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About 19 % of the Italian territory is covered by protected areas (PAs), 5.1 % of which fall in IUCN categories Ia and II, which can be considered strictly protected areas (StPAs). The 2030 EU Biodiversity Strategy sets a target of 30 % coverage for PAs (of which 10 % should be StPAs). We assessed the area coverage of StPAs, for the territory of Italy, with respect to biogeographical regions, ecoregions, elevation range, habitats, and the distribution of species threatened with extinction according to the IUCN Red List (Vulnerable, VU; Endangered, EN; or Critically Endangered, CR). We found that most of the StPAs are located in the Mediterranean biogeographical region, followed by the Alpine and Continental regions, and that the spatial distribution of such protected areas is biased towards higher elevation. Moreover, we found that three of the fourteen terrestrial ecoregions of Italy are not protected at all by StPAs (i.e., Illyrian, Ligurian-Provencal, and Central-Adriatic), while the Po Plain and the Sicilia Sections are only marginally protected. Moreover, nine habitats are not covered by any StPAs including one priority habitat (Inland salt meadows). Finally, we found unprotected species among freshwater fish (21), amphibians (3 VU, 3 CR), reptiles (1 CR), birds (2 NE), mammals (1 VU), and plants (20 VU, 14 EN, 21 CR). Our findings suggest that the current amount and spatial distribution of StPAs of Italy are far from the targets of the EU Biodiversity Strategy and needs improvements. [ABSTRACT FROM AUTHOR]

Abstract Aims Current rates of biodiversity loss do not allow for inefficient monitoring. Optimized monitoring maximizes the ratio between information and sampling effort (i.e., time and costs). Sampling effort increases with the number and size of sampling units. We hypothesize that an optimal size and number of sampling units can be determined providing maximal information via minimal effort. We apply an approach that identifies the optimal size and number of sampling quadrats. The approach can be adapted to any study system. Here we focus on alpine grassland, a diverse but threatened ecosystem. Location Gran Paradiso National Park, Italy. Methods We sampled nine 20 m × 20 m-plots. Each plot consisted of 100 2 m × 2 m-subplots. Species richness and Shannon diversity were quantified for different sizes and quantities of subplots. We simulated larger subplot sizes by unifying adjacent 2 m × 2 m-subplots. Shannon's information entropy was used to quantify information content among richness and diversity values resulting from different subplot sizes and quantities. The optimal size and number of subplots is the lowest size and number of subplots returning maximal information. This optimal subplot size and number was determined by Mood's median test and segmented linear regression, respectively. Results The information content among richness values increased with subplot size, irrespective of the number of subplots. Therefore, the largest subplot size available is the optimal size for information about richness. Information content among diversity values increased with subplot size if 18 or less subplots were considered, and decreased if at least 27 subplots were sampled. The subplot quantity consequently determined whether the smallest or largest subplot size available is the optimal size, and whether the optimal size can be generalized across richness and diversity. Given a 2 m × 2 m size, we estimated an optimal quantity of 54. Given a size of 4 m × 4 m, we estimated an optimal number of 36. The optimal number of plots can be generalized across both indices because it barely differed between the indices given a fixed subplot size. Conclusions The information content among richness and diversity values depends on the sampling scale. Shannon's information entropy can be used to identify the optimal number and size of plots that return most information with least sampling effort. Our approach can be adapted to other study systems to create an efficient in-situ sampling design, which improves biodiversity monitoring and conservation under rapid environmental change. Graphical abstract Unlabelled Image Highlights • The optimal sampling design provides maximal information via minimal effort. • The optimal size/number of sampling quadrats cannot be generalized for alpine grassland. • Our approach is applicable to other study systems. [ABSTRACT FROM AUTHOR]

Highlights • Forest management strongly affected the presence of specialist species. • Accounting only for species richness may provide biased information for conservation. • Functional approach is promising for better-informed conservation planning. • Lists of conservation-relevant species are effective for understudied groups. • A multi-taxon framework is needed for guiding conservation action. Abstract Aim We investigated the consistency between richness and trait-based diversity metrics in capturing the effects of management-related habitat factors on biodiversity. The choice of biodiversity metrics can substantially affect the evaluation of conservation tools. However, the relative sensitivity of different metrics is not well investigated, especially in a multi-taxon framework. Location European beech forests in Denmark. Methods We studied 20 beech stands comprising four management types (from intensively managed to long unmanaged stands). We analyzed how management-related environmental variables were reflected in the measure of: (i) species richness, (ii) number of conservation-relevant species (red-listed species and old-growth forest indicators) and (iii) functional diversity targeting five organism groups with different habitat requirements, i.e. vascular plants, epiphytic lichens and bryophytes, saproxylic fungi and breeding birds. Results Plain species richness at stand level was generally misleading, as it did not capture changes in the number of conservation relevant species with changes in management-related environmental variables. The interpretation of functional responses was most informative for the better known vascular plants, while responses were more fragmented for the other organism groups. Overall, however, functional responses were consistent with a loss of specialization and progressive simplification of species assemblages from long-unmanaged to intensively managed stands. Conclusions Our findings suggest that the occurrence of conservation-relevant species is a sound and relevant metric for planning and evaluating conservation actions, especially for less studied organism groups (e.g., saproxylic fungi and epiphytes). The functional approach is promising, but presupposes the availability of databases of relevant traits. [ABSTRACT FROM AUTHOR]

Tropical forest ecosystems are among the most essential habitats on Earth for conserving biological diversity and short-term climate regulation. For this reason, they are key areas of conservation policies in the world. In this paper, we aim to investigate the dynamics of forest cover and their changes in primary productivity by empowering information on historical forest management and fieldwork research with remote sensing vegetation monitoring methods. The study area falls within the central portion of the Indian Western Ghats, a global biodiversity hotspot. In particular, part of the analysis was performed on the Kadamakal Reserve Forest and Pushpagiri Wildlife Sanctuary, which harbours an endemic low elevation dipterocarp evergreen forest. This area was managed by selective logging and became fully protected in 1984. We performed multiple time series macroscale analyses between 1999 and 2020 on the Indian Central Western Ghats region, using satellite products at 1 km spatial resolution from the VITO Copernicus Global Land Service on Dry Matter Productivity, Fraction of Absorbed Photosynthetically Active Radiation, and Normalised Difference Vegetation Index. We also performed a very-high spatial resolution Normalised Difference Vegetation Index differential analysis between 2021 and 2016 with Sentinel 2-L2A products to investigate forest dynamics within the reserve. At the 1 km spatial resolution has been found an increase in all three vegetation indices, by employing the LOESS statistical method for the smoothed transition autoregressive model of raster data medians of our datasets. The boxplot raster distribution analysis also highlighted a significant imbalance in dry matter productivity in the last decade (2010−2020) comparing the previous one (1999–2009). The second part of the analysis, at 10 m spatial resolution within the reserve forest, revealed a growth in the vegetation cover on the top of the Pushpagiri Mountain ridge and in a previously landslide area. The study found new erosion channels down to the upper plateau on the South-West side of the reserve due to an increment of the run-off processes during the monsoon period. This satellite analysis highlighted generalised positive vegetation trends in the Central Western Ghats, India, over the last twenty-two years, enhancing an improvement in the ecosystem functioning and carbon storage ecosystem service. Notably, through this work, we also developed a standardised and open-access framework to monitor the vegetation remotely (SVIT) during periods of forest inaccessibility for fieldwork sampling. [Display omitted] • Tropical forest ecosystems are hotspots for conserving biological diversity • Natural conservation policies focus on the tropical region's legacy • Remote sensing tools as proxies for monitoring the vegetation functioning • Open-source ecology as a tool for standard methods and information consistency • Highlights of conservation effectiveness efforts in Central Western Ghats, India [ABSTRACT FROM AUTHOR]

Lichens are symbiotic organisms sensitive to climate change and susceptible to a severe decline in diversity, especially in high elevation environments that are already threatened. In this study, we focused on water-energy relationships derived from climatic variables and phylogenetic diversity indices of terricolous lichen communities occurring on a representative Mediterranean mountain. We hypothesized that the variation of precipitation and temperature and their interaction along the altitudinal gradient will shape the phylogenetic diversity and structure of lichen communities. Our results reveal that dry and arid conditions lead to a strong loss in phylogenetic diversity with consequent impoverishment of high elevation lichen communities under a climate change scenario. The interaction between variables, reflecting water-energy relationships with phylogenetic and community diversity patterns, suggests that in a future climate change scenario, the novel climatic conditions may reduce the capability of the species to survive harsher conditions, and Mediterranean mountains may face a severe loss of genetic diversity in a climate change scenario. [ABSTRACT FROM AUTHOR]

The identification of shape and size of sampling units that maximises the number of plant species recorded in multiscale sampling designs has major implications in conservation planning and monitoring actions. In this paper we tested the effect of three sampling shapes (rectangles, squared, and randomly shaped sampling units) on the number of recorded species. We used a large dataset derived from the network of protected areas in the Siena Province, Italy. This dataset is composed of plant species occurrence data recorded from 604 plots (10 m × 10 m), each divided in a grid of 16 contiguous subplot units (2.5 m × 2.5 m). Moreover, we evaluated the effect of plot orientation along the main environmental gradient, to examine how the selection of plot orientation (when elongated plots are used) influences the number of species collected. In total, 1041 plant species were recorded from the study plots. A significantly higher species richness was recorded by the random arrangement of 4 subplots within each plot in comparison to the ‘rectangle’ and ‘square’ shapes. Although the rectangular shape captured a significant larger number of species than squared ones, plot orientation along the main environmental gradient did not show a systematic effect on the number of recorded species. We concluded that the choice of whether or not using elongated (rectangular) versus squared plots should dependent upon the objectives of the specific survey with squared plots being more suitable for assessing species composition of more homogeneous vegetation units and rectangular plots being more suited for recording more species in the pooled sample of a large area. [ABSTRACT FROM AUTHOR]

Despite a considerable effort of scientific community and a huge amount of literature, the capacity to assess and monitor biodiversity at coarser spatial scales in short time periods is still limited. Thus assessing indicator or surrogate information from existing data sets, such as forest inventories, is a challenge for biodiversity management and monitoring. We used two forest data sets (woody plants and all vascular plants) to test whether the diversity of woody plant species can be used as predictor of the diversity of all vascular plant species. Our study was performed in the forests of Liguria, Italy. In order to take into account several levels of community organisation, we calculated different measures of species diversity at different levels of sampling hierarchy for both data sets (alpha, beta and gamma diversity). We used ordinary linear regression to test the predictive power of the diversity measures obtained by the occurrences of woody plant species with respect to those obtained by all vascular plant species. Our results suggest that beta diversity and gamma diversity of woody species can be used to predict the beta diversity and the gamma diversity of all vascular plant species, at different levels of sampling hierarchy, while the alpha diversity of woody species cannot be used to predict the alpha diversity of all vascular plant species. These results point out the importance to consider measures based non only on species richness and to interpret the relation between species richness of woody plants and species richness of all vascular plants taking into account the scale dependence of this relations. Thus, our work demonstrates the feasibility of using data on woody plant species as recorded by forest inventories to predict the diversity patterns of all plant species in forest ecosystems. [ABSTRACT FROM AUTHOR]

The Convention on Biological Diversity's strategic plan lays out five goals: “(A) address the underlying causes of biodiversity loss by mainstreaming biodiversity across government and society; (B) reduce the direct pressures on biodiversity and promote sustainable use; (C) improve the status of biodiversity by safeguarding ecosystems, species and genetic diversity; (D) enhance the benefits to all from biodiversity and ecosystem services; (E) enhance implementation through participatory planning, knowledge management and capacity building.” To meet and inform on the progress towards these goals, a globally coordinated approach is needed for biodiversity monitoring that is linked to environmental data and covers all biogeographic regions. During a series of workshops and expert discussions, we identified nine requirements that we believe are necessary for developing and implementing such a global terrestrial species monitoring program. The program needs to design and implement an integrated information chain from monitoring to policy reporting, to create and implement minimal data standards and common monitoring protocols to be able to inform Essential Biodiversity Variables (EBVs), and to develop and optimize semantics and ontologies for data interoperability and modelling. In order to achieve this, the program needs to coordinate diverse but complementary local nodes and partnerships. In addition, capacities need to be built for technical tasks, and new monitoring technologies need to be integrated. Finally, a global monitoring program needs to facilitate and secure funding for the collection of long-term data and to detect and fill gaps in under-observed regions and taxa. The accomplishment of these nine requirements is essential in order to ensure data is comprehensive, to develop robust models, and to monitor biodiversity trends over large scales. A global terrestrial species monitoring program will enable researchers and policymakers to better understand the status and trends of biodiversity. [ABSTRACT FROM AUTHOR]

Since landscape attributes show different patterns at different spatial extents, it is fundamental to identify how the relation between landscape structure and plant species diversity at local scale varies with scale. Then, it is fundamental to assess the appropriate extent at which landscape factors affect plant species richness at the local scale. To investigate this relation, data on plant species richness of forest communities at plot scale were extracted from a large data set and landscape metrics were calculated around the same plots for a range of extents (250–3000 m). Then, multiple regression models and variance partitioning techniques were applied to assess the amount of variance explained by the landscape metrics on plant species richness for a range of extents. In general, we found that increasing extent of the surrounding landscape analyzed, improved the strength of relationship between the landscape metrics and the properties of plant communities at plot scale. The medium-large extent was most informative as it combined a decent total variance explained with high variance explained by the pure fractions of complexity, fragmentation and disturbance and the minimum of collinearity. In conclusion, we found that it is possible and beneficial to identify a specific extent, where the redundancy in the predictor variables is minimized and the explanatory power of the pure fractions (or single groups) maximized, when examining landscape structure effects on local plant species richness. [ABSTRACT FROM AUTHOR]

Abstract: Rarefaction curves represent a powerful method for comparing species richness among habitats on an equal-effort basis. Three assumptions are required to correctly perform rarefaction analysis: (i) data collection should be a representative sample of the community under study, (ii) individuals are randomly dispersed, and (iii) species are independently dispersed. However, the community structure is spatially organized, and these criteria cannot be guaranteed. Recently, Chiarucci et al. (2009) proposed a new type of rarefaction, named Spatially Constrained Rarefaction (SCR), which allows to include the autocorrelated structure of the samples in the construction of a rarefaction curve. Here we present an easy-to-use procedure to calculate Spatially Constrained Rarefaction curve in the R environment. [Copyright &y& Elsevier]

Abstract: Effective conservation of biodiversity in the face of increasing human impacts and global environmental changes requires accurate measurement of key trends and alternative management actions at landscape scales. Past ecological conditions are certainly important key factors in determining the present species diversity patterns and the inclusion of such factors (e.g. by historical cartographic data) can dramatically improve the predictive power of ecological models. In this paper we applied a retrogressive approach with the aim of simulating secondary forest regrowth effects on plant species diversity using present field data and historic land-use maps. The field data from an extensive sample were here used to model the temporal species richness change among the forest areas in the last 60 years. In order to rebuild the past species pool matrix using present field data and historical land use map, we applied a nearest neighbour selection using spatial query. Species-based rarefaction curves were derived for the two dates (1954 and 2010); the two datasets have been interpolated using inverse distance weighted algorithm, obtaining two maps showing the distribution of plant species richness for the two dates. The results showed that the cessation of human pressure on semi-natural areas and the consequent forest recovery, resulted in a decrease of vascular plant as a woodland flora replaces the open habitats flora. This study also showed that secondary forest regrowth and its effect on plant species diversity may be revealed by a retrogressive analysis, which represent a valid support in case of high uncertainty or absence of historical data. [Copyright &y& Elsevier]

Abstract: This paper introduces the integration of additive partitioning with species—area relationships to island biogeography in order to address the question “How are the pteridophyte and spermatophyte native and endemic flora of different oceanic archipelagos partitioned across islands?”. Species richness data of all endemic species and all native species of pteridophytes and spermatophytes were obtained for the Azores, Canaries and Cape Verde in the Atlantic Ocean and Galápagos, Hawaii and Marquesas in the Pacific Ocean. Additive partitioning of species diversity was used to quantify how much of the total diversity of an oceanic archipelago flora (γ-diversity) is due to (i) the mean species richness of the flora of each island (α-diversity), (ii) the variability in species richness of the floras across islands (β Nestedness) and (iii) the complementarity in species composition of the floras of different islands (β Replacement). The analysis was separately performed for the native and endemic pteridophyte and spermatophyte floras. The diversity partitioning of the six archipelagos showed large differences in how the flora of each archipelago is partitioned among the α, β Nestedness and β Replacement components, for pteridophytes and spermatophytes and for all endemic species and all native species. The α-diversity was more important for all native species than for endemic species and more important for pteridophytes than for spermatophytes, with the Azores showing outstanding high values of α-diversity. The β Nestedness was higher for pteridophytes than for spermatophytes and higher for endemic species than for all native species in both pteridophytes and spermatophytes. The values of β Replacement suggested that: (i) the spermatophyte native flora is more differentiated across islands than the pteridophyte native flora and (ii) the pteridophyte endemic flora and, especially, the spermatophyte endemic flora are more differentiated across islands than the corresponding native flora. An outstanding value of β Replacement for endemic and all native spermatophytes was found in Hawaii, confirming the biogeographical island differentiation in this archipelago. [Copyright &y& Elsevier]

Assessing the effects of the spatial components on species diversity in a network of protected areas represents an important step for assessing its conservation “capacity”. A clear evaluation on how α-, β-, and γ-diversity are partitioned among and within spatial scales can help to drive manager decisions and provide method for monitoring species diversity. Moving from these concepts, a probabilistic sample of plant species composition was here applied for quantifying plant species diversity within the Sites of Community Importance (SCIs) of the Natura 2000 network in the Siena Province. All analyses were performed separately for all species and those species defined as “focal” (included in regional, national or continental “red” lists). The results indicated that species richness of the SCIs differed from one location to another one independently from the sampling efforts. Diversity partitioning indicated that most of the flora diversity within the network was given by larger-scale β-diversity, i.e. the differences in species composition among SCIs. β-diversity was then decomposed in two components: β Area (due to the differences in area among SCIs) and β Replacement (due to the compositional differences across SCIs). β Area was particularly important for all species, while β Replacement was the most important factor for focal species. The consequent implications for monitoring and nature conservation strategies are discussed. [Copyright &y& Elsevier]

In the present paper, a test of the spectral variation hypothesis (SVH) was performed using multispectral high resolution satellite data. The SVH was tested by comparing the relationship between the spectral heterogeneity and species richness in plots of different size (100–10000 m2) in a complex wetland ecosystem, the “Montepulciano Lake”, Central Italy. The nature reserve of the Montepulciano Lake is centered on a 100 ha shallow lake surrounded on three sides by a Phragmites australis and Carex sp. pl. marsh of about 280 ha. The monitoring program for the reserve vegetation started in 2002 and is based on the analysis of 1, 100 m2 and 1 ha (10000 m2) plots, organized in such a manner that four of the smaller size plots are nested, following a random design, within a larger one. Data on species composition and community structure were collected in the plots and stored in a GIS-linked archive. A multispectral Quickbird satellite image (3 m spatial resolution) acquired of the wetland and lake ecosystem during the same period was radiometrically and geometrically corrected. We performed an analysis to examine the use of spectral heterogeneity using the four visible and infrared wavebands of the satellite image to predict species richness at the different spatial scales. The spectral heterogeneity was found to explain about 20% of the variance of species richness at the 100 m2 scale and about 50% at the 1 ha scale. It was concluded that multispectral high resolution satellite data can contribute to the biodiversity assessment of complex wetland ecosystems. [Copyright &y& Elsevier]

A desirable property of a diversity index is the so-called sum property. For a diversity index that possesses the sum property, such as species richness N, Shannon’s entropy H or Simpson’s index 1/D, the community diversity is decomposable into species-level patterns and the sum of single species diversities gives the pooled diversity of the species collection. In this paper, parametric diversity of type α is used to quantify how fertilizer applied to soil affects the relative contribution of species endemic or preferential to serpentine soils within a garigue plant community in Tuscany (Italy). Soil fertilizer significantly improved the biomass production of the original species pool without any significant colonization by alien species. However, the major biomass increments were experienced by species that are not exclusive to serpentine soils. In this view, the reduced abundance of species endemic or preferential to serpentine soils can be interpreted as a loss of ‘ecological quality’ of the analyzed community. [Copyright &y& Elsevier]

Long-term intensive monitoring in Europe is presently proceeding in more than 800 plots, where a number of investigations are carried out according to allegedly standardized protocols. While the potential of the program cannot be denied, certain aspects that are binding for data analysis may be a source of problems for future evaluation of program results. Here it is argued that: (i) current biological response indicators adopted by the program will not permit air pollution effects to be distinguished from effects due to other stressors and/or natural variation; (ii) the sampling strategy adopted to select monitoring sites does not enable European scale estimates of the status of attributes of interest or their changes; and that (iii) the sampling tactic suggested at plot level is ambiguous and cannot provide representative, unbiased estimates at plot scale. This latter point implies consequences when plot–level data are used in models, correlative studies and/or to infer cause–effect relationships. [Copyright &y& Elsevier]

In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use of remote sensing approaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similar spectral signature. With the use of high resolution remote sensing data, on a local scale, these subspaces can be identified as separate spectral entities, the so called "spectral species". Our approach extends this concept over wide spatial extents and to a higher level of biological organization. We applied this method to MODIS imagery data across Europe. Obviously, in this case, a spectral species identified by MODIS is not associated to a single plant species in the field but rather to a species assemblage, habitat, or ecosystem. Based on such spectral information, we propose a straightforward method to derive α - (local relative abundance and richness of spectral species) and β -diversity (turnover of spectral species) maps over wide geographical areas. • In-situ data on biodiversity are challenging. • Remote sensing (RS) is a powerful tool for studying biodiversity. • Spectral species can be detected in the electromagnetic spectrum. • Spectral communities can be used to calculate ecosystem diversity. [ABSTRACT FROM AUTHOR]

This work provides an overview of the ecology of all bipartite cyanolichens of Italy, exploring the relationships between ecological factors and species traits. A matrix of 205 species and several ecological descriptors was subjected to multivariate analyses (classification and ordination). Six groups of species with similar ecology were delimited, arranged along a gradient of decreasing aridity and light intensity, from extreme dry habitats on sunny calcareous rocks to very humid and shaded habitats on tree bark. The relationships between ecological species groups and traits were assessed by Principal Component Analysis, carried out on a matrix of ecological species groups and percent occurrences of 11 morpho-biological traits in each group. Along the gradient from arid to humid environments, and from more primeval substrata (rocks, mineral soils) to more recent ones (organic soils, tree bark), morphologically simpler, sexually reproducing cyanolichens are gradually replaced by more complex, often asexual species, which suggests that the current ecology of cyanolichens may retain a phylogenetic signal, indicative of the evolutionary footprint in species adaptation processes. [ABSTRACT FROM AUTHOR]

Protected areas (PAs) are a strategic tool for biodiversity conservation, and conservation planning approaches are used to optimize PAs capacity to preserve specific target groups. Orchidaceae is one of the most threatened plant families, as most species are vulnerable to habitat changes because of their strong ecological specialization. Italy plays a key role in biogeography as a result of its geographical position and hosts one of the most diverse orchid floras in the Mediterranean Basin. The aim of this work is to depict the degree of protection granted to orchids by the current network of PAs across the entire Italian country, testing whether distributional and ecological features affect species' conservation representativeness, and identifying a priority list of species to be further protected. We compiled a dataset comprising 71,693 occurrence records, the spatial conservation representativeness was calculated as the percent of occurrences falling within the borders of PAs. Generalized Linear Models were run to assess differences in the spatial conservation representativeness among species according to the preferred habitat, endemicity, chorology, and protection by the Habitats Directive. We produced a list of species to be used for prioritizing conservation planning. Our findings show that emphasis is needed on adopting orchid species linked to primary or well mature habitats to select additional PAs with high conservation significance. Our findings reiterate the urgency of targeted conservation actions that can protect orchids and prevent their decline. [ABSTRACT FROM AUTHOR]

• Studies of taxonomic, functional and phylogenetic diversity in beech forest understories lack. • Elevation and stand maturity played a major role in shaping multifaceted plant diversity. • Different species-pool, thus biogeography, may influence diversity patterns. • Multifaceted approaches should be incorporated into biodiversity monitoring plans. Studies addressing multiple aspects of biodiversity simultaneously (i.e., multifaceted approaches) can quantify plant diversity-environment links comprehensively - this is because of the multidimensional nature of plant diversity. However, multifaceted studies are scant in forests. Here, we examined taxonomic, functional and phylogenetic diversity patterns in 19 beech forest understory plots in two areas belonging to a biodiversity monitoring plan in Tuscany, Italy. We performed linear mixed effect models to quantify the influence of elevation (proxy for macroclimate), aspect (affecting microclimate), and basal area (related to microclimate and stand maturity) on diversity facets of vascular plants. Elevation played a major role in shaping diversity: high-elevation plots were less rich in species and had a reduced functional diversity of storage organs that may promote cold-tolerance. Conversely, the diversity of flowering phenology increased with elevation, thus low-elevation vegetation converged functionally towards a common, short blooming period. This strategy may be advantageous for understory plants in the deciduous beech forests experiencing longer growing seasons, hence more extended canopy closure at lower elevations. Basal area negatively affected foliar and multiple traits functional diversity which may be associated with highly selective and competitive environment for light capture in closed canopy, mature stands. Slope aspect did not exert any significant effect on diversity facets, neither did interactions among predictors. Overall, these results confirm the usefulness of implementing multifaceted approaches to i) better understand the influence of environmental drivers on different aspects of plant diversity, and ii) inform the biodiversity monitoring plan that is in place in the study forests by systematically including functional diversity instead of taxonomic metrics only. [ABSTRACT FROM AUTHOR]

Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions. [ABSTRACT FROM AUTHOR]

Recently, methods for constructing Spatially Explicit Rarefaction (SER) curves have been introduced in the scientific literature to describe the relation between the recorded species richness and sampling effort and taking into account for the spatial autocorrelation in the data. Despite these methodological advances, the use of SERs has not become routine and ecologists continue to use rarefaction methods that are not spatially explicit. Using two study cases from Italian vegetation surveys, we demonstrate that classic rarefaction methods that do not account for spatial structure can produce inaccurate results. Furthermore, our goal in this paper is to demonstrate how SERs can overcome the problem of spatial autocorrelation in the analysis of plant or animal communities. Our analyses demonstrate that using a spatially-explicit method for constructing rarefaction curves can substantially alter estimates of relative species richness. For both analyzed data sets, we found that the rank ordering of standardized species richness estimates was reversed between the two methods. We strongly advise the use of Spatially Explicit Rarefaction methods when analyzing biodiversity: the inclusion of spatial autocorrelation into rarefaction analyses can substantially alter conclusions and change the way we might prioritize or manage nature reserves. [ABSTRACT FROM AUTHOR]

[Display omitted] • We develop an adaptive monitoring approach, to estimate the coverage of habitat types using a two-phase sampling scheme. • The adaptive monitoring approach demonstrated high reliability in a simulation study performed on the whole country of Italy. • The method is cost effective, adaptable across habitat types, and transferable to other countries or whole European Union. The quantitative assessment of habitat conservation status is a major task for European Union member states in compliance with Council Directive 92/43. One goal of the European 2030 Biodiversity Strategy is the effective management of habitats that show declining trends. While various approaches have been adopted for national assessments, there is no consensus on how to achieve common statistically sound estimates of the criteria indicated by the EU Directive for the evaluation of the status and trend of habitat types. Here, we present an adaptive monitoring approach based on a two-phase sampling scheme to estimate the coverage of EU terrestrial habitat types, which is one of the four criteria indicated by the Habitats Directive. We used 9 habitats distributed among different EU member states choosing Italy as a case study. The development of the methodological approach is described, and a simulation study was performed to check the precision of the coverage estimators accounting for the lack of sampled data (nonresponse treatment), subregions and sustainable sampling effort. We found that our two-phase sampling approach has the potential to increase precision in estimating the coverage of habitat types (approximated at 1 ha cell size) with respect to the precision achieved by simple random sampling without replacement, which is the simplest sampling approach. Adopting a small sampling fraction (⩽ 0.04 %) of the survey area, the relative standard errors ranged from 7 to 15 % for common habitats whose presence is strongly correlated with the habitat suitability scores furnished by an expert team. In the challenging context of a "mandated" monitoring type, our approach provides sound statistical estimates of habitat coverage with the possibility of applying a standardised and transferable sampling scheme that is easily repeatable over time. [ABSTRACT FROM AUTHOR]

While changing climatic conditions may directly impact species distribution ranges, indirect effects related to altered biotic interactions may exacerbate range shifts. This situation fully applies to epiphytic lichens that are sensitive to climatic factors and strongly depend on substrate occurrence and features for their dispersal and establishment. In this work, we modelled the climatic suitability across Italy under current and future climate of the forest species Lobaria pulmonaria , the lung lichen. Comparatively, we modelled the suitability of its main tree species in Italy, as well as that of the alien tree Robinia pseudoacacia , black locust, whose spread may cause the decline of many forest lichen species. Our results support the view that climate change may cause range shifts of epiphytes by altering the spatial pattern of their climatic suitability (direct effect) and simultaneously causing range shifts of their host-tree species (indirect effect). This phenomenon seems to be emphasized by the invasion of alien trees, as in the case of black locust, that may replace native host tree species. Results indicate that a reduction of the habitat suitability of the lung lichen across Italy should be expected in the face of climate change and that this is coupled with a loss of suitable substrate. This situation seems to be determined by two main processes that act simultaneously: 1) a partial reduction of the spatial overlap between the climatic niche of the lung lichen and that of its host tree species, and 2) the invasion of native woods by black locust. The case of lung lichen and black locust in Italy highlights that epiphytes are prone to both direct and indirect effects of climate change. The invasion of alien trees may have consequences that are still poorly evaluated for epiphytes. Unlabelled Image • Climate change may directly and indirectly impact species distribution ranges. • We tested direct and indirect effects of climate change on the epiphytic lung lichen. • We used species distribution modelling for the lung lichen and host tree species. • Range reduction of the lung lichen is coupled with a co-reduction of its host trees. • Lung lichen range reduction is exacerbated by the spread of the alien black locust. [ABSTRACT FROM AUTHOR]

• Species accumulation curves (SACs) can be used to summarize directional and non-directional beta diversity as a function of sampling effort. • Using SACs, multiple-site dissimilarity emerges as the result of a species turnover process, rather than as a static indicator. • For directional SACs, the method, further allows to summarize the spatial autocorrelation in species composition among plots along an a-priori defined spatial, temporal or environmental gradient. Beta diversity has long been used to summarize the amount of variation in species composition among a set of N sampling units. However, while classical beta diversity provides an estimate of multiple-site dissimilarity among all sampling units, it is not informative on the changes of multiple-site dissimilarity as a function of sampling effort. For gamma diversity, this pattern is usually represented as a species accumulation curve, which is the graph of the number of observed species when the number of plots varies from 1 to N. Here, we will show that species accumulation curves may also be used to summarize directional and non-directional beta diversity as a function of sampling effort. The behavior of the proposed measures of beta diversity is illustrated with one worked example on plant species in Mediterranean coastal vegetation. We believe this approach to the measurement of beta diversity provides a relevant contribution to summarize multiple-site dissimilarity as the result of a species turnover process, rather than as a static indicator. For directional species accumulation curves, the method, for which we provide a custom R function, further allows summarizing the spatial autocorrelation in species composition among plots along an a-priori defined spatial, temporal or environmental gradient. [ABSTRACT FROM AUTHOR]

There is growing awareness that protected areas (PA) may not suffice to deliver all the targets set by international conventions and guarantee the conservation of biodiversity and ecosystem services in anthropogenic landscapes. However, landscapes such as sacred natural sites (SNS), which are managed with clear benefits for people and nature although not having conservation as their primary purpose, can help deliver those goals. While a number of studies have demonstrated SNS' values for biodiversity and ecosystem services, the fundamental question of whether and how SNS may complement PA at a national scale has never been addressed. Here, we assembled a nationwide inventory of 2332 SNS in Italy and compared their spatial distribution and landscape features with those of PA. We showed that there is scarce overlap between SNS and PA and that different factors drive the density of the two networks. SNS are more frequently associated with cultural landscapes at low and medium elevations and in extensively agricultural and peri-urban settings. PA, in contrast, are mainly found in more natural environments, at higher elevations, and farther from human settlements. These results indicate that the two networks largely complement each other and have different benefits for people and biodiversity. Land planning approaches should aim to valorize this complementarity. Instead of simply including SNS into PA, SNS could obtain a legal status through other emerging policy frameworks, such as the recognition of "other effective area-based conservation measures". • We tested whether sacred natural sites in Italy complement PAs at a national scale. • Only 18% ca. of the SNS network is included in PAs. • SNS are found in traditional landscapes and at low-medium elevations more than PAs. • SNS are important for protecting traditional landscapes and peri-urban areas. • New protection schemes may be appropriate for SNS with functioning governance. [ABSTRACT FROM AUTHOR]