Comparative studies of ecological niche variation among central and peripheral populations of Mediterranean endemic plants

The Mediterranean basin is a biodiversity hotspot, characterized by its high plant richness and endemism. It is a place of prime interest to test biogeographical hypotheses, such as the centre-periphery hypothesis. Empirical evidences have brought little support to it as a rule, suggesting complex eco-evolutionary mechanisms shape genetic and demographic characteristics. This thesis proposes a new framework that supports a precise evaluation of species history, geography and ecology to investigate genetic and demographic variation. In this perspective, we set up a study of 11 Mediterranean vascular plants to investigate changes in the micro-ecological niche between central and peripheral populations. Several shifts appeared which emphasized the ecological originality of peripheral population. Peripheral populations subsist in cooler and wetter climate compared to their mean central relatives, but are not marginal regarding their climatic niche. Several species presented similar distribution patterns on restricted areas in France, which may result from their persistence in micro-refugia during Pleistocene glaciations. This historical perspective was fundamental to explain patterns of floral polymorphism in Narcissus dubius. Spatial isolation and ecological originality confer to peripheral isolates a high evolutionary potential, and understanding fine scale ecological characteristics and distribution history is essential to shed light on processes driving plant diversity

Assessing the effect of sample bias correction in species distribution models

1. Open-source biodiversity databases contain a large number of species occurrence records but are often spatially biased; which affects the reliability of species distribution models based on these records. Sample bias correction techniques require data filtering which comes at the cost of record numbers, or require considerable additional sampling effort. Since independent data is rarely available, assessment of the correction technique often relies solely on performance metrics computed using subsets of the available – biased – data, which may prove misleading. 2. Here, we assess the extent to which an acknowledged sample bias correction technique is likely to improve models’ ability to predict species distributions in the absence of independent data. We assessed variation in model predictions induced by the aforementioned correction and model stochasticity; the variability between model replicates related to a random component (pseudo-absences sets and cross-validation subsets). We present, then, an index of the effect of correction relative to model stochasticity; the Relative Overlap Index (ROI). We investigated whether the ROI better represented the effect of correction than classic performance metrics (Boyce index, cAUC, AUC and TSS) and absolute overlap metrics (Schoener’s D, Pearson’s and Spearman’s correlation coefficients) when considering data related to 64 vertebrate species and 21 virtual species with a generated sample bias. 3. When based on absolute overlaps and cross-validation performance metrics, we found that correction produced no significant effects. When considering its effect relative to model stochasticity, the effect of correction was strong for most species at one of the three sites. The use of virtual species enabled us to verify that the correction technique improved both distribution predictions and the biological relevance of the selected variables at the specific site, when these were not correlated with sample bias patterns. 4. In the absence of additional independent data, the assessment of sample bias correction based on subsample data may be misleading. We propose to investigate both the biological relevance of environmental variables selected, and, the effect of sample bias correction based on its effect relative to model stochasticity. Accessibility maps Cross-validation Performance metrics Overlap Pseudo-absence selection Terrestrial vertebrates Variable selection Virtual speciespublishedVersio

Heterogeneous forest structures favor persistence of the grassland Mediterranean geophyte Gagea lacaitae

International audienceLand use changes in the northern Mediterranean basin threaten our ability to conserve its habitats and species. Reduced grazing has led to local declines in grassland species and colonization by forest species leading to conservation actions aimed at restoring open habitats. Recently, populations of Gagea lacaitae, a bulbous species typical of Mediterranean open xeric grasslands, have been discovered in forest clearings, an unexpected habitat for this species. Here, we surveyed 48 plots to characterize and compare the ecological niche of G. lacaitae growing in both open xeric and forest clearing habitats. We recorded floristic composition and plant cover and collected soil samples to measure water retention capacity, pH, organic matters and conductivity. Open xeric grasslands and forest clearings differ in plant cover, community composition, and microhabitat structure but not in plant diversity, mean soil conditions, or G. lacaitae cover. Key similarities in conditions allow this species to persist in woodlands that heterogenous enough to include clearings. Such habitats have value for conserving this species and should be sustained

Plants stand still but hide: Imperfect and heterogeneous detection is the rule when counting plants

International audienceThe estimation of population size and its variation across space and time largely relies on counts of individuals, generally carried out within spatial units such as quadrats or sites. Missing individuals during counting (i.e. imperfect detection) results in biased estimates of population size and trends. Imperfect detection has been shown to be the rule in animal studies, and most studies now correct for this bias by estimating detection probability. Yet this correction remains exceptional in plant studies, suggesting that most plant ecologists implicitly assume that all individuals are always detected. To assess if this assumption is valid, we conducted a field experiment to estimate individual detection probability in plant counts conducted in 1 × 1 m quadrats. We selected 30 herbaceous plant species along a gradient of conspicuousness at 24 sites along a gradient of habitat closure, and asked groups of observers to count individuals in 10 quadrats using three counting methods requiring progressively increasing times to complete (quick count, unlimited count and cell count). In total, 158 participants took part in the experiment, allowing an analysis of the results of 5024 counts. Over all field sessions, no observer succeeded in detecting all the individuals in the 10 quadrats. The mean detection rate was 0.44 (ranging from 0.11 to 0.82) for the quick count, 0.59 for the unlimited count (range 0.18–0.87) and 0.74 for the cell count (range 0.46–0.94). Detection probability increased with the conspicuousness of the target species and decreased with the density of individuals and habitat closure. The observer's experience in botany had little effect on detection probability, whereas detection was strongly affected by the time observers spent counting. Yet although the more time-consuming methods increased detection probability, none achieved perfect detection, nor did they reduce the effect on detection probability of the variables we measured. Synthesis. Our results show that detection is imperfect and highly heterogeneous when counting plants. To avoid biased estimates when assessing the size, temporal or spatial trends of plant populations, plant ecologists should use methods that estimate the detection probability of individuals rather than relying on raw counts

Spatially balanced sampling methods are always more precise than random ones for estimating the size of aggregated populations

International audiencePopulation size is a crucial parameter for both ecological research and conservation planning. When individuals are aggregated, estimating the size of a population through sampling raises methodological challenges, as the high variance between sampling units leads to imprecise estimates. Choosing the right sample design depending on the population aggregation level could improve the precision of estimates; however, this is difficult because studies comparing sample designs for aggregated populations have been limited to a few populations and sampling designs, so their results cannot be generalised. To address this gap, we combined simulations of spatial point populations and field counts of three plant species to compare the relative precision of estimates between three sampling methods: simple random sampling (SRS), systematic sampling (SYS) and spatially balanced sampling (SBS). Comparisons were performed on density and aggregation gradients for a range of sample sizes. Our simulations showed that SYS and SBS were always more precise than SRS when individuals were aggregated, reducing sampling variance up to 80% and 60%. The highest precision for estimating population size was always obtained when the average distance between sampling units equalled the diameter of the clusters (i.e. the groups of individuals). The difference in precision was similar for the natural populations, with sampling variance lowered by up to 75% (SYS) and 60% (SBS) compared to SRS. These findings lead us to recommend using SYS or SBS rather than SRS to estimate population size when individuals are spatially aggregated, as these consistently provide more precise estimates. Assessing cluster diameters in the field enables a quick assessment of the potential gain in precision to expect, and thus the best choice of sampling method depending on the trade-off between precision and field constraints

DRYAD_ms.ecography_quad

This excel file synthesis all data used for the quadratic analysis. Columns headers are detailed within the manuscript

Data from: Ecological niche differentiation in peripheral populations: a comparative analysis of eleven Mediterranean plant species

Aim: The “central-peripheral” hypothesis has provided a baseline for many studies of population dynamics and genetic variability at species distribution limits. Although peripheral populations are often assumed to occur in ecologically marginal conditions, little is known about whether they effectively occur in a distinct ecological niche. Location: Western Mediterranean basin. Time Period: 2013-2014. Major taxa studied: A cross-taxa analysis of 11 Mediterranean vascular plants. Methods: We quantified variation in the ecological niche between populations at the northern range limits of species in Mediterranean France and those in the central part of the distribution in continental Spain or Italy. We analyzed both the macro-ecological niche where populations occur in terms of broad habitat and altitudinal range and the micro-ecological niche where individual plants grow in terms of soil and structural biotic and abiotic characteristics. Results: Most species occur in a single broad habitat type common to central and peripheral populations and have a narrower altitudinal range in the latter. In contrast, for the micro-ecological niche we detected marked variation in several niche parameters among central and peripheral populations. Although many differences are species-specific some are common to several species. We found a trend towards narrower micro-niche breadth in peripheral populations. Main conclusions: Our results illustrate the importance of studying the precise ecological characteristics where plants grow and the pertinence of a multi-species approach to correctly assess niche variation. The ecological originality of peripheral populations underlines their evolutionary potential and conservation significance

The indigenous vascular flora of the forest domain of Anela (Sardinia, Italy)

The importance of mountains for plant diversity and richness is underestimated, particularly when transition zones between different bioclimates are present along altitudinal gradients. Here we present the first floristic data for a mountain area in the island of Sardinia (Italy), which exhibits Mediterranean bioclimates at the bottom and temperate bioclimate at the top. We discovered a very high floristic richness, despite the fact that the number of endemic taxa is not high and the number of exclusive taxa is very low. Many of the detected taxa are at their range periphery and/or ecological margin. We conclude that climate transition zones in Mediterranean mountains and especially on islands are key areas regarding plant biodiversity and should be better investigated and protected

Prioritization of natural habitats: A methodological framework applied to the French Mediterranean

International audienceLong-term preservation of habitats has become a cornerstone of modern conservation policies. As resources allocated to conservation actions are often limited, developing relevant prioritizing methods is necessary. Although many studies have been published on species prioritization, habitats have been the subject of less research. This study aims to develop a simple prioritization method suitable for habitats and appropriate to any typology. We analyzed literature to select criteria that would be the most accurate to rank habitats. Our final method consists in calculating a score based on four criteria: legal obligation, territorial responsibility, conservation condition and an extra criterion designed to fit local interests and objectives. The method is applied on habitats listed in Annex I of the Habitats Directive (92/43/EEC) on the territory of RESEDA-Flore, a network of stakeholders involved in the conservation of Mediterranean flora. Results highlight that dune habitats show the highest conservation values, while rocky habitats and caves obtain relatively low scores. At the top of the ranking, Mediterranean temporary ponds (3170), Dunes with Pinus pinea and/or Pinus pinaster forests (2270) and Coastal dunes with Juniperus spp. (2250) appear to be a high priority. These results can be used to design and implement habitat conservation strategies in the French Mediterranean

Assessing the effect of sample bias correction in species distribution models

Open-source biodiversity databases contain a large amount of species occurrence records, but these are often spatially biased, which affects the reliability of species distribution models based on these records. Sample bias correction techniques include data filtering at the cost of record numbers or require considerable additional sampling effort. However, independent data are rarely available and assessment of the correction technique must rely on performance metrics computed with subsets of the only available (biased) data, which may be misleading. Here we assess the extent to which an acknowledged sample bias correction technique is likely to improve models' ability to predict species distributions in the absence of independent data. We assessed the variation in model predictions induced by the correction and model stochasticity. We present an index of the effect of correction relative to model stochasticity, the Relative Overlap Index (ROI). We tested whether the ROI better represented the effect of correction than classic performance metrics and absolute overlap metrics using 64 vertebrate species and 21 virtual species with a generated sample bias. When based on absolute overlaps and cross-validation performance metrics, we found no effect of correction, except for cAUC. When considering its effect relative to model stochasticity, the effect of correction depended on the site and the species. Virtual species enabled us to verify that the correction actually improved distribution predictions and the biological relevance of the selected variables at the sites with a clear gradient of sample bias, and when species distribution predictors are not correlated with sample bias patterns.Comment: 17 pages, 8 figures + Appendi