Integrative models explain the relationships between species richness and productivity in plant communities

The relationship between plant productivity and species richness is one of the most debated and important issues in ecology. Ecologists have found numerous forms of this relationship and its underlying processes. However, theories and proposed drivers have been insufficient to completely explain the observed variation in the forms of this relationship. Here, we developed and validated integration models capable of combining twenty positive or negative processes affecting the relationship. The integration models generated the classic humped, asymptotic, positive, negative and irregular forms and other intermediate forms of the relationship between plant richness and productivity. These forms were linked to one another and varied according to which was considered the dependent variable. The total strengths of the different positive and negative processes are the determinants of the forms of the relationship. Positive processes, such as resource availability and species pool effects, can offset the negative effects of disturbance and competition and change the relationship. This combination method clarifies the reasons for the diverse forms of the relationship and deepens our understanding of the interactions among processes

An interspecific variation in rhizosphere effects on soil anti-erodibility

Soil erosion due to underground leakage is a major factor causing land degradation in karst regions. Rhizosphere effects (REs) on soil anti-erodibility (SAE) can alleviate this type of soil erosion by improving soil physical processes such as aggregate stability. However, the magnitudes and causes of interspecific variation in REs on SAE remain unclear. We tested the rhizosphere SAE indices of 42 key woody species distributed worldwide. Biologically active matter (BAM) and analogs of antibiotics (AOAs) that affect the SAE in rhizosphere soils were tested by gas chromatography-mass spectrometry (GC-MS). We then used principal component analysis (PCA) and redundancy analysis (RA) to establish a spectrum of interspecific variability in the REs for the first time. The spectrum shows a gradient of change among species. Eleven species exerted negative REs on the SAE, while the remaining species showed positive effects along the spectrum. The species with large positive effects were mostly deciduous, which have high contents of both BAM and total organic matter and low contents of AOAs in their rhizosphere soil; compared with the other species tested, these species also have more leaves and roots and are better adapted to barren soils. The botanical characteristics of species with negative REs on the SAE differed from those with large positive effects. The contents of BAM in the rhizosphere accounted for 16\u201323% of the total variation in REs on the SAE. This study quantified interspecific variation in REs and identified root exudates with negative REs

There is room for everyone: Invasion credit cannot be inferred from the species–area relationship in fragmented forests

Questions: Land use change, habitat fragmentation and biological invasion represent major drivers of global change that strongly interact to alter ecosystems. Following the breaking apart of forests into smaller fragments or the afforestation of former agricultural lands, biodiversity experiences drastic changes due to species loss and turnover over time. This leads to two important outcomes, namely extinction debt and invasion (colonization) credit, which both reflect the inertia of the system's response to environmental changes. Our study investigated the following questions: Is it possible to infer invasion credit from species–area relationship (SAR) residuals both for native and alien plants? Is there any trend linked with the degree of habitat fragmentation through time?. Location: Somme, Oise and Aisne departments, northern France. Methods: We analyzed the pattern of SARs' residuals for native and alien vascular plant species separately across nine sets of forest fragments that differ by the landscape matrix they are embedded in (i.e., open field, bocage, forest), while considering plant richness, area and age of the 355 forest patches. Results: The relationship between alien and native SARs’ residuals is positive across all landscapes, suggesting a lack of invasion credit. Instead, these results support the “rich get richer” hypothesis, that is a high environmental heterogeneity allows colonization by new species, be they native or alien. Interestingly, the relationship between alien and native residuals depends upon fragment age (i.e., time since patch creation) in the most intensively managed landscapes (i.e., open fields). In the latter, recent forest patches are more prone to alien invasion, as a likely consequence of increased alien propagule pressure (i.e., more sources and vectors for alien plants), increased forest invasibility (i.e., disturbance-induced environmental heterogeneity), and decreased matrix permeability (i.e., natives are more dispersal-limited than aliens). Conclusions: Our study provides new insights into alien species ecology, by showing that (i) it is not possible to infer “invasion credit” from the SAR's residuals; (ii) the invasion rate by alien species in forest fragments increases with their native species richness, and (iii) this relationship depends upon patch age in intensively managed landscapes

Optimizing sampling effort and information content of biodiversity surveys: a case study of alpine grassland

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 7 20 m-plots. Each plot consisted of 100 2 m 7 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 7 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 7 2 m size, we estimated an optimal quantity of 54. Given a size of 4 m 7 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

Characterizing historical transformation trajectories of the forest landscape in Rome's metropolitan area (Italy) for effective planning of sustainability goals

With the aim at developing a landscape dynamics framework for environmental planning and management and testing the effectiveness of protected areas in achieving the 2030 Agenda of the United Nations sustainability goals, we characterized the historical transformation trajectories of forest area changes from 1936 to 2010 in the Metropolitan City of Rome Capital (Italy). Remote sensing-based products coupled with landscape pattern metrics and fragmentation analysis have been implemented, comparing different historical forest maps. The results show a remarkable forest area gain – from 17.6% to 25.5% – thanks to 68,299 ha of recently established forest. Statistical descriptors showed that the highest relative gain occurred in mountain zones, confirming a wide European forest recovery pattern in marginal areas from past deforestation and overexploitation. Deforestation mainly occurred in the flat and hilly areas where almost 26,000 ha of forests were lost since 1936. In summary, two main forest landscape dynamics were reconstructed: (I) the increase of forest cover fragmentation in the lowland areas; and (II) the rise in the forest area in the interior sectors of the mountain landscape, mainly within protected areas. Restoring the forest ecosystem's bioecological integrity has been highlighted as an urgent action for biodiversity conservation and carbon mitigation. In lowland areas, the study revealed the urgent need to establish new protected areas and rewilding spaces as landscape metrics are relatively below the sustainability targets for healthy forest ecosystems. The proposed framework can be used for testing the effectiveness of environmental planning and management in other forest landscapes to achieve the Agenda 2030 goals

Data on alpine grassland diversity in Gran Paradiso National Park, Italy

The diversity of alpine grassland species and their functional traits constitute alpine ecosystem functioning and services that support human-wellbeing. However, alpine grassland diversity is threatened by land use and climate change. Field surveys and monitoring are necessary to understand and preserve such endangered ecosystems. Here we describe data on abundances (percentage cover) of 247 alpine plant species (including mosses and lichens) inside nine 20 m by 20 m plots that were subdivided into 2 m by 2 m subplots. The nine plots are located in Gran Paradiso National Park, Italy. They cover three distinct alpine vegetation subtypes (\u2018pure\u2019 natural grassland, sparsely vegetated \u2018rocky\u2019 grassland, and wetland) in each of three valleys (Bardoney, Colle de Nivolet and Levionaz) between 2200 and 2700 m a.s.l., i.e. above the treeline. The vegetation survey was conducted in 2015 at the peak of vegetation development during August. The dataset is provided as supplementary material and associated with the research article \u201cOptimizing sampling effort and information content of biodiversity surveys: a case study of alpine grassland\u201d [1]. See [1] for data interpretation

Biogeography of orchids and their pollination syndromes in small Mediterranean islands

Aims Despite the research on orchid in insular conditions, few studies are focused on the spatial distribution of their reproductive syndromes across complex insular systems. By using island species-area relationships (ISAR), we explore orchid biogeography in the Central Western-Mediterranean islands. In this study, we aim to investigate variation in ISARs using orchid pollination mechanisms as proxies to establish permanent populations explaining how the c and z parameters of ISARs vary among island types and pollination strategies and defining the most influential factors in shaping orchids' distribution.LocationMediterranean Basin.TaxonOrchidaceae. MethodsChecklist of native orchids was obtained for 112 islands of Central-Western Mediterranean Basin. The Arrhenius power function (S=c center dot Az$$S=c\cdotp {A}z$$) was used to fit ISARs for the total number of orchids as well as for functional groups defined by the pollination strategies, across different island types. We used GLM to investigate the relation between pollination syndromes with area and isolation as well as elevation, island origin, taxa richness of the source area and habitat diversity.ResultsWe found that ISARs differ between continental and volcanic islands depending on isolation. The z-value was found to be higher for more specialized strategies while the c-value increases from autogamy to allogamy, supporting the role of these two parameters in understanding distributional dynamics. Distance from the mainland is a negative predictor for all the strategies except when deception is decoupled; island area is a positive predictor only for allogamic, deceptive and food deceptive strategies, while habitat diversity is a positive predictor for allogamic, rewarding and deceptive strategies. Main Conclusions Pollination syndromes contribute in explaining the distribution of orchids in insular conditions. Furthermore, we identified differences in ISARs across pollination syndromes in which the intercept increases when the pollination shifts from a generalist to a more specialized one

Drivers of distance-decay in bryophyte assemblages at multiple spatial scales: Dispersal limitations or environmental control?

Questions: Despite the increasing scientific interest in distance decay of compositional similarity in ecology, the scale dependence of geographical versus environmental control on distance decay of biological communities has not been properly addressed so far. The present work highlights the relative importance of niche-based processes versus dispersal limitations on distance decay patterns of epilithic bryophyte assemblages at different spatial scales. Location: Serra de Sintra, central Portugal. Methods: We adopted a nested sampling design with 32 selected sampling sites in each of which two clusters, each with five rocks, were surveyed. Each cluster was characterized by a set of 15 macroscale variables, which were divided into environmental and anthropogenic. For each rock eight microscale variables were recorded. Partial Mantel tests were used to assess the relative importance of geographical and environmental distance on community dissimilarity for each grain size (site, cluster, rock). Quantile regressions were used to describe the decay patterns of community similarity with respect to geographical and environmental distances. Ordination analyses and variation partitioning techniques were applied to assess the pure and shared effects of measured variables on bryophyte community composition. Results: Environmental distance based upon macroscale predictors was significantly correlated to community similarity, while no significant correlation was found for ecological distance calculated for microscale predictors, except at the largest grain size. The decrease of community similarity with geographical and environmental distance was thus consistently strengthened with increasing sample grain. Compositional variation was best explained by anthropogenic variables. Conclusions: The relative importance of environmental versus geographical distance on compositional similarity in epilithic bryophyte communities varies with the spatial scale of the predictors and with the sample grain. The decrease of similarity with increasing distance is related to changes in habitat features, especially those driven by human disturbance, while it is weakly affected by variations in substrate features

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

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\u201317% 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

Exploring patterns of beta-diversity to test the consistency of biogeographical boundaries: A case study across forest plant communities of Italy

Aim: To date, despite their great potential biogeographical regionalization models have been mostly developed on descriptive and empirical bases. This paper aims at applying the beta-diversity framework on a statistically representative data set to analytically test the consistency of the biogeographical regionalization of Italian forests. Location: Italy. Taxon: Vascular plants. Methods: Forest plant communities were surveyed in 804 plots made in a statistically representative sample of forest communities made by 201 sites of Italian forests across the three biogeographical regions of the country: Alpine, Continental, and Mediterranean. We conducted an ordination analysis and an analysis of beta-diversity, decomposing it into its turnover and nestedness components. Results: Our results provide only partial support to the consistency of the biogeographical regionalization of Italy. While the differences in forest plant communities support the distinction between the Alpine and the other two regions, differences between Continental and Mediterranean regions had lower statistical support. Pairwise beta-diversity and its turnover component are higher between- than within-biogeographical regions. This suggests that different regional species pools contribute to assembly of local communities and that spatial distance between-regions has a stronger effect than that within-regions. Main conclusions: Our findings confirm a biogeographical structure of the species pools that is captured by the biogeographical regionalization. However, nonsignificant differences between the Mediterranean and Continental biogeographical regions suggest that this biogeographical regionalization is not consistent for forest plant communities. Our results demonstrate that an analytical evaluation of species composition differences among regions using beta-diversity analysis is a promising approach for testing the consistency of biogeographical regionalization models. This approach is recommended to provide support to the biogeographical regionalization used in some environmental conservation polices adopted by EU