Species Abundance Data Research Articles

Inferred seasonal interaction rewiring of a freshwater stream fish network

Despite evidence that seasonal variation may lead to the persistence of competing species, studies on the effect of seasonality on community network structures are sparse. Identifying whether seasonal network changes are the result of turnover or rewiring (i.e. rearrangement of interactions among species), also remains understudied in multi‐trophic communities. Using species abundance data for 38 species over three years (from nine sites across central/eastern United States) and a novel tree‐based inference method, we constructed seasonal networks for a multi‐trophic freshwater stream fish community. We found that seasonality influences species interactions, particularly through rewiring (81%) as compared to species turnover (19%). Moreover, the number of rewiring interactions was best explained by fish status as a piscivore/non‐piscivore and species maximum length (R2 = 0.41). Our findings suggest that rewiring may be a dominant process in stream fish communities experiencing seasonal environments and that traits linked to trophic‐level could be a good indicator of a species contribution to rewiring. As networks dominated by rewiring may be more robust, this network approach could be a valuable conservation tool for identifying which biological relationships must be retained for communities to avoid extinction.

Responses of global waterbird populations to climate change vary with latitude

Most research on climate change impacts on global biodiversity lacks the resolution to detect changes in species abundance and is limited to temperate ecosystems. This limits our understanding of global responses in species abundance—a determinant of extinction risk and ecosystem function and services—to climate change, including in the highly biodiverse tropics. We address this knowledge gap by quantifying the abundance response of waterbirds, an indicator taxon of wetland biodiversity, to climate change at 6,822 sites between 55° S and 64° N. Using 1,303,651 count records of 390 species, we show that with temperature increase, the abundance of species and populations decreased at lower latitudes, particularly in the tropics, but increased at higher latitudes. These contrasting latitudinal responses indicate potential global-scale poleward shifts of species abundance under climate change. The negative responses to temperature increase in tropical species are of conservation concern, as they are often also threatened by other anthropogenic factors. Gaps in geographic coverage of species abundance data, especially in the tropics, make determining species’ responses to climate change difficult. Modelling a dataset on global waterbird abundance shows abundance declines in the tropics and increases at higher latitudes when temperatures increase.

A wavelet-based approach to revealing the Tweedie distribution type in sparse data

We propose two approaches to the analysis of sparse stochastic data, which exhibit a power-law dependence between their first and second moments (Taylor’s law), and determining the respective power index, when it has a value between 1 and 2. They are based on the analysis of components of the Haar wavelet expansion. The first method uses a dependence between the first iterations of averaging and wavelet coefficients with the subsequent studying the statistics of zero paddings on the line, which corresponds the linear dependence between two first moments of the analysed distributions. The second method refers to Taylor’s plot formed by the full set of wavelet coefficients. It is discussed that such representations provide also an opportunity to check time–scale stability of analysed data and distinguish between particular cases of the Tweedie probabilistic distribution. Both simulated series and real marine species abundance data for five spatial regions of the Pacific are used as example illustrating an applicability of these approaches.

Completing Linnaeus's inventory of the Swedish insect fauna: Only 5,000 species left?

Despite more than 250 years of taxonomic research, we still have only a vague idea about the true size and composition of the faunas and floras of the planet. Many biodiversity inventories provide limited insight because they focus on a small taxonomic subsample or a tiny geographic area. Here, we report on the size and composition of the Swedish insect fauna, thought to represent roughly half of the diversity of multicellular life in one of the largest European countries. Our results are based on more than a decade of data from the Swedish Taxonomy Initiative and its massive inventory of the country's insect fauna, the Swedish Malaise Trap Project The fauna is considered one of the best known in the world, but the initiative has nevertheless revealed a surprising amount of hidden diversity: more than 3,000 new species (301 new to science) have been documented so far. Here, we use three independent methods to analyze the true size and composition of the fauna at the family or subfamily level: (1) assessments by experts who have been working on the most poorly known groups in the fauna; (2) estimates based on the proportion of new species discovered in the Malaise trap inventory; and (3) extrapolations based on species abundance and incidence data from the inventory. For the last method, we develop a new estimator, the combined non-parametric estimator, which we show is less sensitive to poor coverage of the species pool than other popular estimators. The three methods converge on similar estimates of the size and composition of the fauna, suggesting that it comprises around 33,000 species. Of those, 8,600 (26%) were unknown at the start of the inventory and 5,000 (15%) still await discovery. We analyze the taxonomic and ecological composition of the estimated fauna, and show that most of the new species belong to Hymenoptera and Diptera groups that are decomposers or parasitoids. Thus, current knowledge of the Swedish insect fauna is strongly biased taxonomically and ecologically, and we show that similar but even stronger biases have distorted our understanding of the fauna in the past. We analyze latitudinal gradients in the size and composition of known European insect faunas and show that several of the patterns contradict the Swedish data, presumably due to similar knowledge biases. Addressing these biases is critical in understanding insect biomes and the ecosystem services they provide. Our results emphasize the need to broaden the taxonomic scope of current insect monitoring efforts, a task that is all the more urgent as recent studies indicate a possible worldwide decline in insect faunas.

From species presences to abundances: Using unevenly collected plant species presences to disclose the structure and functioning of a dryland ecosystem

Abstract Species abundance data is essential to understand ecosystems structure and functioning and to support species and habitat conservation. However, most regional to global databases provide only presence or presence/absence data. The main aim of this paper is to develop a methodology to estimate plant species abundances from a presence/absence database using as a case-study the largest and one of the most diverse tropical dry forest of the world – the understudied Caatinga vegetation, that dominates in the drylands of Brazil. Plant data missed abundance estimations and derived from different sources, with uneven sampling efforts over space and time. Starting from the raw data, we considered only the presence records of terrestrial plant individuals identified to the species-level. Afterwards, we applied the re-sampling method to estimate species abundances thus obtaining database DB1. To deal with the uneven sampling effort along the study area and increase information reliability, we filtered DB1 in two ways: (i) we excluded re-sampling units with a lower sampling effort and produced the Database DB2; (ii) we excluded low occurrence species and build the Database DB3. The reliability of the databases was compared by calculating a measure of their completeness. DB1 had 789 species over 323 sampling units, DB2 retained 530 species distributed in 38 sampling units, and DB3 retained 48 species over 113 sampling units. In DB1 and DB2, despite the different number of species considered, the percentage of exotic (7%), endemism (14%), woody (44%), climber (12%), and herbaceous species (45%) was similar. DB3 included only native species (no exotic species) and displayed a higher percentage of endemism (29%) and woody species (79%), and a lower proportion of herbaceous species (21%) than DB1 and DB2. The databases obtained provide an important basis to improve Caatinga ecological knowledge and conservation: we suggest the use of DB2 to support conservation strategies, and of DB3 to support ecosystem structure and functioning studies. Moreover, the re-sampling methodology proposed to estimate plant abundances from presence data, dealing with uneven sampling efforts across large areas and over time, provides an important tool that may be used to obtain abundance data, often essential to the development of plant-based indicators of ecosystem structure and functioning, and to support conservation studies.

Community structure of vascular epiphytes: a neutral perspective

Vascular epiphytes form a diverse group of almost 30 000 species, yet theory concerning their community structure is still largely lacking. We therefore employed the simplest models of biodiversity, (near‐)neutral models, to generate hypotheses concerning their community structure. With recently developed tools for (near‐)neutral models we analyzed species abundance data from many samples in Central and South America which we divided into four metacommunities (Mesoamerica, Central America, Amazonia and Paraná), where for each metacommunity we considered two subsets differing in dispersal syndrome: an animal‐dispersed guild and a wind‐dispersed guild. We considered three models differing in the underlying speciation mode. Across all metacommunities, we found observed patterns to be indistinguishable from patterns generated by neutral or near‐neutral processes. Furthermore, we found that subdivision in different dispersal guilds was often supported, with recruitment limitation being stronger for animal‐dispersed species than for wind‐dispersed species. This is the first time that (near‐)neutral theory has been applied to epiphyte communities. Future efforts with additional data sets and more refined models are expected to further improve our understanding of community structure in epiphytes and will have to test the generality of our findings.

Biotic homogenization of wetland vegetation in the conterminous United States driven by Phalaris arundinacea and anthropogenic disturbance

Biotic homogenization (BH), the process by which β-diversity erodes, is suspected to be severe among plant communities due to widespread anthropogenic disturbances. However, few studies have directly linked anthropogenic disturbance with patterns of BH. The US National Wetlands Condition Assessment (NWCA) provides an opportunity to investigate patterns of β-diversity related to anthropogenic disturbances. Our objectives were to compare β-diversity between highly, intermediately and less-disturbed herbaceous emergent wetlands across the temperate region of the conterminous US, and to identify species with greatest influence on β-diversity patterns within disturbance categories. Using species occurrence and abundance data, average distances to group centroids in ordination space were used to assess wetland β-diversity across a disturbance gradient. Species contributions to β-diversity were calculated per disturbance category. Compared to the least and intermediately disturbed wetlands, highly disturbed wetlands had significantly lower β-diversity based on species abundances across the study area. When using only species occurrences, highly disturbed wetlands had significantly lower β-diversity than intermediately disturbed wetlands. No significant differences were found amongst disturbance categories at the within-site scale. The invasive grass Phalaris arundinacea had the greatest influence on β-diversity, especially in the most disturbed wetlands. Our results demonstrate that anthropogenic disturbances have homogenized regional botanical diversity. This homogenization is a function of disturbance intensity, which, after a threshold is crossed creates environmental conditions that lead to the local dominance of a single, widespread invader. This process is repeated across the region, scaling up to homogenize the flora of the entire region.

The Burgess Shale paleocommunity with new insights from Marble Canyon, British Columbia

AbstractThe middle (Wuliuan Stage) Cambrian Burgess Shale is famous for its exceptional preservation of diverse and abundant soft-bodied animals through the “thick” Stephen Formation. However, with the exception of the Walcott Quarry (Fossil Ridge) and the stratigraphically older Tulip Beds (Mount Stephen), which are both in Yoho National Park (British Columbia), quantitative assessments of the Burgess Shale have remained limited. Here we first provide a detailed quantitative overview of the diversity and structure of the Marble Canyon Burgess Shale locality based on 16,438 specimens. Located 40 km southeast of the Walcott Quarry in Kootenay National Park (British Columbia), Marble Canyon represents the youngest site of the “thick” Stephen Formation. We then combine paleoecological data sets from Marble Canyon, Walcott Quarry, Tulip Beds, and Raymond Quarry, which lies approximately 20 m directly above the Walcott Quarry, to yield a combined species abundance data set of 77,179 specimens encompassing 234 species-level taxa. Marble Canyon shows significant temporal changes in both taxonomic and ecological groups, suggesting periods of stasis followed by rapid turnover patterns at local and short temporal scales. At wider geographic and temporal scales, the different Burgess Shale sites occupy distinct areas in multivariate space. Overall, this suggests that the Burgess Shale paleocommunity is far patchier than previously thought and varies at both local and regional scales through the “thick” Stephen Formation. This underscores that our understanding of Cambrian diversity and ecological networks, particularly in early animal ecosystems, remains limited and highly dependent on new discoveries.

Biodiversity and structure of marine sponge assemblages around a subtropical island

We evaluated the structural responses of marine sponge assemblages to different substrates as well as their positioning around Ilha Grande, a local hotspot of marine biodiversity sheltered in a bay area off Southeast Brazil. Sampling sites were distributed between sides of the island facing the continent (North) and ocean (South) across two depth-dependent substrates. As proved by ordination and permutation analyses, these two factors accounted for nearly half the variation observed among assemblages, either with species abundance or coverage area data. Out of 46 OTUs surveyed (~ 3000 individuals), Tedania (Tedania) ignis, Scopalina ruetzleri, and Iotrochota arenosa dominated the community, even though most of the dissimilarity detected among assemblages relied on 20% of the OTUs. The northern side was proved as more diverse, and the south-facing side held more unspecific, putatively new OTUs. Assemblages dwelling on rocky-to-sandy interface bottoms were meager in species number, although they mainly included Dragmacidon reticulatum and the endemic Brazilian sponge Polymastia janeirensis. By highlighting structuring factors operating on Ilha Grande’s sponge assemblage, we hope to support future monitoring surveys on an environment increasingly impacted by human activities over the years.

Prediction of Neighbor-Dependent Microbial Interactions From Limited Population Data.

Modulation of interspecies interactions by the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method termed the Minimal Interspecies Interaction Adjustment (MIIA) that predicts the reorganization of interaction networks in response to the addition of new species such that the modulation in interaction coefficients caused by additional members is minimal. While the theoretical basis of MIIA was established through the previous work by assuming the full availability of species abundance data in axenic, binary, and complex communities, its extension to actual microbial ecology can be highly constrained in cases that species have not been cultured axenically (e.g., due to their inability to grow in the absence of specific partnerships) because binary interaction coefficients – basic parameters required for implementing the MIIA – are inestimable without axenic and binary population data. Thus, here we present an alternative formulation based on the following two central ideas. First, in the case where only data from axenic cultures are unavailable, we remove axenic populations from governing equations through appropriate scaling. This allows us to predict neighbor-dependent interactions in a relative sense (i.e., fractional change of interactions between with versus without neighbors). Second, in the case where both axenic and binary populations are missing, we parameterize binary interaction coefficients to determine their values through a sensitivity analysis. Through the case study of two microbial communities with distinct characteristics and complexity (i.e., a three-member community where all members can grow independently, and a four-member community that contains member species whose growth is dependent on other species), we demonstrated that despite data limitation, the proposed new formulation was able to successfully predict interspecies interactions that are consistent with experimentally derived results. Therefore, this technical advancement enhances our ability to predict context-dependent interspecies interactions in a broad range of microbial systems without being limited to specific growth conditions as a pre-requisite.

Enhanced inference of ecological networks by parameterizing ensembles of population dynamics models constrained with prior knowledge

BackgroundAccurate network models of species interaction could be used to predict population dynamics and be applied to manage real world ecosystems. Most relevant models are nonlinear, however, and data available from real world ecosystems are too noisy and sparsely sampled for common inference approaches. Here we improved the inference of generalized Lotka–Volterra (gLV) ecological networks by using a new optimization algorithm to constrain parameter signs with prior knowledge and a perturbation-based ensemble method.ResultsWe applied the new inference to long-term species abundance data from the freshwater fish community in the Illinois River, United States. We constructed an ensemble of 668 gLV models that explained 79% of the data on average. The models indicated (at a 70% level of confidence) a strong positive interaction from emerald shiner (Notropis atherinoides) to channel catfish (Ictalurus punctatus), which we could validate using data from a nearby observation site, and predicted that the relative abundances of most fish species will continue to fluctuate temporally and concordantly in the near future. The network shows that the invasive silver carp (Hypophthalmichthys molitrix) has much stronger impacts on native predators than on prey, supporting the notion that the invader perturbs the native food chain by replacing the diets of predators.ConclusionsEnsemble approaches constrained by prior knowledge can improve inference and produce networks from noisy and sparsely sampled time series data to fill knowledge gaps on real world ecosystems. Such network models could aid efforts to conserve ecosystems such as the Illinois River, which is threatened by the invasion of the silver carp.

Different but valuable: Anthropogenic habitats as genetic diversity reservoirs for endangered dry grassland species – A case study of Stipa pennata

Abstract Increasing urbanisation has led to the fragmentation of natural habitats and biodiversity decline. In Central Europe, this fate has befallen semi-natural xerothermic grasslands. However, in the case of species well adapted to open habitats, urbanisation may positively affect dispersal. In many places specialised xerothermic species start to spread in secondary habitats such as roadsides or railway embankments. However, little is known about the genetic variability of such newly-established populations. In an era of growing anthropogenic pressure, understanding the role of secondary, anthropogenic habitats in the maintenance biodiversity should be considered a crucial issue in the conservation of species associated with Central European dry grasslands. Therefore, on the basis of a combined analysis of xerothermic species abundance, bioclimatic and soil data, and genetic diversity, we wish to examine the suitability of secondary habitats (as substitutes for primary) and to demonstrate their role in the conservation of xerothermic species. Our results suggest that smaller competition for light and greater habitat connectivity indicate suitability of habitats for xerothermic species conservation. On one hand, the occurrence of these species in secondary habitats may be limited by the pressure of expansive grasses, on the other, the negative impact of the latter is buffered by the reduced presence of shrubs, and thus the greater availability of light. Plant communities from secondary habitats are less richness in xerothermic species, and particular species are less abundant, for this reason secondary habitats should be treated more as refuges (with suboptimal conditions) than as substitution habitats. But yet, Stipa pennata populations from secondary habitats do not suffer from genetic depauperation. Populations from secondary habitats are characterised by comparable share of two genotypes, indicating existence of gene flow between populations from south and north-west part of studied area. Through the maintenance of meta-population processes by means of dynamic connectivity between habitats on a landscape scale, secondary habitats possess an undoubtedly high conservation value for xerothermic species.

Ecological similarity explains species abundance distribution of small mammal communities

For several decades, ecologists have been trying to explain how species abundance distributions (SAD) emerge within communities. Niche models predict that species habitat requirements and life-history traits determine SADs. Here, based on predictions from a well-known niche-based SAD (Sugihara's model), we tested whether abundant species are ecologically less similar among each other than less abundant ones, and whether the strength of this relationship is reduced in high productivity areas. Using species abundance and trait data from 88 small mammal communities around the world we found that the most abundant species are similar to other abundant species, but less similar to rare species. However, this relationship is weakened in high-productivity areas, such as the tropics. These results suggest that niche differences moderate species abundances, and that low-productivity habitats have a reduced ecological space, especially for specialist species. A next step to uncover biological processes underlying the formation of SADs is to understand how they are influenced by the order of species arrivals during the assembly of communities.

Lichen species as element bioindicators for air pollution in the eastern United States of America

AbstractLichen element (N, S, metals) indicators of local air pollution load (a widely used technique) are recommended for five predefined regions covering central and southern parts of the eastern United States. The final recommendations integrate the advice of regional lichenologists, information from regional floras, and species abundance data from a United States Forest Service Forest Inventory and Analysis Program (FIA) lichen database for 11 of the 21 covered eastern states. Recommended species were frequent in their region, easy for nonspecialists to distinguish in the field after training, and easy to handle using clean protocols. Regression models of species abundance in FIA plots from five southeastern states vs. climate, air pollution (both from a regional lichen response model) and type of nearby landcover (from the National Land Cover Database) identified species’ environmental limitations. Punctelia rudecta is recommended for cooler forested uplands of all regions, with three Physcia species combined and Punctelia missouriensis for isolated woodlands or urban areas of three regions. Parmotrema hypotropum and P. hypoleucinum combined (weak environmental limitation) or P. perforatum. and P. subrigidum combined (limited in more polluted areas) are recommended for warmer Coastal Plains in two regions each. Additional species are recommended for single regions. Each species must be quantitatively evaluated in each region, to demonstrate indication reliability in practice and to calculate element data conversions between species for region-wide bioindication.

Conservation importance of previously undescribed abundance trends: increase in loggerhead turtle numbers nesting on an Atlantic island

AbstractFor many species abundance data from across their entire range are incomplete, and therefore it is difficult to accurately assess their conservation status. Even for species that are large, charismatic and relatively easy to study, conservation assessments are often hampered by lack of data. Here we report a marked, previously undescribed, increase in numbers at a breeding colony of the loggerhead turtle Caretta caretta, a species that is Critically Endangered in several parts of its range, and place this report in the global context for this species. We present a 10-year (2008–2017) dataset of nesting activities for this species on the island of Sal, one of the Cape Verde islands in the Atlantic Ocean. Foot patrols recorded 21,938 nests during the study period. We estimate that the annual number of nests on Sal increased from 506 in 2008 to 7,771 in 2017. Taking into account that there are only two known loggerhead turtle rookeries (on Masirah Island, Oman, and in Florida, USA) with > 50,000 nests reported annually, and few with > 1,000 nests per year, our results suggest that Sal is one of the 10 largest loggerhead turtle rookeries globally. Our work highlights the conservation significance of reporting trends in abundance at breeding sites for marine turtles and other taxa.

Proportional mixture of two rarefaction/extrapolation curves to forecast biodiversity changes under landscape transformation.

Progressive habitat transformation causes global changes in landscape biodiversity patterns, but can be hard to quantify. Rarefaction/extrapolation approaches can quantify within-habitat biodiversity, but may not be useful for cases in which one habitat type is progressively transformed into another habitat type. To quantify biodiversity patterns in such transformed landscapes, we use Hill numbers to analyse individual-based species abundance data or replicated, sample-based incidence data. Given biodiversity data from two distinct habitat types, when a specified proportion of original habitat is transformed, our approach utilises a proportional mixture of two within-habitat rarefaction/extrapolation curves to analyticallypredict biodiversity changes, with bootstrap confidence intervalsto assess sampling uncertainty. We also derive analytic formulas for assessing species composition (i.e. the numbers of shared and unique species) for any mixture of the two habitat types. Our analytical and numerical analyses revealed that species unique to each habitat type are the most important determinants of landscape biodiversity patterns.

Consideration of species-specific diatom indicators of anthropogenic stress in the Great Lakes.

Robust inferences of environmental condition come from bioindicators that have strong relationships with stressors and are minimally confounded by extraneous environmental variables. These indicator properties are generally assumed for assemblage-based indicators such as diatom transfer functions that use species abundance data to infer environmental variables. However, failure of assemblage approaches necessitates the interpretation of individual dominant taxa when making environmental inferences. To determine whether diatom species from Laurentian Great Lakes sediment cores have the potential to provide unambiguous inferences of anthropogenic stress, we evaluated fossil diatom abundance against a suite of historical environmental gradients: human population, agriculture, mining, atmospheric nutrient deposition, atmospheric temperature and ice cover. Several diatom species, such as Stephanodiscus parvus, had reliable relationships with anthropogenic stress such as human population. However, many species had little or no indicator value or had confusing relationships with multiple environmental variables, suggesting one should be careful when using those species to infer stress in the Great Lakes. Recommendations for future approaches to refining diatom indicators are discussed, including accounting for the effects of broad species geographic distributions to minimize region-specific responses that can weaken indicator power.

Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance.

Cystic fibrosis (CF) is a fatal genetic disease characterized by chronic lung infections due to aberrant mucus production and the inability to clear invading pathogens. The traditional view that CF infections are caused by a single pathogen has been replaced by the realization that the CF lung usually is colonized by a complex community of bacteria, fungi, and viruses. To help unravel the complex interplay between the CF lung environment and the infecting microbial community, we developed a community metabolic model comprised of the 17 most abundant bacterial taxa, which account for >95% of reads across samples, from three published studies in which 75 sputum samples from 46 adult CF patients were analyzed by 16S rRNA gene sequencing. The community model was able to correctly predict high abundances of the "rare" pathogens Enterobacteriaceae, Burkholderia, and Achromobacter in three patients whose polymicrobial infections were dominated by these pathogens. With these three pathogens removed, the model correctly predicted that the remaining 43 patients would be dominated by Pseudomonas and/or Streptococcus. This dominance was predicted to be driven by relatively high monoculture growth rates of Pseudomonas and Streptococcus as well as their ability to efficiently consume amino acids, organic acids, and alcohols secreted by other community members. Sample-by-sample heterogeneity of community composition could be qualitatively captured through random variation of the simulated metabolic environment, suggesting that experimental studies directly linking CF lung metabolomics and 16S sequencing could provide important insights into disease progression and treatment efficacy. IMPORTANCE Cystic fibrosis (CF) is a genetic disease in which chronic airway infections and lung inflammation result in respiratory failure. CF airway infections are usually caused by bacterial communities that are difficult to eradicate with available antibiotics. Using species abundance data for clinically stable adult CF patients assimilated from three published studies, we developed a metabolic model of CF airway communities to better understand the interactions between bacterial species and between the bacterial community and the lung environment. Our model predicted that clinically observed CF pathogens could establish dominance over other community members across a range of lung nutrient conditions. Heterogeneity of species abundances across 75 patient samples could be predicted by assuming that sample-to-sample heterogeneity was attributable to random variations in the CF nutrient environment. Our model predictions provide new insights into the metabolic determinants of pathogen dominance in the CF lung and could facilitate the development of improved treatment strategies.

Is genomic diversity a useful proxy for census population size? Evidence from a species-rich community of desert lizards.

Species abundance data are critical for testing ecological theory, but obtaining accurate empirical estimates for many taxa is challenging. Proxies for species abundance can help researchers circumvent time and cost constraints that are prohibitive for long-term sampling. Under simple demographic models, genetic diversity is expected to correlate with census size, such that genome-wide heterozygosity may provide a surrogate measure of species abundance. We tested whether nucleotide diversity is correlated with long-term estimates of abundance, occupancy and degree of ecological specialization in a diverse lizard community from arid Australia. Using targeted sequence capture, we obtained estimates of genomic diversity from 30 species of lizards, recovering an average of 5,066 loci covering 3.6Mb of DNA sequence per individual. We compared measures of individual heterozygosity to a metric of habitat specialization to investigate whether ecological preference exerts a measurable effect on genetic diversity. We find that heterozygosity is significantly correlated with species abundance and occupancy, but not habitat specialization. Demonstrating the power of genomic sampling, the correlation between heterozygosity and abundance/occupancy emerged from considering just one or two individuals per species. However, genetic diversity does no better at predicting abundance than a single day of traditional sampling in this community. We conclude that genetic diversity is a useful proxy for regional-scale species abundance and occupancy, but a large amount of unexplained variation in heterozygosity suggests additional constraints or a failure of ecological sampling to adequately capture variation in true population size.

A height-wood-seed axis which is preserved across climatic regions explains tree dominance in European forest communities

Environmental constraints on both functional traits and trait–trait correlation patterns are extremely relevant research questions to understand assembling mechanisms and scaling processes in ecology. In fact, community weighted mean (CWM) and functional diversity (FD) metrics assimilate meaningful complementary information from species to community level. Relating species abundance data from national forest inventories (France, Italy and Spain) with species trait values from published sources, we explored CWM and FD variations along climatic gradients for traits related to leaf, hydraulic and live history strategies, and how the CWM or the FD of single traits co-vary. Results show how the combined effects of water availability and temperature modulate CWM, and to a lower extent FD, of Western European forests. PCA on CWM traits data showed that main axis accounts for 46.6% of the variability and is represented by wood density, seed dry weight (SDW) and maximum height. This axis is similarly preserved in humid and dry areas and potentially related to competition ability, growth rates and successional status of tree species dominants. Furthermore, the second axis is associated with leaf wilting and cavitation resistance (P50), but not consistent in dry areas. Correlation patterns of FD data, which were partially preserved across climatic regions, showed one main axis involving the joint variability of all traits. However, between humid and dry areas determinants of SDW and P50 differ from all other traits. Results showed that at least a part of the co-variation patterns among traits change with climate conditions, suggesting scale-dependent effects which should be taken into account when scaling assembly mechanisms.