James Tsakalos

In open biomes, plants tend to allocate most of their biomass below‐ground into coarse organs, which constitute the perennial portion of their body (roots or stems). As a result, in these environments, height and age can be decoupled, forming independent dimensions. These functional traits can shape plant fitness because (1) plant height influences above‐ground space occupancy, light capture, photosynthetic capacity and associated biomass production as well as dispersal of reproductive propagules, (2) plant age indicates individual on‐spot persistence defining the timespan a plant occupies a given space where it acquires, uses and stores resources in different above‐ and below‐ground organs. However, the extent to which plant height and age are decoupled in open biomes and the degree to which they may affect other plant functional traits remains largely untested using quantitative data. Here, we aim to tackle this gap, focusing on eight species (from five families) specialized and restricted to temperate dry grasslands in Central Europe. We examined how plant height and age affect other functional traits related to carbon allocation, resource use and conservation and transport efficiency—alone or in interaction, at the interspecific and intraspecific level. Our findings indicate that plant height and age are decoupled across and within species. Yet, these traits affect other plant functional traits when their effect is taken separately and in interaction—with highly species‐specific patterns. The interacting effect of plant height and age is especially strong for traits related to resource use and transport efficiency (annual radial growth, vessel size). We also reveal a widespread lack of trait coordination at the intraspecific level. Synthesis . While confined to a few species of one habitat type, our study provides detailed insights into a widely assumed yet poorly tested idea. Our results tend to align with the grow fast–die young versus grow slow–live long functional spectrum while also showing how plant height and age can affect other plant functions differentially. This, together with highly species‐specific responses, cautions against overly broad generalizations.

Anthropogenic biodiversity decline threatens the functioning of ecosystems and the many benefits they provide to humanity1. As well as causing species losses in directly affected locations, human influence might also reduce biodiversity in relatively unmodified vegetation if far-reaching anthropogenic effects trigger local extinctions and hinder recolonization. Here we show that local plant diversity is globally negatively related to the level of anthropogenic activity in the surrounding region. Impoverishment of natural vegetation was evident only when we considered community completeness: the proportion of all suitable species in the region that are present at a site. To estimate community completeness, we compared the number of recorded species with the dark diversity—ecologically suitable species that are absent from a site but present in the surrounding region2. In the sampled regions with a minimal human footprint index, an average of 35% of suitable plant species were present locally, compared with less than 20% in highly affected regions. Besides having the potential to uncover overlooked threats to biodiversity, dark diversity also provides guidance for nature conservation. Species in the dark diversity remain regionally present, and their local populations might be restored through measures that improve connectivity between natural vegetation fragments and reduce threats to population persistence.

This study investigates the scale-dependent alpha and beta diversity patterns in the subalpine grasslands of the Central Balkan Mountains following decades of reduced grazing. We examined two distinct vegetation patches: pure grasslands (N-type) and grasslands mixed with dwarf shrubs (V-type), focusing on coarse-scale (among stands) and fine-scale (within stands) heterogeneity. Using micro-quadrat transects and dissimilarity analyses, we assessed the species composition variability and spatial complexity of the two vegetation patches. The results showed that the N-type exhibited higher coarse-scale beta diversity, attributed to fluctuating dominant grass proportions, and lower fine-scale diversity due to competitive exclusion. Conversely, V-type vegetation displayed lower coarse-scale but higher fine-scale diversity, reflecting the heterogeneous spatial matrix created by dwarf-shrub encroachment. Fine-scale spatial complexity, quantified by the compositional diversity of dominants, strongly correlated with species richness and diversity. Two main conclusions emerged: (a) Grazing decline-driven succession toward grass–dwarf shrub mixtures enhanced local diversity while reducing landscape heterogeneity. Conversely, regeneration toward typical dominant grasses diminished local diversity but increased landscape heterogeneity. (b) A balanced fine-scale spatial mixture of dominant species was found to reduce their individual negative impact on other species’ diversity. Effective high-mountain pasture management requires the consideration of scale and local plant co-existence.

Protected areas are supposed to mitigate the loss of diversity caused by human activities in forests. However, different management strategies applied across protected areas affect diversity in various ways. This study compares the taxonomic, functional, and phylogenetic diversity, and the species composition of understory plants, between sustainably managed forests and strictly protected forests. From temperate beech (Fagus sylvatica L.) forests within the Foreste Casentinesi National Park (Northern Apennine, Italy), we selected 28 quadrats in strictly protected and managed zones. In each quadrat, we recorded the cover abundance of vascular plant species and measured two functional traits (specific leaf area and clonal lateral spread) on the most abundant understory species. We used generalized linear models to test for differences in taxonomic (species richness and the percentage of forest specialist species), functional (functional richness for single and multiple traits), and phylogenetic diversity (mean pairwise distance) between protection zones. Lastly, we evaluated differences in species composition between protection zones using non-metric multidimensional scaling, supported by PERMANOVA and indicator species analyses. Species richness and phylogenetic diversity did not differ between strictly protected and managed zones. Strictly protected forests had a significantly higher percentage of forest specialist species and functional richness of clonal lateral spread than forests allowing sustainable logging. Species composition was significantly different between strictly protected and managed forests; the most important indicator species detected within managed zones were Sanicula europaea and Aremonia agrimonoides, while Veronica montana, Oxalis acetosella, and Salvia glutinosa were indicator species within strictly protected forests. The difference between strictly protected forests and forests managed with sustainable logging is reflected in the proportion of forest specialist species and the diversity of belowground space occupation and resource acquisition strategies. Instead, species richness and phylogenetic diversity do not discriminate between the two protection zones. We suggest incorporating specialist species, functional and compositional diversity metrics into the evaluation framework to guide future conservation and management practices.

An in-depth understanding of local plant community assembly is critical to direct conservation efforts to promising areas and increase the efficiency of management strategies. This, however, remains elusive due to the sheer complexity of ecological processes. The maximum entropy-based Community Assembly via Trait Selection (CATS) model was designed to quantify the relative contributions of trait-based filtering, dispersal mass effects, and stochastic processes on community assembly. As a maximum entropy model, it does so without introducing additional bias or assumptions. Despite its increasing use, questions regarding its robustness and potential limitations remain. Here, we compared model predictions using either local or database-derived trait values, across different levels of species richness and between different taxonomic levels. A total of 19 datasets and 790 plots were analysed, spanning multiple habitat types (n = 18) and biomes (n = 7). Results indicate trait value origin does indeed influence model outcomes, warranting caution in selecting the method for obtaining trait data. We hypothesise that, for example, intraspecific trait variation combined with trait-based filtering or stochastic processes causes local and database trait values to deviate, potentially even further exacerbated by imputing missing trait data. Furthermore, trait-related information obtained from the model decreased with increasing species richness. We further hypothesise this could signal that stochastic processes are more dominant within species-rich systems, for example, due to functional redundancy or the existence of multiple fitness strategies. This general pattern was conserved across biomes, although with varying strength, showing CATS’ robustness despite these challenges.

Long-term monitoring is pivotal for the collection of data capable of unravelling spatio-temporal changes in plant diversity. Here we present a dataset including plant presence and abundance data collected using a probabilistic sampling design in the “Montagna di Torricchio” Strict Nature Reserve, central Apennines, Italy. Five surveys were conducted in 35 plots during a period spanning 22 years (2002–2024). This dataset allows for the study of plant diversity changes over space and time across different habitat types by using statistical inference based on solid sampling theory.

Biodiversity is changing rapidly, and ecologists use various measures to monitor and conserve it, but not all are equally effective. In the European temperate forests, ecologists are tasked with assessing the impact of global changes on plant species richness; however, this fails at capturing vital information about plant interactions. Using a chronosequence of beech forest stands, spanning 600 years of growth, we demonstrate the application of a different measure of diversity compared to classical species richness in the understorey. This measure, called compositional diversity (CD), considers the number of species combinations and their relative frequency within a community. The response of both classical species richness and CD along with succession, corresponded with our expectations based on ecological theory’s U-shape prediction of diversity along the successional gradient. However, after 300 years, there was a significant decoupling between the two measures’ responses. While species richness remained low and constant across old-growth and primeval forests, CD peaked in primeval forests, implying that the same number of late-successional species generated more diverse assemblages. This new information emphasises the need to protect old-growth and primeval forests not only to conserve species richness but also to preserve their unique network of species co-occurrence patterns – a factor not well represented by the classical species richness measure.

In macroecology, shifting from coarse- to local-scale explanatory factors is crucial for understanding how global change impacts functional diversity (FD). Plants possess diverse traits allowing them to differentially respond across a spectrum of environmental conditions. We aim to assess how macro- to microclimate, stand-scale measured soil properties, forest structure, and management type, influence forest understorey FD at the macroecological scale.

Our study covers Italian forests, using thirteen predictors categorized into climate, soil, forest structure, and management. We analyzed five traits (i.e., specific leaf area, plant size, seed mass, belowground bud bank size, and clonal lateral spread) capturing independent functional dimensions to calculate the standardized effect size of functional diversity (SES-FD) for all traits (multi-trait) and for single traits. Multiple regression models were applied to assess the effect of predictors on SES-FD.

We revealed that climate, soil, and forest structure significantly drive SES-FD of specific leaf area, plant size, seed mass, and bud bank. Forest management had a limited effect. However, differences emerged between herbaceous and woody growth forms of the understorey layer, with herbaceous species mainly responding to climate and soil features, while woody species were mainly affected by forest structure.

Future warmer and more seasonal climate could reduce the diversity of resource economics, plant size, and persistence strategies of the forest understorey. Soil eutrophication and acidification may impact the diversity of regeneration strategies; canopy closure affects the diversity of above- and belowground traits, with a larger effect on woody species. Multifunctional approaches are vital to disentangle the effect of global changes on functional diversity since independent functional specialization axes are modulated by different drivers. (Display Omitted)

The Fynbos biome (at the continental biome level) is a member of the global warm-temperate Ethesial Zone (zonobiome S1). The dominating feature of the vegetation supported by this biome are species- and endemic-rich shrublands. The occurrence of bioclimatically and pedologically marginal coastal thickets as well as inland fire-shy Cape thickets is briefly discussed. The relationship between pockets of fire-shy afrotemperate forests (belonging to another zonobiome) and the fynbos shrublands are also analysed. The CB Fynbos is here divided into 19 regional biomes, of which most are intrazonal pedobiomes, and two are extrazonal; only four regional biomes (all characterised by renosterveld vegetation) are of true zonal nature. This chapter presents descriptions of all 19 regional biomes.

The biomes of the zonobiome E2 Tropical Seasonal Zone occupy the largest portion of the tropical and subtropical regions of the world. This zone is also the dominant zonobiome of the studied MBSA. Physiognomically, the biomes of this zone are represented by savanna grasslands and woodlands, as well as Tropical Dry Forests (TDF). In bioclimatic terms, these biomes are characterised by alternation of prolonged dry and wet periods. In the study region we recognise Mesic and Arid Savanna at the rank of global biome, each comprising 25 and 9 regional biomes, respectively. While the savanna units are functionally underpinned by the domination of highly productive C4 grasslands, the TDF is characterised by an overall lack of grassy (or shrubby) understorey beneath a (semi)closed canopy of trees of predominantly low stature. There are two regional biomes of TDF recognised within the study area, namely Southern African Dry Forest and Southern African Dry Thicket. This chapter presents descriptions of all regional biomes of the zonobiome E2.