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opencc-by-4.0Jun 2020View details →

FIGURE 2 in A new species of Cyphocharax (Characiformes: Curimatidae) with a horizontal color pattern from the rio Tapajós drainage, Amazon basin, Brazil

FIGURE 2 | Map of the lower Tapajós basin and its confluence with rio Amazonas showing the distribution of Cyphocharax cramptoni. The red dot indicates the type locality.

opencc-by-4.0Jun 2020View details →

FIGURE 1 in A new species of Cyphocharax (Characiformes: Curimatidae) with a horizontal color pattern from the rio Tapajós drainage, Amazon basin, Brazil

FIGURE 1 | Cyphocharax cramptoni; A. holotype, ZUE C 17124, 49.7 mm SL, Brazil, Pará, Santarém, rio Mentaí; B. Living specimen, ZUEC 12071, 30.2 mm SL, same data as holotype.

opencc-zeroNov 2021View details →

Data from: Drivers of global pre-industrial patterns of species turnover in planktonic foraminifera

Anthropogenic climate change is altering global biogeographical patterns. However, it remains difficult to quantify how bioregions are changing because pre-industrial records of species distributions are rare. Marine microfossils, such as planktonic foraminifera, are preserved in seafloor sediments and allow the quantification of bioregions in the past. Using a recently compiled data set of pre-industrial species composition of planktonic foraminifera in 3802 worldwide seafloor sediments, we employed multivariate and statistical model-based approaches to study spatial turnover in order to 1) quantify planktonic foraminifera bioregions and 2) understand the environmental drivers of species turnover. Four latitudinally banded bioregions emerge from the global assemblage data. The polar and temperate bioregions are bi-hemispheric, supporting the idea that planktonic foraminifera species are not limited by dispersal. The equatorial bioregion shows complex longitudinal patterns and overlaps in sea surface temperature (SST) range with the tropical bioregion. Compositional-turnover models (Bayesian bootstrap generalised dissimilarity models) identify SST as the strongest driver of species turnover. The turnover rate is constant across most of the SST gradient, showing no SST threshold values with rapid shifts in species composition, but decelerates above 25°C, suggesting SST is less predictive of species composition in warmer waters. Other environmental predictors affect species turnover non-linearly, and their importance differs across regions. In the Pacific ocean, net primary productivity below 500 mgC m−2 day−1 drives fast compositional change. Water depth values below 3000 m (which affect calcareous microfossil preservation) increasingly drive changes in species composition among death assemblages in the Pacific and Indian oceans. Together, our results suggest that the dynamics of planktonic foraminifera bioregions are expected to be highly responsive to climate change; however, at lower latitudes, environmental drivers other than SST may affect these dynamics.

opencc-zeroApr 2022View details →

Investigating cooccurrence patterns and dynamics for many imperfectly detected species, using a log-linear modelling parameterisation

1. Patterns in, and the underlying dynamics of, species cooccurrence is of interest in many ecological applications. Unaccounted for, imperfect detection of the species can lead to misleading inferences about the nature and magnitude of any interaction. A range of different parameterisations have been published that could be used with the same fundamental modelling framework that accounts for imperfect detection, although each parameterisation has different advantages and disadvantages. 2. We propose a parameterisation based on log-linear modelling that does not require a species hierarchy to be defined (in terms of dominance), and enables a numerically robust approach for estimating covariate effects. 3. Conceptually the parameterisation is equivalent to using the presence of species in the current, or a previous, time period as predictor variables for the current occurrence of other species. This leads to natural, 'symmetric', interpretations of parameter estimates. 4. The parameterisation can be applied to many species, in either a maximum-likelihood or Bayesian estimation framework. We illustrate the method using camera trapping data collected on three mesocarnivore species in South Texas.

Fig. 5 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis

Fig. 5. (left column) Distribution-based Redundancy Analysis (db-RDA) ordination diagram of Lake Chapala with environmental variables (thick arrows), atherinopsids species (italic letters), sampling sites (numbers), and principal coordinates axes (thin arrows) at dry season (a: May of 1999) and rainy season (b: August of 1999; c: 2000). The fish are: jordani = Chirostoma jordani; consocium = Chirostoma consocium; labarcae = Chirostoma labarcae. The environmental variables are: Temp = temperature, DO = dissolved oxygen, Sal = salinity. In figure 5c shallow sites are in italic and deep sites in regular.

Fig. 3 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis

Fig. 3. GAM results for May and August of site influence on fish density to show differential distribution of species in Lake Chapala. a: Chirostoma jordani; b: Chirostoma consocium; c: Chirostoma labarcae. Circles represent the residuals. Spline fit (solid line) is bound by 95% confidence intervals (dotted lines).

Fig. 2 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis

Fig. 2. GAM results for May of environmental characteristics influence on fish density. a: effect of depth (m) on Chirostoma jordani; b: effect of temperature (°C) on C. jordani; c: effect of salinity on C. consocium. Circles represent the residuals. Spline fit (solid line) is bound by 95% confidence intervals (dotted lines).

Fig. 1 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis

Fig. 1. Map of Lake Chapala, Mexico. Numbers in bold represent sample sites and numbers in italic lake depths.

opencc-by-4.0Nov 2013View details →

Fig. 2. – Species prediction for a grid cell. A in Geographical patterns of woody plants' functional traits in Burkina Faso

Fig. 2. – Species prediction for a grid cell. A. Average of maximal plant size; B. Percentage of spinescent species; C. Percentage of species containing latex; D. Percentage of species with compound leaves.

opencc-by-4.0Dec 2020View details →

Fig. 4 in Morphotype And Multivariate Analysis Of The Occlusal Pattern Of The First Lower Molar In European And Asian Arvicoline Species (Rodentia, Microtus, Alexandromys)

Fig. 4. Differentiation on 16 Microtus samples by the morphotypic variation of the occlusal pattern.

opencc-by-4.0Dec 2020View details →

Fig. 3 in Morphotype And Multivariate Analysis Of The Occlusal Pattern Of The First Lower Molar In European And Asian Arvicoline Species (Rodentia, Microtus, Alexandromys)

Fig. 3. Differentiation on six East Asian vole samples by the morphotypic variation of the occlusal pattern.

opencc-by-4.0Dec 2020View details →

Fig. 1 in Morphotype And Multivariate Analysis Of The Occlusal Pattern Of The First Lower Molar In European And Asian Arvicoline Species (Rodentia, Microtus, Alexandromys)

Fig. 1. Elements of the occlusal surface of m1 (the terminology follows van der Meulen, Zagwijn, 1974; Maul et al., 2007).

opencc-zeroApr 2022View details →

Data and code for Winter conditions structure extratropical patterns of species richness of amphibians, birds, and mammals globally

This repository contains the dataset analyzed in 'Winter conditions structure extratropical patterns of species richness of amphibians, birds, and mammals globally' - published in the journal Global Ecology and Biogeography - and the R code used to generate the correlations, generalized additive models, and related figures presented in the manuscript. Column descriptions for the data can be found in the associated README.txt file. Please refer to the manuscript for further detail on the variables and how they were derived. The Winter Indices (WIs) were derived using satellite remote sensing data from optical (MODIS, snow cover) and microwave (MEaSUREs freeze/thaw, frozen ground) sensors. The species richness maps were derived using IUCN range maps for individual species of amphibians, birds, and mammals (data requests can be made here: <a href="https://www.iucnredlist.org/resources/spatial-data-download">https://www.iucnredlist.org/resources/spatial-data-download</a>). Climatic varibales were derived from WorldClim v2.0 data, elevation from USGS GMTED2010 data, and primary productivity from the cumulative dynamic habitat index available here: <a href="http://silvis.forest.wisc.edu/maps-data/">http://silvis.forest.wisc.edu/maps-data/</a>.

opencc-zeroOct 2021View details →

Opposing community assembly patterns for dominant and non-dominant plant species in herbaceous ecosystems globally

Biotic and abiotic factors interact with dominant plants —the locally most frequent or with the largest coverage— and non-dominant plants differently, partially because dominant plants modify the environment where non-dominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing non-dominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit non-dominants. Hence, the nature of interactions among non-dominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among non-dominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co-dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that non-dominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (<50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more non-dominant species than expected at random, suggesting that traits common in non-dominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/non-dominant disparity. We found different assembly patterns for dominants and non-dominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Non-dominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to non-dominant ones, dominant species could have a stronger positive effect on some non-dominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those non-dominants. These results show that the dominant/non-dominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities.

opencc-zeroJun 2022View details →

Broad-scale patterns of geographic avoidance between species emerge in the absence of fine-scale mechanisms of coexistence

Aim: The need to forecast range shifts under future climate change has motivated an increasing interest in better understanding the role of biotic interactions in driving diversity patterns. The contribution of biotic interactions to shaping broad-scale species distributions is however, still debated, partly due to the difficulty of detecting their effects. We aim to test whether spatial exclusion between potentially competing species can be detected at the species range scale, and whether this pattern relates to fine-scale mechanisms of coexistence. Location: Western Palearctic Time period: Anthropocene Taxa: bats (Chiroptera) Methods: We develop and evaluate a measure of geographic avoidance that uses outputs of species distribution models to quantify geographic exclusion patterns expected if interspecific competition affects broad-scale distributions. We apply the measure to 10 Palearctic bat species belonging to four morphologically similar cryptic groups in which competition is likely to occur. We compare outputs to null models based on pairs of virtual species and to expectations based on ecological similarity and fine-scale coexistence mechanisms. We project changes in range suitability under climate change taking into account effects of geographic avoidance. Results: Values of geographic avoidance were above null expectations for two cryptic species pairs, suggesting that interspecific competition could have contributed to shaping their broad-scale distributions. These two pairs showed highest levels of ecological similarity and no trophic or habitat partitioning. Considering the role of competition modified predictions of future range suitability. Conclusions: Our results support the role of interspecific competition in limiting the geographic ranges of morphologically similar species in the absence of fine-scale mechanisms of coexistence. This study highlights the importance of incorporating biotic interactions into predictive models of range shifts under climate change, and the need for further integration of community ecology with species distribution models to understand the role of competition in ecology and biogeography.

opencc-zeroSep 2022View details →

Data and code from: Functional rarity of plants in German hay meadows - patterns on the species level and mismatches with community species richness

Functional rarity (FR) - a feature combining a species' rarity with the distinctiveness of its traits - represents a promising tool to better understand the ecological importance of rare species and consequently to protect functional diversity more efficiently. Yet, we lack a systematic understanding of FR on both the species level (which species are functionally rare and why) and the community level (how is FR associated with biodiversity and environmental conditions). Here, we quantify FR for 218 plant species from German hay meadows on a local, regional, and national scale by combining data from 6500 vegetation relevés and 15 ecologically relevant traits. We investigate the association between rarity and trait distinctiveness on different spatial scales via correlation measures and show which traits lead to low or high trait distinctiveness via distance-based redundancy analysis. We test how species richness and FR are correlated and use boosted regression trees to determine environmental conditions driving species richness and FR. On the local scale, only rare species showed high trait distinctiveness while on larger spatial scales rare and common species showed high trait distinctiveness. As infrequent trait attributes (e.g., legumes, low clonality) led to higher trait distinctiveness, we argue that functionally rare species are either specialists or transients. While specialists occupy a particular niche in hay meadows leading to lower rarity on larger spatial scales, transients display distinct but maladaptive traits resulting in high rarity across all spatial scales. More functionally rare species than expected by chance occurred in species-poor communities indicating that they prefer environmental conditions differing from characteristic conditions of species-rich hay meadows. Finally, we argue that functionally rare species are not necessarily relevant for nature conservation, since many were transients from surrounding habitats. Yet, FR can facilitate our understanding of why species are rare in a habitat and under which conditions these species occur.

Fig. 2 in Ventral And Lateral Spot Patterns Differentiation Between Three Smooth Newt Species (Amphibia: Salamandridae: Lissotriton)

Fig. 2. Color patterns of smooth newt species. Lissotriton schmidtleri: males from Domurcalı (lateral view) and Dursunköy (ventral view), females from Yassıören (lateral view) and Ka- racabey (ventral view), Turkey; L. vulgaris: Gatchina, Russia; L. kosswigi: males from Mollafeneri (lateral view) and Hacılar (ventral view), females from Alibahadır Köyü, Turkey; L. lanzi: males from Ldzaa (lateral view) and Sukhum (ventral view), females from Ldzaa

Fig. 1 in Ventral And Lateral Spot Patterns Differentiation Between Three Smooth Newt Species (Amphibia: Salamandridae: Lissotriton)

Fig. 1. Distribution of Lissotriton vulgaris, L. schmidtleri and L. kosswigi in the Western Palearctic (A) and western Turkey (B). Numbers for localities are given in Table 1

Fig. 4 in Ventral And Lateral Spot Patterns Differentiation Between Three Smooth Newt Species (Amphibia: Salamandridae: Lissotriton)

Fig. 4. Plot of centroids for females (A) and males (B) of Lissotriton kosswigi, L. schmidtleri and L. vulgaris in the space of the first and second canonical discriminant axes

Fig. 3 in Ventral And Lateral Spot Patterns Differentiation Between Three Smooth Newt Species (Amphibia: Salamandridae: Lissotriton)

Fig. 3. Polygons selected on the ventral surface of newts (A) and types of dark spot arrangements located on the border between lateral and ventral surfaces (B), where r is random