Higher Taxa as Surrogates of Plant Biodiversity in a Megadiverse Country

Abstract:  An important question in conservation biology is the extent to which the number of taxonomic supraspecific categories can serve as surrogates of species richness. This issue has been little explored in highly diverse areas. We used 113 floristic inventories from throughout Mexico, a megadiverse country, to evaluate the potential of higher-taxon richness for predicting local species richness of vascular plants. This large biodiversity data set includes the main vegetation types found across the country. In all, 247 families, 2,398 genera, and 11,890 species were used for the analysis, representing 99.6%, 90.2%, and 53.2% of the respective totals recorded in the country. We hypothesized that the number of genera and species would be accurately predicted by the richness of the higher taxon. To avoid getting spurious regressions resulting from the logical increase in lower-taxon richness as a higher taxon becomes richer, we calculated new response variables by subtracting from the number of elements in the lower taxon group the number of those in the higher taxon; these variables were "excess species" (number of species minus number of genera or families) and "excess genera" (number of genera minus number of families). Our results indicate that genera provide very effective surrogates for estimation of local species richness ( R ²= 0.85), whereas families have a more limited potential for this purpose ( R ²= 0.64). The predictive capacity of the diversity of higher taxon increased when the analyses were constrained to particular vegetation types (maximum R ²= 0.95 for genera). This surrogate method may be a valuable tool in locating and designing representative systems of protected areas for vascular plant diversity, especially in megadiverse countries, where conservation efforts are hindered by the lack of complete inventories and insufficient resources.     

Evaluating Completeness of Species Lists for Conservation and Macroecology: a Case Study of Mexican Land Birds

Abstract: Studies of species diversity, macroecology, and conservation are usually based on lists of species, but lists found in the scientific literature vary in completeness. The use of such data sets can produce misleading results, making it necessary to test species lists for completeness before undertaking an analysis. Species-richness estimators are useful for judging the completeness of species lists but have limitations. To add rigor to studies based on species lists, we propose that species lists should test for " omnipresent" taxa—species, genera, and families that occur throughout the region concerned—and for a minimum number of species and families. As a case study, we compared species assemblages in diverse habitats in Mexico and found that seven families and two genera of land birds are omnipresent in mainland Mexico (excluding treeless areas) and that the most depauperate assemblage known contains 35 species from 21 families. We concluded that a list of land birds from Mexico that lacks any of these omnipresent taxa or that contains fewer than 35 species or 21 families is incomplete. Similar analyses can be done for other taxa and other parts of the world. Tests for omnipresent taxa and for a minimum number of species and families can be used in combination with other existing criteria, such as species-richness functions, to better evaluate the completeness of species lists. Realistic results may be produced in macroecological and conservation studies only if they are based on reasonably complete species lists.     

Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model

Species distribution models are usually evaluated with cross-validation. In this procedure evaluation statistics are computed from model predictions for sites of presence and absence that were not used to train (fit) the model. Using data for 226 species, from six regions, and two species distribution modeling algorithms (Bioclim and MaxEnt), I show that this procedure is highly sensitive to "spatial sorting bias": the difference between the geographic distance from testing-presence to training-presence sites and the geographic distance from testing-absence (or testing-background) to training-presence sites. I propose the use of pairwise distance sampling to remove this bias, and the use of a null model that only considers the geographic distance to training sites to calibrate cross-validation results for remaining bias. Model evaluation results (AUC) were strongly inflated: the null model performed better than MaxEnt for 45% and better than Bioclim for 67% of the species. Spatial sorting bias and area under the receiver-operator curve (AUC) values increased when using partitioned presence data and random-absence data instead of independently obtained presence-absence testing data from systematic surveys. Pairwise distance sampling removed spatial sorting bias, yielding null models with an AUC close to 0.5, such that AUC was the same as null model calibrated AUC (cAUC). This adjustment strongly decreased AUC values and changed the ranking among species. Cross-validation results for different species are only comparable after removal of spatial sorting bias and/or calibration with an appropriate null model.     

An inventory of tree species in Europe—An essential data input for air pollution modelling

We present a detailed tree species inventory covering Europe, parts of Africa and parts of Asia. The inventory contains 39 groups of species that are important for biogenic VOCs or pollen emission calculations. For example: oak (Quercus), poplar (Populus), pines (Pinus), spruce (Picea), birch (Betula) and alder (Alnus). The inventory is based on national forest inventories and national statistics and gives tree species distribution in percentage within broadleaved as well as conifer forests. The inventory includes data from 799 regions and is redistributed into the 50 km × 50 km EMEP grid. The inventory is therefore prepared for easy implementation into atmospheric transport models by providing an extension to already applied land use data such as the Corine Land Cover (CLC2000) or Global Land Cover (GLC2000). The gridded version of the data set will be available on the webpage http://www.dmu.dk/International/Air/Models/Background/Trees/.     

Judicious Use of Multiple Hypothesis Tests

Abstract:  When analyzing a table of statistical results, one must first decide whether adjustment of significance levels is appropriate. If the main goal is hypothesis generation or initial screening for potential conservation problems, then it may be appropriate to use the standard comparisonwise significance level to avoid Type II errors (not detecting real differences or trends). If the main goal is rigorous testing of a hypothesis, however, then an adjustment for multiple tests is needed. To control the familywise Type I error rate (the probability of rejecting at least one true null hypothesis), sequential modifications of the standard Bonferroni method, such as Holm's method, will provide more statistical power than the standard Bonferroni method. Additional power may be achieved through procedures that control the false discovery rate (FDR) (the expected proportion of false positives among tests found to be significant). Holm's sequential Bonferroni method and two FDR-controlling procedures were applied to the results of multiple-regression analyses of the relationship between habitat variables and the abundance of 25 species of forest birds in Japan, and the FDR-controlling procedures provided considerably greater statistical power.     

A robust nonparametric method for quantifying undetected extinctions

How many species have gone extinct in modern times before being described by science? To answer this question, and thereby get a full assessment of humanity's impact on biodiversity, statistical methods that quantify undetected extinctions are required. Such methods have been developed recently, but they are limited by their reliance on parametric assumptions; specifically, they assume the pools of extant and undetected species decay exponentially, whereas real detection rates vary temporally with survey effort and real extinction rates vary with the waxing and waning of threatening processes. We devised a new, nonparametric method for estimating undetected extinctions. As inputs, the method requires only the first and last date at which each species in an ensemble was recorded. As outputs, the method provides estimates of the proportion of species that have gone extinct, detected, or undetected and, in the special case where the number of undetected extant species in the present day is assumed close to zero, of the absolute number of undetected extinct species. The main assumption of the method is that the per‐species extinction rate is independent of whether a species has been detected or not. We applied the method to the resident native bird fauna of Singapore. Of 195 recorded species, 58 (29.7%) have gone extinct in the last 200 years. Our method projected that an additional 9.6 species (95% CI 3.4, 19.8) have gone extinct without first being recorded, implying a true extinction rate of 33.0% (95% CI 31.0%, 36.2%). We provide R code for implementing our method. Because our method does not depend on strong assumptions, we expect it to be broadly useful for quantifying undetected extinctions.     

“Chance” and mixed-species associations

Summary Spatial associations between members of different animal species may arise through mutual behavioral attraction, through attraction to common resources or locations, or by chance. I outline a means of calculating the expected duration of associations based on the null hypothesis that members of different species move independently and randomly. Observed association durations can be compared to these expectations to identify those cases of association (or avoidance) that have biologically interesting causes. The method is applicable to any species in which the presence of a second species can be recorded during focal samples of an individual or a cohesive social group. The data required are readily collected in the field; I illustrate the use of the technique with data from several East African forest primates.     

Biodiversity of marine sessile epifauna at an Aegean island subject to hydrothermal activity: Milos, eastern Mediterranean Sea

Sessile macroepifauna was sampled at six rocky sites between 2 and 90 m depth with a number of different methods involving both underwater photography and collection of specimens. A total of 212 species (or varieties) were identified, belonging to seven higher taxa: poriferans (24 species), cnidarians (32), molluscs (8), serpuloidean polychaetes (33), bryozoans (90), brachiopods (4) and ascidians (21). The combined use of a varied array of sampling methods was effective in obtaining a rich faunal inventory. Deep and offshore sites tended to be richer in species than shallow and inshore sites. In all cases species richness was higher at sites closest to hydrothermal vents on the sea floor. Although there are no comparable inventories of marine sessile epifauna in the Aegean, the high number of species found, with a relatively low sampling effort in a restricted area, indicates that the marine biodiversity of this sea is not as low as traditionally believed. Received: 20 January 1999 / Accepted: 25 August 1999     

Random binary matrices in biogeographical ecology—Instituting a good neighbor policy

Binary matrices originating from presence/absence data on species (rows) distributed over sites (columns) have been a subject of much controversy in ecological biogeography. Under the null hypothesis that every matrix is equally likely, the distributions of some test statistics measuring co-occurrences between species are sought, conditional on the row and column totals being fixed at the values observed for some particular matrix. Many ad hoc methods have been proposed in the literature, but at least some of them do not provide uniform random samples of matrices. In particular, some swap algorithms have not accounted for the number of neighbors each matrix has in the universe of matrices with a set of fixed row and column sums. We provide a Monte-Carlo method using random walks on graphs that gives correct estimates for the distributions of statistics. We exemplify its use with one statistic.     

Invertebrate Morphospecies as Surrogates for Species: A Case Study

Environmental monitoring and conservation evaluation in terrestrial habitats may be enhanced by the use of invertebrate inventories, but taxonomic and logistic constraints frequently encountered during conventional taxonomic treatment have greatly restricted their use. To overcome this problem we suggest that nonspecialists may be used to classify invertebrates to morphospecies without compromising scientific accuracy. To test this proposition, large pitfall and litter samples of ants, beetles, and spiders from four forest types were sorted to morphospecies by a nonspecialist and to species by specialists. These data were used to generate morphospecies and species inventories and to estimate richness (α diversity) and turnover (β diversity), information frequently used in the above activities. Our results show that the estimates of richness of ants and spiders varied little between morphospecies and species inventories. Differences between estimates of beetle richness were largely influenced by errors of identification in two families, Curculionidae and Staphylinidae. But morphospecies and species inventories yielded identical ranking of forest type using richness. Turnover was assessed by sample ordination, which revealed similar clusters regardless of the type of inventory. Analysis of similarities of assemblages of ants and beetles showed significant differences between all forest types. Spider assemblages showed a lower level of discrimination. The assessment of turnover was consistent among inventories but different between the major taxa. Our findings suggest that morphospecies may be used as surrogates for species in some environmental monitoring and conservation, in particular when decisions are guided by estimates of richness and the assessment of turnover.     

A comparative analysis of alien plant species along the Romanian Black Sea coastal area. The role of harbours

Previous studies have found a higher proportion of alien plant species along the coastal area of the Black Sea. The goals of the present study were to assess the role of two harbours as gateways and reservoirs for alien plant species, to compare the structure and invasion pattern of the alien plants recorded there, and test methods useful for effective monitoring programs. We inventoried 12 sites along the western Black Sea coast from the harbour of Sulina in the north to Cape Kaliakra in the south. Each site was visited at least three times each. A more intensive survey was done in the two harbours targeted by our study: Constanţa and Sulina. The proportion of neophytes was higher in the harbours (representing about one third of the total plant species) and lower in coastal protected areas (with an average proportion of 6.7%). Species accumulation curves and estimators of species richness indicated that while the plant inventory was not complete, invasive alien species (IAS) were adequately inventoried. Harbours act not only as gateways for IAS but also as reservoirs, facilitating their acclimatization and naturalization. The use of species accumulation curves and estimators of species richness are useful tools in designing and evaluating simple monitoring programs based on repeated inventories. Our study has stressed the importance of monitoring not only coastal waters but also green areas in harbours for the early detection of IAS.     

A Successful Predictive Model of Species Richness Based on Indicator Species

Abstract:  Because complete species inventories are expensive and time-consuming, scientists and land managers seek techniques to alleviate logistic constraints on measuring species richness, especially over large spatial scales. We developed a method to identify indicators of species richness that is applicable to any taxonomic group or ecosystem. In an initial case study, we found that a model based on the occurrence of five indicator species explained 88% of the deviance of species richness of 56 butterflies in a mountain range in western North America. We validated model predictions and spatial transferability of the model using independent, newly collected data from another, nearby mountain range. Predicted and observed values of butterfly species richness were highly correlated with 93% of the observed values falling within the 95% credible intervals of the predictions. We used a Bayesian approach to update the initial model with both the model-building and model-validation data sets. In the updated model, the effectiveness of three of the five indicator species was similar, whereas the effectiveness of two species was reduced. The latter species had more erratic distributions in the validation data set than in the original model-building data set. This objective method for identifying indicators of species richness could substantially enhance our ability to conduct large-scale ecological assessments of any group of animals or plants in any geographic region and to make effective conservation decisions.     

Cost-Efficiency of Decaying Wood as a Surrogate for Overall Species Richness in Boreal Forests

Abstract:  Decaying wood is one of the most important elements for species richness in boreal forests. We tested how well reserve selection based on the amount and quality of decaying wood results in a representation of four ecologically different taxa (beetles, birds, wood-inhabiting fungi, and vascular plants). We also compared the cost-efficiency of the use of dead-wood indicators with comprehensive species inventory. Our database included 32 seminatural old-forest stands located in northern Finland. Decaying wood was a relatively good indicator of saproxylic species but not overall species richness. Even though dead wood did not reflect accurately overall species richness, our results indicated that the use of decaying wood as an indicator in site selection was more cost-efficient than using information from large-scale species inventories. Thus, decaying wood is a valuable surrogate for species richness, but other cost-efficient indicators that reflect the requirements of those species which are not dependent on decaying wood should be identified.     

大气污染物排放清单的建立及不确定性

本文在调研国内外大气污染物排放清单的基础上,总结了清单编制的基本程序,介绍大气污染物排放清单的建立,包括技术路线和计算方法,以及清单的管理、改善及质量保证与控制计划。不确定性分析是完善清单的重要方面,本文阐述了清单不确定性的来源及定量、定性的评价方法。     

A Century of Plant Species Loss from an Isolated Fragment of Lowland Tropical Rain Forest

An isolated 4-ha fragment of lowland tropical rain forest has been preserved in the Singapore Botanic Gardens since their founding in 1859. The Botanic Gardens'Jungle has recently had enumerated all woody stems 5 cm diameter at breast height (dbh) and larger and the complete vascular plant flora inventoried. This inventory can be compared with the historic record of the flora of the Gardens'Jungle obtained from the extensive collection of herbarium specimens dating back to the 1890s. Of the 448 historically recorded native species, 220 are still present. Ninety-four native species for which there were no historic records and 80 introduced species were also recorded in the recent inventory. The 50.9% loss of plant species richness over approximately the last century has not been distributed uniformly across plant life-form groups. Tree species have been less likely to go extinct than shrubs, climbers, or epiphytes. But half of the tree species present in 1994 were represented by only one or two individuals ≥ 5 cm dbh and larger. Individual longevity may be the major correlate with persistence of plant species in isolated forest fragments. Shade-tolerant understory shrubs (mostly Rubiaceae ) and rattans ( Palmae ) have been particularly prone to extinction. Some species have probably proliferated during the period of isolation. The tree Calophyllum ferrugineum currently constitutes one quarter of all woody stems. A group of climbers has become very common and covers large areas, probably inhibiting tree regeneration. We conclude that tiny fragments will act as refuges for tropical rain-forest plant species for decades, possibly even centuries after isolation but on their own they will not provide a permanent guarantee of the conservation of tropical biodiversity.     

Effects of Detectability on Estimates of Geographic Range Size in Bignonieae

Abstract: Extinction risk has not been evaluated for 96% of all described plant species. Given that the Global Strategy for Plant Conservation proposes preliminary conservation assessments of all described plant species by 2010, herbarium specimens (i.e., primary occurrence data) are increasingly being used to infer threat components from estimates of geographic range size. Nevertheless, estimates of range size based on herbarium data may be inaccurate due to collection bias associated with interspecific variation in detectability. We used data on 377 species of Bignonieae to test the hypothesis that there is a positive relationship between detectability and estimates of geographic range size derived from herbarium specimens. This relationship is expected if the proportion of the true geographic range size of a species that is documented by herbarium specimens is given by the product of the true geographic range size and the detectability of the species, assuming no relationship between true geographic range size and detectability. We developed 4 measures of detectability that can be estimated from herbarium data and examined the relationship between detectability and 2 types of estimates of geographic range size: area of occupancy and extent of occurrence. Our results from regressing estimates of extent of occurrence and area of occupancy on detectability across genera provided no support for this hypothesis. The same was true for regressions of estimated extent of occurrence on detectability across species within genera. Nevertheless, regressions of estimated area of occupancy on detectability across species within genera provided partial support for our hypothesis. We considered 3 possible explanations for this mixed outcome: violation of the assumption of no relationship between true geographic range size and detectability; the relationships between estimated geographic range size and detectability may be an artifact of a negative relationship between estimated area of occupancy and the sampling variance of detectability; detectability may have had 2 opposite effects on estimated species range sizes: one determines the proportion of the true range of a species documented by herbarium specimens and the other determines the distribution of true range size for the species actually observed with herbarium data. Our findings should help improve understanding of the potential biases incurred with the use of herbarium data.     

Null model analysis of species nestedness patterns

Nestedness is a common biogeographic pattern in which small communities form proper subsets of large communities. However, the detection of nestedness in binary presence-absence matrices will be affected by both the metric used to quantify nestedness and the reference null distribution. In this study, we assessed the statistical performance of eight nestedness metrics and six null model algorithms. The metrics and algorithms were tested against a benchmark set of 200 random matrices and 200 nested matrices that were created by passive sampling. Many algorithms that have been used in nestedness studies are vulnerable to type I errors (falsely rejecting a true null hypothesis). The best-performing algorithm maintains fixed row and fixed column totals, but it is conservative and may not always detect nestedness when it is present. Among the eight indices, the popular matrix temperature metric did not have good statistical properties. Instead, the Brualdi and Sanderson discrepancy index and Cutler's index of unexpected presences performed best. When used with the fixed-fixed algorithm, these indices provide a conservative test for nestedness. Although previous studies have revealed a high frequency of nestedness, a reanalysis of 288 empirical matrices suggests that the true frequency of nested matrices is between 10% and 40%.     

Significance tables for the exact variance test for the Poisson distribution with alternative underdispersion

Fisher (1950) introduced the variance or dispersion index test statistic to test deviations of the Poisson distribution. For this test approximate critical values exist for large sample sizes. If the number of observations is small this approximation can lead to a wrong conclusion. For small samples, the exact critical values can only be derived by enumeration of all possibilities. Tables of critical values for overdispersion already exist (e.g., Rao and Chakravarti, 1956) However, in many biological situations underdispersion, a more-regular-than-Poisson distribution, is a common phenomenon. Therefore, we have tabulated in this paper the one-tailed critical values for a small number of observations under the null hypothesis (H₀) that the random variable is Poisson distributed against the alternative hypothesis of underdispersion. With the help of this table, the hypothesis that the observations in a data set are Poisson distributed, can be tested easily with the variance test. The tables are illustrated with examples from the literature and some observations from our own research. In general, the ² approximation gives a smaller significance level than the exact variance test.     

Modeling and Predicting Species Occurrence Using Broad-Scale Environmental Variables: an Example with Butterflies of the Great Basin

Abstract: If occurrence of individual species can be modeled as a function of easily quantified environmental variables (e.g., derived from a geographic information system [GIS]) and the predictions of these models are demonstrably successful, then the scientific foundation for management planning will be strengthened. We used Bayesian logistic regression to develop predictive models for resident butterflies in the central Great Basin of western North America. Species inventory data and values for 14 environmental variables from 49 locations (segments of canyons) in the Toquima Range ( Nevada, U.S.A.) were used to build the models. Squares of the environmental variables were also used to accommodate possibly nonmonotonic responses. We obtained statistically significant models for 36 of 56 (64%) resident species of butterflies. The models explained 8–72% of the deviance in occurrence of those species. Each of the independent variables was significant in at least one model, and squared versions of five variables contributed to models. Elevation was included in more than half of the models. Models included one to four variables; only one variable was significant in about half the models. We conducted preliminary tests of two of our models by using an existing set of data on the occurrence of butterflies in the neighboring Toiyabe Range. We compared conventional logistic classification with posterior probability distributions derived from Bayesian modeling. For the latter, we restricted our predictions to locations with a high ( 70%) probability of predicted presence or absence. We will perform further tests after conducting inventories at new locations in the Toquima Range and nearby Shoshone Mountains, for which we have computed environmental variables by using remotely acquired topographic data, digital-terrain and microclimatic models, and GIS computation.     

Inventories and Distribution of Radiocaesium in Arctic Marine Sediments: Influence of Biological and Physical Processes

Extensive surveys of sediment burdens of radiocaesium, specifically ¹³⁷Cs, and other radioactive contaminants in the Arctic during the 1990's, indicate that almost all anthropogenic radionuclides buried on continental shelves adjacent to Alaska are derived from global bomb fallout. the ¹³⁷Cs (half-life: 30.2y) activities observed in surface (0-4 cm) marine sediments however, vary widely, albeit much less than the expected current inventory resulting from bomb fallout at this latitude (∼100mBq cm^-2). This observed geographical variation provided the opportunity to evaluate physical and biological mechanisms that may affect caesium biogeochemistry on Arctic continental shelves. We investigated whether high biological productivity in portions of the Bering and Chukchi Seas is effective in removing dissolved radiocaesium from the water column, and whether biological production in overlying water affects total radiocaesium inventories in sediments. Based upon C/N ratios in the organic fraction of shallow sediments, we found no evidence that higher inventories or surface activities of radiocaesium are present in areas with higher deposition of particulate organic matter. Based upon stable carbon isotope ratios of organic matter in sediments, we found no evidence that terrestrial runoff contributes proportionally to higher surface activities, although terrestrial runoff may affect total inventories of the radionuclide. Radiocaesium content of surface sediments was significantly correlated with total organic carbon content of sediments and the proportion of sediments in the finest sediment fractions. Because high current flow can also be expected to influence distributions of those sedimentary parameters, we conclude that re-distribution of