Luisa Conti

Aim: The influence of species phylogenetic relatedness on the formation of insular assemblages remains understudied in functional island biogeography, especially for terrestrial habitat islands (i.e. distinct habitat patches embedded in a matrix that differ in the prevailing environmental conditions). Here, we tested three eco‐evolutionary hypotheses: (1) functional specialization of species (i.e. specialism) is associated with phylogenetic clustering at the habitat archipelago scale, (2) such clustering increases with insularity at the habitat island scale and (3) traits indicative of effective local persistence strategies shape island specialism.Location: Terrestrial habitat islands, Europe (Fens in the Western Carpathians, Outcrops in Moravia and Mountaintops in the Cantabrian Range).Taxon: Angiosperms.Methods: We assessed the phylogenetic relatedness of habitat specialists in three different archipelagos composed of terrestrial habitat islands based on phylogenetic signals and phylogenetic diversity (PD) measures. We estimated the effect of insularity on PD using linear models and the effect of persistence traits on specialism using phylogenetic logistic regressions.Results: Our hypotheses were largely not supported. Outcrop and mountaintop specialist assemblages did not exhibit any phylogenetic structuring, whereas fen specialists were clustered at the archipelago scale. Therefore, insularity seems not to act as a selective force for phylogenetic structure, and ecologically important persistence traits do not operate as precursors of specialism.Main Conclusions: Our results show that species phylogenetic relatedness plays a minor role in shaping habitat island specialist assemblages. Furthermore, the effects of phylogenetic relatedness on assemblages of island specialists are system and scale dependent. Finally, accounting for species' phylogenetic relatedness on persistence traits yielded results similar to previous studies, which corroborates the positive relationship between insularity and functional traits (indicative of enhanced plant persistence abilities with increasing within‐archipelago insularity).

Biodiversity monitoring is constrained by cost- and labour-intensive field sampling methods. Increasing evidence suggests that remotely sensed spectral diversity (SD) is linked to plant diversity, holding promise for monitoring applications. However, studies testing such a relationship reported conflicting findings, especially in challenging ecosystems such as grasslands, due to their high temporal dynamism and variety. It follows that a thorough investigation of the key factors, such as the metrics applied (i.e., continuous, categorical) and phenology (e.g., flowering), influencing such a relationship is necessary. Thus, this study aims to assess the applicability of SD for plant diversity monitoring at the local scale by testing six different SD metrics while considering the effect of the presence of flowering on the relationship and resampling the original data to assess how spatial resolution affects the results. Taxonomic diversity was calculated based on data collected in 159 plots with 1.5 m ×1.5 m experimental mesic grassland communities. Spectral information was collected using a UAV-borne sensor measuring reflectance across six bands in the visible and near-infrared range at ∼2 cm spatial resolution. Our results show that, in the presence of flowering, the relationship is significant and positive only when SD is calculated using categorical metrics. Despite the observed significance, the variance explained by the models had very low values, with no evident differences when resampling spectral data to coarser pixel sizes. Such findings suggest that new insights into the possible confounding effects on the SD∼plant diversity in grassland communities are needed to use SD for monitoring purposes.

Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species' ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.

Summary: Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species’ ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, specially across different ecosystems. To address this, we compiled a global collection of long-term permanent vegetation records (>7000 plots from 78 datasets) from a wide range of habitats and combined this with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits and multivariate axes of trait variations (PCoA axes). We found that species with greater leaf dry matter content and seed mass were consistently more stable over time (lower variability in species abundance) although other leaf traits played a significant role as well, albeit weaker. Using multivariate axes did not improve predictions by specific traits. Our results confirm existing theory, providing compelling empirical evidence on the importance of specific traits, which point at ecological trade-offs in different resource use and dispersal strategies, on the stability of plant populations worldwide.

Aim: Species on islands are at high risk of extinction due to environmental changes, including global warming, land‐use alterations and invasions. At local scales, extinctions can be offset by strategies promoting in situ persistence. We explored how persistence‐related traits of plants—that is, linked to belowground resource conservation, growth, size and longevity—on edaphic islands respond to variation in insularity and the environment (soil and microclimate), including intraspecific variability, which is rarely considered in functional island biogeography. We hypothesised that plants facing strong insularity and harsh soil conditions are characterised by enhanced persistence abilities.Location: Shallow‐soil temperate dry grasslands on granite outcrops, Central Europe.Methods: We focussed on edaphic island specialist species belonging to different life histories, namely clonal and non‐clonal perennial plants. We used linear and linear mixed‐effect models to examine intra‐ and interspecific trait patterns versus variation in insularity, soil and microclimate.Results: Insularity tended to promote smaller plants (non‐clonal species) and belowground resource‐conservative strategies (both clonal and non‐clonal species), increasing the likelihood of local persistence. Soil also contributed largely to explaining persistence‐related trait patterns: plants growing in harsh soil conditions tended to be resource conservative. Clonal species are distinguished by highly consistent responses to variation in insularity and soil conditions, whereas non‐clonal plants showed distinct species‐specific responses.Main conclusions: Our findings have important implications for the conservation biogeography of edaphic island plant specialists. Clonal species may be susceptible to local extinction should insularity or soil conditions vary, for example, due to abrupt changes in the geographical setting (e.g. habitat loss) or local environmental factors (e.g. N‐deposition). Non‐clonal species may instead face environmental changes differently; some will go extinct, whereas others will survive, depending on the prevailing abiotic pressures. This seems to challenge previous views that predicted clonal species to be the winners and non‐clonal species the losers against local extinction.

Aim: Trait‐based approaches are being used increasingly in island biogeography, providing key insights into the eco‐evolutionary dynamics of insular systems. However, the determinants of persistence of plant species after they have arrived and established on an island remain largely unexplored. Here, we used three edaphic island systems (i.e., habitat patches distinguished from the landscape matrix by distinct soil conditions and specialized vegetation) to examine relationships between persistence strategies (those associated with clonality, bud bank, seed mass and life‐form) and insularity. We hypothesized that insularity promotes and selects strategies to persist locally, such that species occurring on small and/or isolated edaphic islands show trait values indicative of enhanced persistence and lower functional diversity.Location: Three European systems of edaphic islands in the Western Carpathians, Moravia and the Cantabrian Range.Time period: Present.Major taxa studied: Vascular plants.Methods: For each system, we used linear models to explore persistence‐related plant trait patterns (mean trait values and functional diversity) in relationship to three insularity metrics (island size, isolation and target effect). We focused on patterns of edaphic island specialists because their presence is confined to the islands.Results: We found that insularity metrics largely explained the variation of the mean value and diversity of persistence‐related traits of edaphic island plant specialists. Specifically, insularity was positively related to traits supporting local persistence (e.g., more extensive lateral spread) and to a reduced variability in persistence traits. More insular systems showed stronger and more numerous trait–insularity links.Main conclusions: Insularity can affect plant species diversity, form and function in edaphic island systems, such as selecting for enhanced and less diverse persistence strategies. Plant species occurring in insular systems might therefore avoid or delay local extinction by promoting adaptive strategies to persist in situ.

Aim: The spectral variability hypothesis (SVH) suggests a link between spectral variation and plant biodiversity. The underlying assumptions are that higher spectral variation in canopy reflectance (depending on scale) is caused by either (1) variation in habitats or linked vegetation types or plant communities with their specific optical community traits or (2) variation in the species themselves and their specific optical traits.Methods: The SVH was examined in several empirical remote‐sensing case studies, which often report some correlation between spectral variation and biodiversity‐related variables (mostly plant species counts); however, the strength of the observed correlations varies between studies. In contrast, studies focussing on understanding the causal relationship between (plant) species counts and spectral variation remain scarce. Here, we discuss these causal relationships and support our perspectives through simulations and experimental data.Results: We reveal that in many situations the spectral variation caused by species or functional traits is subtle in comparison to other factors such as seasonality and physiological status. Moreover, the degree of contrast in reflectance has little to do with the number but rather with the identity of the species or communities involved. Hence, spectral variability should not be expressed based on contrast but rather based on metrics expressing manifoldness. While we describe cases where a certain link between spectral variation and plant species diversity can be expected, we believe that as a scientific hypothesis (which suggests a general validity of this assumed relationship) the SVH is flawed and requires refinement.Conclusions: To this end we call for more research examining the drivers of spectral variation in vegetation canopies and their link to plant species diversity and biodiversity in general. Such research will allow critically assessing under which conditions spectral variation is a useful indicator for biodiversity monitoring and how it could be integrated into monitoring networks.

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long‐term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng‐Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time‐series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time‐series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine‐grained vegetation time‐series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of vascular plants in permanent plots. With 79 datasets from five continents and 7789 vegetation time-series monitored for at least six years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.

Aims: The link between spectral diversity and in‐situ plant biodiversity is one promising approach to using remote sensing for biodiversity assessment. Nevertheless, there is little evidence as to whether this link is maintained at fine scales, as well as to how it is influenced by vegetation's vertical complexity. Here we test, at the community level in grasslands, the link between diversity of the spectral signal (S_Div) and taxonomic diversity (T_Div), and the influence of vertical complexity.Methods: We used 196 1.5 m × 1.5 m experimental communities with different biodiversity levels. To measure vertical complexity, we quantified height diversity (H_Div) of the most abundant species in the community. T_Div was calculated using the Shannon index based on species cover. Canopy spectral information was gathered using an unmanned aerial vehicle (UAV) mounted with a multi‐spectral sensor providing spectral information via six 10‐nm bands covering the visible and near‐infrared region at a spatial resolution of 3 cm. We measured S_Div in a core area of 1 m ×1 m within the communities as mean Euclidean distance of all pixels in a feature space spanned between the two first components of a PCA calculated for the complete raster stack. We modelled S_Div through mixed‐effect linear models, using T_Div, H_Div, and their interaction as fixed‐effect predictors.Results: Contrary to our expectations, T_Div was negatively linked to S_Div. The diversity in plant height was positively related to S_Div. More importantly, diversity in plant height and T_Div had a significant negative interaction, meaning the more complex the vegetation was in terms of height, the more the S_Div–T_Div relationship became negative.Conclusions: Our results suggest that in order to exploit the S_Div–T_Div link for monitoring purposes, it needs to be contextualized. Moreover, the results highlight that communities’ functional characteristics (i.e. plant height) mediate such a link, calling for new insights into the relation between S_Div and functional diversity.