Pteridophyte species richness in the central Himalaya is limited by cold climate extremes at high elevations and rainfall seasonality at low elevations

There is a consensus that climate factors strongly influence species richness along elevation gradients, but which factors are crucial and how they operate are still elusive. Here, we assess the relative importance of temperature-related versus precipitation-related variables and the relative importance of extreme climate versus climate seasonality in driving pteridophyte species richness. We used correlation and regression analyses to relate species richness of pteridophytes, and their two major groups (lycophytes, ferns), in fifty 100-m vertical bands to climatic factors representing different aspects of climatic conditions (general climate, stressful climate, and climate seasonality). Variation partitioning analysis was used to determine the relative importance of each group of climatic factors on species richness. Across the entire elevational gradient, species richness had a parabolic response to mean annual temperature (adjusted R2 = .87−.91), and a linear response to annual precipitation (adjusted R2 = .82). Mean annual temperature and annual precipitation in the second-order polynomial model together explained 96.3%−98.7% of the variation in species richness. The variation in species richness uniquely explained by minimum temperature of the coldest month was much greater than that uniquely explained by temperature seasonality, but the variation in species richness uniquely explained by precipitation during the driest month was much smaller than that uniquely explained by precipitation seasonality. Overall, extreme climate variables explained slightly more variation than did climate seasonality. Our study suggests that pteridophyte richness along the elevational gradient is largely driven by a combination of both temperature- and precipitation-related parameters, although precipitation-related variables play a slightly stronger role, and that extreme low temperature events (at high elevations) and seasonal precipitation variability (at low elevations) are the strongest determinants of pteridophyte species richness.publishedVersio

Restoring heathlands after afforestation on two islands in western Norway

The ongoing loss of red-listed coastal heathlands is a threat to biodiversity and cultural heritage legacies throughout the Atlantic coastal regions of Europe. It is possible to restore degraded and afforested heathlands, but restoration interventions are often labour-intensive and costly, and the outcome of specific restoration actions are not well documented. We assess the efficiency of restoring coastal heathlands through natural succession (i.e. ‘passive restoration') after removal of Sitka spruce Picea sitchensis (Bong.) Carr. plantations. The study was replicated on two neighbouring islands in a nature reserve in Western Norway. Low-intensity free-range sheep grazing was implemented as part of the reserve management plan. Furthermore, we tested the effect of leaving the clear-felled woody material as chips on site, this being a cost-efficient strategy on islands. Succession was monitored 1, 2, 4/5 and 8 years after clear-felling, and revegetation of vascular plants and bryophytes was compared to target heathland vegetation. Surprisingly, we found different successional trajectories on the two islands. Species composition on one island approached target heathland vegetation during succession, but not on the other. Wood chips reduced species richness and slowed the restoration process, but these negative effects were only short-term (<8 years). Differences in seed bank composition and soil conditions due to land use may explain the deviating successional trajectories on the two islands. We also found that management actions beyond clear-felling and introducing sheep grazing are necessary due to the rapid seed regeneration of the Sitka spruce.publishedVersio

Do sub-groups of butterflies display different elevational distribution patterns in the Eastern Himalaya, India?

Understanding the pattern of biodiversity along environmental gradients helps in identifying diversity hotspot areas that can be prioritized for conservation. While the elevational distribution of several taxa has been studied, responses of the sub-groups within a taxon to elevation and its associated factors are not properly understood. Here we study species richness and butterfly density along an elevation gradient in Sikkim, Eastern Himalaya, India and explore the underlying causes of the patterns. We sampled butterflies using a fixed-width point count method in 16 elevational bands (150–200 m intervals), between a range of 300 and 3300 m a.s.l. We categorized butterflies into various sub-groups based on family, range size, biogeographic affinity, and host-plant specialization. We recorded 3603 individuals and 253 species of butterflies after the completion of 1860 point counts. Overall, species richness in the majority of the sub-groups (except for Riodinidae and Palearctic species) declines with elevation, as does the density of almost all the sub-groups. From a selection of environmental factors, annual actual evapotranspiration has the strongest effect on the species richness pattern of butterflies as well as on the density of the overall butterfly community, especially the Lycaenidae family. The richness and density of butterfly groups display varied responses to the richness and density of trees and shrubs. The conducive climatic conditions and diverse habitats in the lower valleys of the Eastern Himalaya support a high diversity of butterflies (with majority of small range species) and thus warrants conservation attention.publishedVersio

A pan-Himalayan test of predictions on plant species richness based on primary production and water-energy dynamics

Spatial variation in plant species diversity is well-documented but an overarching first-principles theory for diversity variation is lacking. Chemical energy expressed as Net Primary Production (NPP) is related to a monotonic increase in species richness at a macroscale and supports one of the leading energy-productivity hypotheses, the More individuals Hypothesis. Alternatively, water-energy dynamics (WED) hypothesizes enhanced species richness when water is freely available and energy supply is optimal. This theoretical model emphasises the amount and duration of photosynthesis across the year and therefore we include the length of the growing season and its interaction with precipitation. This seasonal-WED model assumes that biotemperature and available water represent the photosynthetically active period for the plants and hence, is directly related to NPP, especially in temperate and alpine regions. This study aims to evaluate the above-mentioned theoretical models using interpolated elevational species richness of woody and herbaceous flowering plants of the entire Himalayan range based on data compiled from databases. Generalized linear models (GLM) and generalized linear mixed models (GLMM) were used to analyse species richness (elevational gamma diversity) in the six geopolitical sectors of the Himalaya. NPP, annual precipitation, potential evapotranspiration (derived by the Holdridge formula), and length of growing season were treated as the explanatory variables and the models were evaluated using the Akaike Information Criterion (AIC) and explained deviance. Both precipitation plus potential evapotranspiration (PET), and NPP explain plant species richness in the Himalaya. The seasonal-WED model explains the species richness trends of both plant life-forms in all sectors of the Himalayan range better than the NPP-model. Despite the linear precipitation term failing to precisely capture the amount of water available to plants, the seasonal-WED model, which is based on the thermodynamical transition between water phases, is reasonably good and can forecast peaks in species richness under different climate and primary production conditions.publishedVersio

Weighted average regression and environmental calibration as a tool for quantifying climate-driven changes in vegetation

Aims: Studies of the climatic responses of plant assemblages via vegetation-based environmental reconstructions by weighted averaging (WA) regression and calibration are a recent development in modern vegetation ecology. However, the performance of this technique for plot-based vegetation datasets has not been rigorously tested. We assess the estimation accuracy of the WA approach by comparing results, mainly the root mean square error of prediction (RMSEP) of WA regressions for six different vegetation datasets (total species, high-frequency species and low-frequency species as both abundance and incidence) each from two sites. Methods: Vegetation-inferred environment (plot elevation) calibrated over time is used to quantify the elevational shift in species assemblages. Accuracy of the calibrations is assessed by comparing the linear regression models developed for estimating elevational shifts. The datasets were also used for the backward predictions to check the robustness of the forward predictions. Important Findings: WA regression has a fairly high estimation accuracy, especially with species incidence datasets. However, estimation bias at the extremes of the environmental gradient is evident with all datasets. Out of eight sets (each set with a model for total species, low-frequency species and high-frequency species) of WA regression models, the lowest RMSEPs are produced in the four models based on the total species datasets and in three models based on the high-frequency species only. The inferred environment mirrored the estimation precision of the WA regressions, i.e. precise WA regression models produced more accurate calibrated environmental estimates, which, in turn, resulted in regression models with a higher adjusted r2 for estimating the elevational shift in the species assemblages. Reliable environmental estimates for plot-based datasets can be achieved by WA regression and calibration, although the edge effect may be evident if species turnover is high along an extensive environmental gradient. Species incidence (0/1) data may improve the estimation accuracy by minimizing any potential census and field estimation errors that are more likely to occur in species abundance datasets. Species data processing cannot guarantee the most reliable WA regression models. Instead, generally optimal estimations can be achieved by using all the species with a consistent taxonomy in the training and reconstruction datasets.acceptedVersio

High species turnover and low intraspecific trait variation in endemic and non-endemic plant species assemblages on an oceanic island

Questions Both species turnover and intraspecific trait variation can affect plant assemblage dynamics along environmental gradients. Here, we asked how community assemblage patterns in relation to species turnover and intraspecific variation differ between endemic and non-endemic species. We hypothesized that endemic species show lower intraspecific variation than non-endemic species because they tend to have high rates of in situ speciation, whereas non-endemic species are expected to have a larger gene pool and higher phenotypic plasticity. Location La Palma, Canary Islands. Methods We established 44 sampling sites along a directional gradient of precipitation, heat load, soil nitrogen, phosphorus and pH. Along this gradient, we estimated species abundances and measured three traits (plant height, leaf area and leaf thickness) on perennial endemic and non-endemic plant species. In total, we recorded traits for 1,223 plant individuals of 43 species. Subsequently, we calculated community-weighted mean traits to measure the relative contribution of species turnover, intraspecific variation and their covariation along the analysed gradient. Results The contribution of intraspecific variation to total variation was similar in endemic and non-endemic assemblages. For plant height, intraspecific variation explained roughly as much variation as species turnover. For leaf area and leaf thickness, intraspecific variation explained almost no variation. Species turnover effects mainly drove trait responses along the environmental gradient, but intraspecific variation was important for responses in leaf area to precipitation. Conclusions Despite their distinct evolutionary history, endemic and non-endemic plant assemblages show similar patterns in species turnover and intraspecific variation. Our results indicate that species turnover is the main component of trait variation in the underlying study system. However, intraspecific variation can increase individual species’ fitness in response to precipitation. Overall, our study challenges the theory that intraspecific trait variation is more important for the establishment of non-endemic species compared with endemic species.publishedVersio

Assessing the potential replacement of laurel forest by a novel ecosystem in the steep terrain of an Oceanic Island

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. T. Biological invasions are a major global threat to biodiversity and often affect ecosystem services negatively. They are particularly problematic on oceanic islands where there are many narrow-ranged endemic species, and the biota may be very susceptible to invasion. Quantifying and mapping invasion processes are important steps for management and control but are challenging with the limited resources typically available and particularly difficult to implement on oceanic islands with very steep terrain. Remote sensing may provide an excellent solution in circumstances where the invading species can be reliably detected from imagery. We here develop a method to map the distribution of the alien chestnut (Castanea sativa Mill.) on the island of La Palma (Canary Islands, Spain), using freely available satellite images. On La Palma, the chestnut invasion threatens the iconic laurel forest, which has survived since the Tertiary period in the favourable climatic conditions of mountainous islands in the trade wind zone. We detect chestnut presence by taking advantage of the distinctive phenology of this alien tree, which retains its deciduousness while the native vegetation is evergreen. Using both Landsat 8 and Sentinel-2 (parallel analyses), we obtained images in two seasons (chestnuts leafless and in-leaf, respectively) and performed image regression to detect pixels changing from leafless to in-leaf chestnuts. We then applied supervised classification using Random Forest to map the present-day occurrence of the chestnut. Finally, we performed species distribution modelling to map the habitat suitability for chestnut on La Palma, to estimate which areas are prone to further invasion. Our results indicate that chestnuts occupy 1.2% of the total area of natural ecosystems on La Palma, with a further 12–17% representing suitable habitat that is not yet occupied. This enables targeted control measures with potential to successfully manage the invasion, given the relatively long generation time of the chestnut. Our method also enables research on the spread of the species since the earliest Landsat images

High species turnover and low intraspecific trait variation in endemic and non-endemic plant species assemblages on an oceanic island

Questions: Both species turnover and intraspecific trait variation can affect plant assemblage dynamics along environmental gradients. Here, we asked how community assemblage patterns in relation to species turnover and intraspecific variation differ between endemic and non-endemic species. We hypothesized that endemic species show lower intraspecific variation than non-endemic species because they tend to have high rates of in situ speciation, whereas non-endemic species are expected to have a larger gene pool and higher phenotypic plasticity. Location: La Palma, Canary Islands. Methods: We established 44 sampling sites along a directional gradient of precipitation, heat load, soil nitrogen, phosphorus and pH. Along this gradient, we estimated species abundances and measured three traits (plant height, leaf area and leaf thickness) on perennial endemic and non-endemic plant species. In total, we recorded traits for 1,223 plant individuals of 43 species. Subsequently, we calculated community-weighted mean traits to measure the relative contribution of species turnover, intraspecific variation and their covariation along the analysed gradient. Results: The contribution of intraspecific variation to total variation was similar in endemic and non-endemic assemblages. For plant height, intraspecific variation explained roughly as much variation as species turnover. For leaf area and leaf thickness, intraspecific variation explained almost no variation. Species turnover effects mainly drove trait responses along the environmental gradient, but intraspecific variation was important for responses in leaf area to precipitation. Conclusions: Despite their distinct evolutionary history, endemic and non-endemic plant assemblages show similar patterns in species turnover and intraspecific variation. Our results indicate that species turnover is the main component of trait variation in the underlying study system. However, intraspecific variation can increase individual species’ fitness in response to precipitation. Overall, our study challenges the theory that intraspecific trait variation is more important for the establishment of non-endemic species compared with endemic species

Diversity of European habitat types is correlated with geography more than climate and human pressure

Habitat richness, that is, the diversity of ecosystem types, is a complex, spatially explicit aspect of biodiversity, which is affected by bioclimatic, geographic, and anthropogenic variables. The distribution of habitat types is a key component for understanding broad-scale biodiversity and for developing conservation strategies. We used data on the distribution of European Union (EU) habitats to answer the following questions: (i) how do bioclimatic, geographic, and anthropogenic variables affect habitat richness? (ii) Which of those factors is the most important? (iii) How do interactions among these variables influence habitat richness and which combinations produce the strongest interactions? The distribution maps of 222 terrestrial habitat types as defined by the Natura 2000 network were used to calculate habitat richness for the 10 km × 10 km EU grid map. We then investigated how environmental variables affect habitat richness, using generalized linear models, generalized additive models, and boosted regression trees. The main factors associated with habitat richness were geographic variables, with negative relationships observed for both latitude and longitude, and a positive relationship for terrain ruggedness. Bioclimatic variables played a secondary role, with habitat richness increasing slightly with annual mean temperature and overall annual precipitation. We also found an interaction between anthropogenic variables, with the combination of increased landscape fragmentation and increased population density strongly decreasing habitat richness. This is the first attempt to disentangle spatial patterns of habitat richness at the continental scale, as a key tool for protecting biodiversity. The number of European habitats is related to geography more than climate and human pressure, reflecting a major component of biogeographical patterns similar to the drivers observed at the species level. The interaction between anthropogenic variables highlights the need for coordinated, continental-scale management plans for biodiversity conservation.Research contributing to this study was funded by the project “Development of a National Plan for Biodiversity Monitoring” (Italian National Institute for Environmental Protection and Research – ISPRA). BIOME Group was partially supported by the H2020 SHOWCASE (Grant agreement No 862480) and by the H2020 COST Action CA17134 ‘Optical synergies for spatiotemporal sensing of scalable ecophysiological traits (SENECO)’

Analysing the distribution of strictly protected areas toward the EU2030 target

Protecting global biodiversity is one of the most urgent tasks for the coming decades. Area-based conservation is a pillar for preserving ecosystems and species. Strictly protected areas specifically preserve biodiversity and ecosystem processes. The “EU Biodiversity Strategy for 2030” targets strict protection for 10% of land area. Here we performed the first analysis of strictly protected areas (as IUCN type Ia, Ib, and II) across Europe, by investigating their area coverage at the level of biogeographical regions, countries and elevation gradients. We show that, with few exceptions, the amount of strictly protected area is very limited and the spatial distribution of such protected areas is biased towards higher elevation sites, as in the case of other protected areas. Then, we suggest that potential areas should be identified to expand strictly protected areas with low economic and social costs including, for instance, areas with high biodiversity value, low population, and low productive land use. Finally, we propose that a coordinated effort and a strategic plan to achieve continental-scale conservation are fundamental, and at least half of this land under strict conservation (i.e. 5%) should be under the protection categories Ia and Ib