look at a number of case studies of isolated islands with depauperate faunas and floras and then expand their findings further.

The authors then conducted marine littoral (seashore and nearshore submerged and intertidal habitats) zones around an area of coast in the northwest Pacific coast of the Americas. The authors counted organisms within quadrates. To address whether certain groups of organisms were missing because of habitat or distribution (i.e., dispersal barriers) the authors did transplantation experiments.

The authors paid particular attention to obligate dispersers. A few final observations of the authors were:

"Algae, most or all of which are poor dispersers, were more depauperate even though a rare colonization event should have resulted in good local self-recruitment."

"Overall, our results are encouraging for the design of broadly effective systems of marine reserves. Our results indicate that such varied marine organisms can persist at an isolated site by quite different means. For species with a long pelagic larval period, connectivity and persistence can result from larvae that are dispersed far from the parental area if source populations are large. For species with little or no transport of propagules, persistence can result from much rarer transport between reserves because of a higher capacity for local recruitment."

"Moreover, the absence of some expected species, particularly algae, on isolated jetties suggests that spacing reserves at 50 km could reduce connectivity too much for their arrival or persistence, although distance from sources is not yet demonstrated to be the direct cause of these absences."

Review: Tulloss (1997) Assessment of Similarity Indices for undesirable properties and a new Tripartite Similarity Index based on cost functions, pp.122-143, In: Palm, Chapela (Eds.) Mycology in Sustainable Development: Expanding concepts, vanishing borders. Parkway Publishers, Boone NC USA.

Feature Paper: DOWNLOAD * Tulloss (1997) Assessment of Similarity Indices for undesirable properties and a new Tripartite Similarity Index based on cost functions, pp.122-143, In: Palm, Chapela (Eds.) Mycology in Sustainable Development: Expanding concepts, vanishing borders. Parkway Publishers, Boone NC USA.

Author Abstract: Comparison of lists is a common element of many studies including ethnomycological, ecological, and mycological investigations. The items on the lists might be species in a habitat, uses of a given organism by indigenous people, character states present in an individual fungus, or lists of unusual spellings in segments of the Dead Sea Scrolls. Often, it is desirable to express the similarity of two related lists by some formula (a similarity index). Such an index might be used in summarizing data otherwise presented or as input to further numerical processing, such as the creation of a dendrogram (Pankhurst, 1991:54). In examining several works using formulae to provide a single number expressing the similarity of the contents of two lists, a number of difficulties with the formulae were noted. For example, for some indices the same value was generated for two or more quite different situations, e.g., one in which a pair of lists were nearly identical, and another in which one list was much larger than the other. This problem came up during review of material for the present book, thus motivating the present chapter. The purpose of this chapter is to motivate, describe, and offer an implementation for, a working similarity index that avoids the difficulties noted for the others.

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Today we'll finish up our review of taxonomic similarity indices with the "Tripartite Similarity Index." This analysis was developed by using mathematical formulas from outside of the biological sciences and applying them towards biology, which is an increasingly common theme as scientists across multiple disciplines are starting to communicate.

The author of today's paper developed a new similarity index because he was dissatisfied with other similarity indices for a number of reasons (summarized in his abstract above). Through his comparison, he reviewed 20 "existing and commonly used similarity indices" and determined that "no problem-free index was found in the list." However, through the review of "manufacturing engineering" cost function metrics, the author was able to create an index that solved the problems of all reviewed indices.

I won't go through all 20 similarity indices reviewed (see the original paper for that), but I highly recommend reviewing the original paper for a thorough explanation of all the pros and cons of each similarity index and considerations that all researchers should have before comparing lists for similarity.

However, for ease, I'll list the 10 indices the author spent a longer time reviewing and debunking, but leave it to the reader to look to the full paper for explanations of all the limitations involved in each index:

1. Simpson Coefficient
2. Second Kulczynski Coefficient
3. Ochiai / Otsuka Coefficient
4. Dice Coefficient
5. Jaccard Coefficient
6. Sokal and Sneath Coefficient
7. First Kulczynski Coefficient
8. Mountford Coefficient
9. Braun-Blanquet Coefficient
10. Fager and McGowan Coefficient

In developing a new similarity index, the author found 8 requirements missing (usually in part, as nearly all similarity indices qualified some of the requirements) from the indices reviewed:

1. "A similarity index shall be sensitive to the relative size of the two lists to be compared; and great difference in size shall be interpreted to reduce the value of the similarity index."
2. "A similarity index shall be sensitive to the size of the sublist shared by a pair of lists; and an increase in difference in size between the smaller of the two lists and the sublist of common entries shall be interpreted to reduce the value of the similarity index."
3. "A similarity index shall be sensitive to the percentage of entries in the larger list that are in common between the lists and to the percentage of entries in the smaller list that are in common between the two lists and shall increase as these two percentages increase."
4. "A similarity index shall yield values having fixed upper and lower bounds."
5. "A similarity index shall have the property that when two lists are identical, the similarity index for the two lists shall be equal to the upper bound of the index."
6. "A similarity index shall have the property that when two lists have no entries in common, the similarity index for the lists shall be equal to the lower bound of the index."
7. "Distribution of values of a similarity index between zero and one shall be such that (a) if the size of two input lists is fixed, then the output shall vary roughly directly as the number of entries shared between the lists; and (b) if the smaller list is a subset of the larger list, then the value of the similarity index shall vary roughly inversely as the size of the larger list."
8. "A similarity index program shall check its input data to verify that the following relationships hold: a + b > 0 and a + c > 0."

Through satisfying all 8 requirements listed above, the author came up with the following formula composed of 3 individual components (hence the name Tripartite Similarity Index): 

T = √(U x S x R) where the following subformulae apply:

The author cautions however that while the Tripartite Similarity Index does satisfy all requirements other authors have described for similarity indices, the T-values produced are a bit abstract and can't be thought of as simple percentages of similarity. Instead, the author notes that "Our primary hope is that our intuitions about a loosely defined property of points in the three dimensional space (similarity) is reflected in the position of a corresponding point on a line."

So now that you have a new formula for comparing lists of data, have fun computing some T-values and compare how the plots appear related to other more commonly taught indices, such as the Simpson, Jaccard, and Braun-Blanquet similarity indices.

Next we'll have two papers dealing with various patterns of species diversity, with links to papers below.

Review: Izsak, Price (2001) Measuring β-diversity using a taxonomic similarity index, and its relation to spatial scale. Marine Ecology Progress Series, 215:69-77.

Feature Paper: DOWNLOAD * Izsak, Price (2001) Measuring β-diversity using a taxonomic similarity index, and its relation to spatial scale. Marine Ecology Progress Series, 215:69-77.

Author Abstract: We present a new similarity index, taxonomic similarity (ΔS), which can be used to measure β-diversity. ΔS utilises species presence/absence data, and incorporates both higher taxon richness and evenness concepts. It is derived from the average taxonomic distance (relatedness) of any 2 species from different sites. Therefore ΔS is analogous to taxonomic distinctness recently developed for biodiversity assessment at α- and γ- (landscape or seascape) scales. ΔS is a new index, although its derivation uses a concept similar to the ‘optimal taxonomic mapping statistic’ developed independently for quantifying structural redundancy in marine macrobenthos. Using echinoderm data, we show that ΔS exhibits smoother behaviour and is less influenced by species richness, and hence sampling effort, than the widely used Jaccard coefficient of species similarity. We also believe ΔS to be a more intuitive and comprehensive measure of similarity than Jaccard and other conventional indices based solely on species held in common. Taxonomic similarity between sites is computed for echinoderms examined over 3 different spatial scales: local/small-scale (<10 km), intermediate-scale (10 to 100s km) and province/oceanic-scale (100s to 1000s km). Taxonomic similarity between sites increases progressively with spatial scale, with significantly lower values and higher β-diversity at small spatial scales. The same pattern is evident for species similarity, using the Jaccard coefficient. Possible explanations for this pattern centre on: (1) the large-scale oceanic area examined (Indo-West Pacific), representing a metapopulation of echinoderms for the 2 other, smaller areas examined within (Pula Wé, Sumatra and Lakshadweeps); (2) greater biophysical instability and unpredictability at small spatial scales. Compared with larger spatial scales, these may be characterised by greater likelihood and influence of species migrations and extinctions on a site’s total species composition. Hence, species composition may be highly changeable at small scales, leading to high β-diversity. These findings are based on 1 set of comparative data for 1 faunal group. Any wider conclusions drawn would be premature, although corals may also show greater β-diversity at small spatial scales. The extent to which patterns observed are evident for other marine species groups is not well known.

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Today we will look at a then-new similarity index, called "taxonomic similarity) and how it relates to β-diversity, or beta diversity. According to Wikipedia, β-diversity can be defined as "the rate of change in species composition across habitats or among communities. It gives a quantitative measure of diversity of communities that experience changing environments." Therefore, unlike alpha diversity (or pure species counts for an individual location), β-diversity compares the species diversity between locations and looks at change across locales, while gamma diversity looks at β-diversity across a very large regional or global scale. Like Monday's paper (first paper this week) I encourage readers to download the full article to learn the mathematical formulas for the taxonomic similarity index defined. What I'll do is just look at the basics of the paper and interested readers can follow up with the download link to learn more.

The authors use species presence / absence data (checklists) to derive "the average minimum path length between any 2 species in different sites / areas." They use "path lengths" based on taxonomic relatedness, in the following way: "taxonomic path lengths are 0 (same species), 1 (different species but same genus), 2 (different genus but same family), 3 (different family but same order), etc. However, path length here refers to species in different sites / areas, rather than in only one site / area."

A summary of how the authors look at taxonomic similarity can be seen in their figure, below:

In their paper, the authors also showed the effect of increasing sampling effort and sampling area on taxonomic similarity measurements, but I'll leave it to interested readers to follow up, since the authors go into a very extensive analysis and compare their results and index to the Jaccard similarity index.

The authors further point out that while alpha diversity is quite well known in the marine environment (presence / absence checklists are one of the staples of marine biodiversity studies), beta diversity is less well known and that they hope their similarity index (which "appears to be less influenced by sampling effort than [the] Jaccard [index]") helps contribute to scientific progress. Furthermore, their index also seems to be less influenced by difference in area between localities, though common sense would dictate that one should try to compare relatively similarly sized areas… but sometimes only country-level data are available and at least there is some way to compare such areas.

The authors conclude by mentioning that all taxonomic levels ("not just species") should be considered in biodiversity studies, though many authors have shown that at least for the majority of tropical marine organisms, biodiversity is relatively similar across taxonomic levels (though not for all organisms so one must be careful about drawing comparisons between their group of interest and other groups).

Review: Clarke, Warwick (2001) A further biodiversity index applicable to species lists: variation in taxonomic distinctness. Marine Ecology Progress Series, 216:265-278.

Feature Paper: DOWNLOAD * Clarke, Warwick (2001) A further biodiversity index applicable to species lists: variation in taxonomic distinctness. Marine Ecology Progress Series, 216:265-278.

Author Abstract: A further biodiversity index is proposed, based on taxonomic (or phylogenetic) relatedness of species, namely the ‘variation in taxonomic distinctness’ (VarTD, Λ+) between every pair of species recorded in a study. It complements the previously defined ‘average taxonomic distinctness’ (AvTD, Δ+), which is the mean path length through the taxonomic tree connecting every pair of species in the list. VarTD is simply the variance of these pairwise path lengths and reflects the unevenness of the taxonomic tree. For example, a species list in which there are several different orders represented only by a single species, but also some genera which are very species-rich, would give a high Λ+ by comparison with a list (of equivalent Δ+) in which all species tended to be from different families but the same order. VarTD is shown to have the same desirable sampling properties as AvTD, primarily a lack of dependence of its mean value on the sample size (except for unrealistically small samples). Such unbiasedness is of crucial importance in making valid biodiversity comparisons between studies at different locations or times, with differing or uncontrolled degrees of sampling effort. This feature is emphatically not shared by indices related to species richness and also not by properties of the phylogeny adapted from proposals in other, conservation contexts, such as ‘average phylogenetic diversity’ (AvPD, Φ+). As with AvTD, the VarTD statistic for any local study can be tested for ‘departure from expectation’, based on a master taxonomy for that region, by constructing a simulation distribution from random subsets of the master list. The idea can be extended to summarising the joint distribution of AvTD and VarTD, so that values from real data sets are compared with a fitted simulation ‘envelope’ in a 2 d (Δ+, Λ+) plot. The methodology is applied to 14 species lists of free-living marine nematodes, and related to a master list for UK waters. The combination of AvTD and VarTD picks out, in different ways, some degraded locations (low Δ+, low to normal Λ+) and the pristine island fauna of the Scillies (normal Δ+, high Λ+). The 2 indices are also demonstrated to be measuring effectively independent features of the taxonomic tree, at least for this faunal group (although it is shown theoretically that this will not always be the case). The combination of Δ+ and Λ+ is therefore seen to provide a statistically robust summary of taxonomic (or phylogenetic) relatedness patterns within an assemblage, which has the potential to be applied to a wide range of historical data in the form of simple species lists.

Note to Readers: Follow links above for author email, full article text, or the publishing scientific journal. Author notes in my review are in quotes.

Review: Today is the first of three papers on how measurements of taxonomic similarity between populations are used to determine biogeographic affinities between locations. This paper is a bit complicated in that they introduce specific mathematical formulas for assessing taxonomic similarity. I won't go into the mathematics in my review because I aim to help both laypersons and new graduate students (or advanced undergraduates) understand the reviews. The basics of the mathematical principles are described in the author's abstract above in any event. I encourage those wishing to know more about the subject to follow the download link for a free copy of the complete article.

I also want to point out that prospective or current Master's of Science students should examine this article and others in the journal Marine Ecological Progress Series (MEPS) as one professor once told me that a Master's degree thesis is basically a MEPS-worthy paper. Use MEPS as yore guideline when trying to decide scope of a research project or when determining how much of an advisor's idea you can tackle in about one year of research and one year writing up the results for your thesis. Don't do more… trust me. Save that for your PhD and Postdoc.

Now, onto the review. As the first paragraph of the authors' article states: 

"Species richness measures have traditionally been the mainstay in assessing the effects of environmental degradation on the biodiversity of natural assemblages of organisms. However, the sampling problems associated with ascertaining true species richness and making comparable assessments with historical data are well-known, and it should be noted that richness is not the only measurable component of community level biodiversity, even when the data consist simply of lists of species presence/absences. The phylogenetic structure of the assemblage is also clearly important, and an assemblage comprising a group of closely related species must be regarded as less ‘biodiverse’ than an assemblage of the same number of more distantly related species, for example all belonging to different phyla. Measures of phylogenetic structure, based on analysis of cladograms of particular groups of organisms, have been proposed by conservation biologists as a means of assigning conservation priorities that preserve the greatest amount of phylogenetic diversity or ‘evolutionary history’ (May 1990, Vane-Wright et al. 1991, Williams et al. 1991, Faith 1992, 1994, Humphries et al. 1995, Nee & May 1997). Little attention, however, has been devoted to analysis of the ways in which environmental degradation affects phylogenetic structure on local or regional scales, and the extent to which properties of this structure can be used as measures of biodiversity for the purposes of biological effects monitoring."

I copied the entire paragraph because not only is it an excellent example of scientific writing, but it clearly states the problem the authors seek to address in their paper. To address the problem at hand (last sentence in the author introduction above), the authors use the concept of "taxonomic distinctness," which they define as "a measure of the average degree to which individuals in an assemblage are related to each other."

Oftentimes when researchers want to conduct global or large-scale analyses of target species, the highest resolution consistent data available are species presence-or-absence lists, also known as checklists. Usually, scientists use such lists to determine taxonomic diversity and total richness, but the authors propose determining "average taxonomic distinctness" of populations, for which they provide formulas (look to the original article).

But in essence, what the authors are trying to point out is that when confronted with only checklists, one needn't be restricted just to total species (or other taxonomic levels) richness. One can determine which locations are related to each other based on species compositions that are shared. Recall last Saturday's review (Week 5 Paper 2) where atolls have characteristic floras and faunas and how rainfall and island elevation can help structure and determine how related those floras and faunas are. 

The authors' taxonomic distinctness levels can be used to aid historical biogeography through determining sources of radiation or speciation events. The authors also use their metric to show how environmental degradation can skew species richness and thus can help determine which species are likely to "drop off" or go locally extinct. Thus, taxonomic distinctness can be used for management purposes, as well as for computer simulations to test various historical biogeography theories.

The authors also state that "Theories of island biogeography have largely been developed from data on species that are easily censused and for which complete inventories can be produced in relation to island size, such as birds, reptiles and certain groups of insects (MacArthur & Wilson 1967). For groups such as free-living nematodes, or other small cryptic taxa, a complete census is rarely possible, except for very small areas. [Taxonomic distinctness measures] therefore offer a useful alternative, and might also help to address longstanding questions concerning island biogeography that cannot be resolved by a count of the number of species alone: for example whether increasing numbers of species are a function of increasing island size per se, or are related to the larger number of habitats."

The authors then conclude with: "Because of the impracticality of routinely attempting comprehensive surveys, surrogacy methods will clearly become the norm in biodiversity estimation (Harper & Hawksworth 1994), and the search for appropriate indicators of marine and coastal biodiversity has become an important research goal (Feral 1999)."

In essence, this is what nearly all fieldwork is: gathering a sample subset of an entire population and hoping that you can sample enough to draw statistically powerful conclusions about the whole population. Furthermore, if certain "keystone" or important species are known to have a tight relationship with other organisms of interest, studying the one will often provide information about the state of the other. 

For example, butterflyfishes are mostly coralivorous, with many being obligate coralivores. This means that many butterflyfish species only eat living coral. Therefore, counting butterflyfishes on a reef and knowing a given reef area can help coral reef biologists determine approximate levels of coral cover needed to sustain such levels of butterflyfishes.

Next we'll look at how beta-diversity can be measured from another kind of taxonomic similarity index. Download links below as usual.