Connectivity Gradients Research Articles

The convergence and divergence of episodic and semantic functions across lateral parietal cortex.

Decades of research have highlighted the importance of lateral parietal cortex (LPC) across a myriad of cognitive domains. Yet, the underlying function of LPC remains unclear. Two domains that have emphasized LPC involvement are semantic memory and episodic memory retrieval. From each domain, sophisticated functional models have been proposed, as well as the more domain-general assumption that LPC is engaged by any form of internally directed cognition (episodic/semantic retrieval being examples). Here we used a combination of functional magnetic resonance imaging, functional connectivity, and diffusion tensor imaging white-matter connectivity to show that (i) ventral LPC (angular gyrus [AG]) was positively engaged during episodic retrieval but disengaged during semantic memory retrieval and (ii) activity negatively varied with task difficulty in the semantic task whereas episodic activation was independent of difficulty. In contrast, dorsal LPC (intraparietal sulcus) showed domain general activation that was positively correlated with task difficulty. Finally, (iii) a dorsal-ventral and anterior-posterior gradient of functional and structural connectivity was found across the AG (e.g. mid-AG connected with episodic retrieval). We propose a unifying model in which LPC as a whole might share a common underlying neurocomputation (multimodal buffering) with variations in the emergent cognitive functions across subregions arising from differences in the underlying connectivity.

Network traits predict ecological strategies in fungi

Colonization of terrestrial environments by filamentous fungi relies on their ability to form networks that can forage for and connect resource patches. Despite the importance of these networks, ecologists rarely consider network features as functional traits because their measurement and interpretation are conceptually and methodologically difficult. To address these challenges, we have developed a pipeline to translate images of fungal mycelia, from both micro- and macro-scales, to weighted network graphs that capture ecologically relevant fungal behaviour. We focus on four properties that we hypothesize determine how fungi forage for resources, specifically: connectivity; relative construction cost; transport efficiency; and robustness against attack by fungivores. Constrained ordination and Pareto front analysis of these traits revealed that foraging strategies can be distinguished predominantly along a gradient of connectivity for micro- and macro-scale mycelial networks that is reminiscent of the qualitative ‘phalanx’ and ‘guerilla’ descriptors previously proposed in the literature. At one extreme are species with many inter-connections that increase the paths for multidirectional transport and robustness to damage, but with a high construction cost; at the other extreme are species with an opposite phenotype. Thus, we propose this approach represents a significant advance in quantifying ecological strategies for fungi using network information.

Fragmentation of forest-steppe predicts functional community composition of wild bee and wasp communities

Increased habitat fragmentation in natural areas is one of the causes of declining insect diversity and biomass globally. Wild bees and wasps and their ecosystem functions are not exceptions of the trend. To stop this trend, we need to increase our understanding of interactions between functional traits and the environment for better informing conservation and restoration. Therefore, we studied how habitat fragmentation (i.e., connectivity, fragment size) and flower availability (abundance and species richness) affect functional traits of wild bees and wasps. Forest‐steppe is a complex ecosystem ranging from far East of Asia to Eastern Central Europe, consisting of a mosaic of woody and herbaceous vegetation patches. We selected 30 natural forest-steppe fragments along a connectivity gradient in the Hungarian Great Plain region. The size of the selected fragments ranged between 0.16 and 6.88 ha. We collected wild bees and wasps with yellow pan traps. We selected four functional traits: social habit, body size, feeding preference, and nesting location and investigated them in relation to habitat connectivity, patch size, flower abundance and richness. We used RLQ ordination to analyse the pollinators' functional community composition. We found that habitat connectivity supported larger, eusocial and ground nesting wild bees. Fragment size was closely related to larvae feeding preference in both studied groups by positively affecting oligolectic bees and carnivore wasps. Additionally, higher abundance and species richness of flowers maintained polygolectic bees and solitary, ground-nesting wasps. In our study, we described for the first time the relationship between the functional traits and habitat fragmentation of wild bee and wasp communities in a natural forest-steppe habitat. Our findings suggest that improved knowledge about the response of functional traits of wild bee and wasp communities to habitat fragmentation will allow a better understanding and prediction of subsequent effects on ecosystem functioning. We conclude that a combination of large, high-quality and well-connected patches maintains specialist wild bee and wasp communities. • Habitat fragmentation predicts functional trait changes of pollinators. • Diverse flowers maintained polygolectic bees and solitary, ground-nesting wasps. • Large fragments positively affected oligolectic bees and carnivore wasps. • Well-connected fragments supported large, eusocial, and ground-nesting bees.

Linking cerebellar functional gradients to transdiagnostic behavioral dimensions of psychopathology

High co-morbidity and substantial overlap across psychiatric disorders encourage a transition in psychiatry research from categorical to dimensional approaches that integrate neuroscience and psychopathology. Converging evidence suggests that the cerebellum is involved in a wide range of cognitive functions and mental disorders. An important question thus centers on the extent to which cerebellar function can be linked to transdiagnostic dimensions of psychopathology. To address this question, we used a multivariate data-driven statistical technique (partial least squares) to identify latent dimensions linking human cerebellar connectome as assessed by functional MRI to a large set of clinical, cognitive, and trait measures across 198 participants, including healthy controls (n = 92) as well as patients diagnosed with attention-deficit/hyperactivity disorder (n = 35), bipolar disorder (n = 36), and schizophrenia (n = 35). Macroscale spatial gradients of connectivity at voxel level were used to characterize cerebellar connectome properties, which provide a low-dimensional representation of cerebellar connectivity, i.e., a sensorimotor-supramodal hierarchical organization. This multivariate analysis revealed significant correlated patterns of cerebellar connectivity gradients and behavioral measures that could be represented into four latent dimensions: general psychopathology, impulsivity and mood, internalizing symptoms and executive dysfunction. Each dimension was associated with a unique spatial pattern of cerebellar connectivity gradients across all participants. Multiple control analyses and 10-fold cross-validation confirmed the robustness and generalizability of the yielded four dimensions. These findings highlight the relevance of cerebellar connectivity as a necessity for the study and classification of transdiagnostic dimensions of psychopathology and call on researcher to pay more attention to the role of cerebellum in the dimensions of psychopathology, not just within the cerebral cortex.

Reshaping Cortical Connectivity Gradient by Long-Term Cognitive Training During Development

Reshaping Cortical Connectivity Gradient by Long-Term Cognitive Training During Development

Resting-state functional heterogeneity of the right insula contributes to pain sensitivity

Previous studies have described the structure and function of the insular cortex in terms of spatially continuous gradients. Here we assess how spatial features of insular resting state functional organization correspond to individual pain sensitivity. From a previous multicenter study, we included 107 healthy participants, who underwent resting state functional MRI scans, T1-weighted scans and quantitative sensory testing on the left forearm. Thermal and mechanical pain thresholds were determined. Connectopic mapping, a technique using non-linear representations of functional organization was employed to describe functional connectivity gradients in both insulae. Partial coefficients of determination were calculated between trend surface model parameters summarizing spatial features of gradients, modal and modality-independent pain sensitivity. The dominant connectopy captured the previously reported posteroanterior shift in connectivity profiles. Spatial features of dominant connectopies in the right insula explained significant amounts of variance in thermal (R2 = 0.076; p < 0.001 and R2 = 0.031; p < 0.029) and composite pain sensitivity (R2 = 0.072; p < 0.002). The left insular gradient was not significantly associated with pain thresholds. Our results highlight the functional relevance of gradient-like insular organization in pain processing. Considering individual variations in insular connectopy might contribute to understanding neural mechanisms behind pain and improve objective brain-based characterization of individual pain sensitivity.

Magnetic Structure in Successively Erupting Active Regions: Comparison of Flare-Ribbons With Quasi-Separatrix Layers

This paper studies the magnetic topology of successively erupting active regions (ARs) 11,429 and 12,371. Employing vector magnetic field observations from Helioseismic and Magnetic Imager, the pre-eruptive magnetic structure is reconstructed by a model of non-linear force-free field (NLFFF). For all the five CMEs from these ARs, the pre-eruptive magnetic structure identifies an inverse-S sigmoid consistent with the coronal plasma tracers in EUV observations. In all the eruption cases, the quasi-separatrix layers (QSLs) of large Q values are continuously enclosing core field bipolar regions in which inverse-S shaped flare ribbons are observed. These QSLs essentially represent the large connectivity gradients between the domains of twisted core flux within the inner bipolar region and the surrounding potential like arcade. It is consistent with the observed field structure largely with the sheared arcade. The QSL maps in the chromosphere are compared with the flare-ribbons observed at the peak time of the flares. The flare ribbons are largely inverse-S shape morphology with their continuity of visibility is missing in the observations. For the CMEs in the AR 12371, the QSLs outline the flare ribbons as a combination of two inverse J-shape sections with their straight parts being separated. These QSLs are typical with the weakly twisted flux rope. Similarly, for the CMEs in the AR 11429, the QSLs are co-spatial with the flare ribbons both in the middle of the PIL and in the hook sections. In the frame work of standard model of eruptions, the observed flare ribbons are the characteristic of the pre-eruptive magnetic structure being sigmoid which is reproduced by the NLFFF model with a weakly twisted flux rope at the core.

Contribution of animal models toward understanding resting state functional connectivity

Functional connectivity, which reflects the spatial and temporal organization of intrinsic activity throughout the brain, is one of the most studied measures in human neuroimaging research. The noninvasive acquisition of resting state functional magnetic resonance imaging (rs-fMRI) allows the characterization of features designated as functional networks, functional connectivity gradients, and time-varying activity patterns that provide insight into the intrinsic functional organization of the brain and potential alterations related to brain dysfunction. Functional connectivity, hence, captures dimensions of the brain's activity that have enormous potential for both clinical and preclinical research. However, the mechanisms underlying functional connectivity have yet to be fully characterized, hindering interpretation of rs-fMRI studies. As in other branches of neuroscience, the identification of the neurophysiological processes that contribute to functional connectivity largely depends on research conducted on laboratory animals, which provide a platform where specific, multi-dimensional investigations that involve invasive measurements can be carried out. These highly controlled experiments facilitate the interpretation of the temporal correlations observed across the brain. Indeed, information obtained from animal experimentation to date is the basis for our current understanding of the underlying basis for functional brain connectivity. This review presents a compendium of some of the most critical advances in the field based on the efforts made by the animal neuroimaging community.

Spatiotemporal trajectories in resting-state FMRI revealed by convolutional variational autoencoder

Recent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.

Connectivity gradients on tractography data: Pipeline and example applications.

Gray matter connectivity can be described in terms of its topographical organization, but the differential role of white matter connections underlying that organization is often unknown. In this study, we propose a method for unveiling principles of organization of both gray and white matter based on white matter connectivity as assessed using diffusion magnetic ressonance imaging (MRI) tractography with spectral embedding gradient mapping. A key feature of the proposed approach is its capacity to project the individual connectivity gradients it reveals back onto its input data in the form of projection images, allowing one to assess the contributions of specific white matter tracts to the observed gradients. We demonstrate the ability of our proposed pipeline to identify connectivity gradients in prefrontal and occipital gray matter. Finally, leveraging the use of tractography, we demonstrate that it is possible to observe gradients within the white matter bundles themselves. Together, the proposed framework presents a generalized way to assess both the topographical organization of structural brain connectivity and the anatomical features driving it.

A tale of two gradients: differences between the left and right hemispheres predict semantic cognition

Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.

Spatial configuration and landscape context of wildflower areas determine their benefits to pollinator α- and β-diversity

Wildflower areas have become a staple tool within agro-environmental schemes (AES) to counteract pollinator declines. While their role in providing food resources to resident flower-visiting insects is unambiguous, the conservation effectiveness in a landscape context is less clear. Particularly, how multiple vs. single wildflower area utilization differs between simple and complex landscapes is understudied. We examined colonisation and community dynamics of wild bees and hoverflies in 33 newly established wildflower areas across a gradient of landscape complexity (amount of semi-natural habitat) and connectivity (presence of additional wildflower areas) for seven weeks during three consecutive years (one year during and two after establishment). We recorded more than 25% of the wild bee and hoverfly species of Hesse in an area of approx. 10 ha, substantiating the general benefit of wildflower areas to pollinators. While alpha-diversity increased with landscape complexity in isolated wildflower areas, the opposite pattern was observed for connected areas. The low alpha-diversity in complex landscapes indicated a dilution effect between connected sites. The inverse relationship between alpha and beta diversity among wildflower areas within landscapes suggests interspecific trade-offs between local resource conditions and landscape context. Accordingly, the establishment of multiple wildflower areas within AES is advisable to increase connectivity of suitable habitats in simple landscapes. Moreover, adjusting local conditions (plant diversity) to landscape context likely optimizes conservation effectiveness in modern agroecosystems.

Cortical patterning of morphometric similarity gradient reveals diverged hierarchical organization in sensory-motor cortices.

The topological organization of the cerebral cortex provides hierarchical axes, namely gradients, which reveal systematic variations of brain structure and function. However, the hierarchical organization of macroscopic brain morphology and how it constrains cortical function along the organizing axes remains unclear. We map the gradient of cortical morphometric similarity (MS) connectome, combining multiple features conceptualized as a "fingerprint" of an individual's brain. The principal MS gradient is anchored by motor and sensory cortices at two extreme ends, which are reliable and reproducible. Notably, divergences between motor and sensory hierarchies are consistent with the laminar histological thickness gradient but contrary to the canonical functional connectivity (FC) gradient. Moreover, the MS dissociates with FC gradients in the higher-order association cortices. The MS gradient recapitulates fundamental properties of cortical organization, from gene expression and cyto- and myeloarchitecture to evolutionary expansion. Collectively, our findings provide a heuristic hierarchical organization of cortical morphological neuromarkers.

Spatial Effects of Urban-Rural Ditch Connectivity Gradient Changes on Water Quality to Support Ditch Optimization and Management

Ditch networks play crucial roles in regulating water fluxes with their surroundings. The connectivity of ditches can have great impacts on nutrient migration and transformations. However, connectivity patterns related to ditch networks have rarely been studied, especially the relationships with water quality assessed through spatial analysis. This paper considered ditch connectivity and water quality indicators comprehensively, using spatial autocorrelation and geographically weighted regression (GWR) models, to analyze the impact of ditch connectivity on water quality from urban to rural gradients. The results suggested that water quality in rural areas and towns was better than in suburbs and transition zones, and the different areas exhibited variable spatial ditch connectivity. The Moran’s I index of the connectivity indicators showed the clustering state of spatial distribution, with ditch connectivity explaining 61.06% of changes in water quality. The circularity and network connectivity of the ditches had the most influence on water quality. However, the degree of influence varied with region. Circularity had the greatest impact on water quality in urban areas, and network connectivity had the greatest impact on water quality in township areas. Therefore, future water improvement projects, based on ditch optimization and management, need to consider the more related influencing factors and their spatial differences.

Habitat heterogeneity enables spatial and temporal coexistence of native and invasive macrophytes in shallow lake landscapes

AbstractMacrophyte invasive alien species (IAS) fitness is often hypothesised to be associated with beneficial environmental conditions (environmental matching) or species‐poor communities. However, positive correlations between macrophyte IAS abundance and native plant richness can also arise, due to habitat heterogeneity (defined here as variation in abiotic and native biotic conditions over space and time). We analysed survey and palaeoecological data for macrophytes in satellite lakes along the Upper Lough Erne (ULE) system (Northern Ireland, UK), covering a gradient of eutrophication and connectivity to partition how environmental conditions, macrophyte diversity and habitat heterogeneity explained the abundance of Elodea canadensis, a widely distributed non‐native macrophyte in Europe. E. canadensis abundance positively correlated with macrophyte richness at both the within‐ and between‐lake scales indicating coexistence of native and invasive species over time. E. canadensis was also more prolific in highly connected and macrophyte‐rich lakes, but sparser in the more eutrophic‐isolated ones. Partial boosted regression trees revealed that in eutrophic‐isolated lakes, E. canadensis abundances correlated with water clarity (negatively), plant diversity (positively), and plant cover (negatively) whereas in diverse‐connected lakes, beta diversity (both positively and negatively) related to most greatly E. canadensis abundance. Dense macrophyte cover and unfavourable environmental conditions thus appear to confer invasibility resistance and sufficient habitat heterogeneity to mask any single effect of native biodiversity or environmental matching in controlling E. canadensis abundance. Therefore, in shallow lake landscapes, habitat heterogeneity variously enables the coexistence of native macrophytes and E. canadensis, reducing the often‐described homogenisation effects of invasive macrophytes.

Spatial representation of in-stream sediment phosphorus release combining channel network approaches and in-situ experiments

Impairment of rivers by elevated phosphorus (P) concentration is an issue often studied at outlets of mesoscale catchments. Our objective was to evaluate within-catchment spatio-temporal processes along connected reaches to understand processes of internal P loading associated with sediment input, accumulations in channels and sediment-water column P exchange. Our overall hypothesis was that heterogeneous sediment residence within the channel of a 52 km2 mixed land cover catchment resulted in key zones for sediment-water P exchange. We evaluated the channel network through ground-survey, spatial data methods establishing connectivity and energy gradients. This gave a background to understand sampling of sediments and P release/uptake to the water column using 90 s in-situ resuspension isolating a portion of streambed over five sets of three-location transects in May (spring storms, recent active erosion) and September (summer low flow, longer sediment residence). Simple transect position models (top, mid, bottom) predicted increased sediment resuspension yields and P contents in lower settings. Sediment P release following resuspension were mean (and range) 0.5 (−0.8 to 1.8) and 0.5 (−2.5 to 3.6) mg soluble reactive P/m2 bed in May and September, respectively, strengthening generally down the transects but inconsistently. Relationships (log form) showed a steepening rise in fine sediments, P content, background and disturbance-released dissolved P, with specific stream power < 40 W/m2. In-situ methods showed sediments dominantly (12 cases May, 13 cases Sep) as P sources capable of influencing dissolved P concentrations and with potential explanation that heterogeneous locations of internal P loading influence the systems longer-term observed P trends. Combining channel network, stream power assessment and in-situ sorption studies improved the understanding of influential zones of sediment-water P exchange within this mesoscale catchment. Such methods have potential to inform P model development and management.

Structural Connectivity Gradients of the Temporal Lobe Serve as Multiscale Axes of Brain Organization and Cortical Evolution.

The temporal lobe is implicated in higher cognitive processes and is one of the regions that underwent substantial reorganization during primate evolution. Its functions are instantiated, in part, by the complex layout of its structural connections. Here, we identified low-dimensional representations of structural connectivity variations in human temporal cortex and explored their microstructural underpinnings and associations to macroscale function. We identified three eigenmodes which described gradients in structural connectivity. These gradients reflected inter-regional variations in cortical microstructure derived from quantitative magnetic resonance imaging and postmortem histology. Gradient-informed models accurately predicted macroscale measures of temporal lobe function. Furthermore, the identified gradients aligned closely with established measures of functional reconfiguration and areal expansion between macaques and humans, highlighting their potential role in shaping temporal lobe function throughout primate evolution. Findings were replicated in several datasets. Our results provide robust evidence for three axes of structural connectivity in human temporal cortex with consistent microstructural underpinnings and contributions to large-scale brain network function.

Fragment connectivity shapes bird communities through functional trait filtering in two types of grasslands

Habitat fragmentation is considered one of the most severe threatening factors for global biodiversity. Here we assessed, how local and landscape scale environmental variables, such as fragment size (small vs. large) and landscape configuration (measured as connectivity index) relates to bird community composition, species richness, abundance and functional diversity. We surveyed 60 grassland fragments in Hungary, belonging to two different threatened grassland types, namely forest-steppes and kurgans. Forest-steppes are natural mosaics of grasslands and forests at the contact zone between closed-canopy temperate forests and steppe grasslands. Kurgans are ancient burial mounds, found on the Eurasian steppe and forest steppe zone. These fragments were embedded in plantation forestry, respectively, agricultural matrix with gradients of size and connectivity. Both habitats are threatened by forestry and agricultural intensification, though these fragments may serve as important wildlife refuges. Our findings revealed that forest-steppe birds were more diverse and abundant in large and well-connected than in small isolated fragments. High connectivity affected ground nesting birds in small forest-steppe fragments positively. Birds inhabiting kurgan area showed higher trait similarity in well-connected than in isolated fragments. Bird abundance of kurgans associated with small home range size and ground feeding habit were higher in connected compared to isolated fragments. Highly isolated kurgans filtered for more specialised bird species but not for generalists. We provide conservation implications for enhancing grassland specialist bird communities, which consist of preservation of large, well-connected grassland fragments within production landscapes and through reconsideration of the currently used intensive forestry.

Gradients of connectivity as graph Fourier bases of brain activity.

The application of graph theory to model the complex structure and function of the brain has shed new light on its organization, prompting the emergence of network neuroscience. Despite the tremendous progress that has been achieved in this field, still relatively few methods exploit the topology of brain networks to analyze brain activity. Recent attempts in this direction have leveraged on the one hand graph spectral analysis (to decompose brain connectivity into eigenmodes or gradients) and the other graph signal processing (to decompose brain activity “coupled to” an underlying network in graph Fourier modes). These studies have used a variety of imaging techniques (e.g., fMRI, electroencephalography, diffusion-weighted and myelin-sensitive imaging) and connectivity estimators to model brain networks. Results are promising in terms of interpretability and functional relevance, but methodologies and terminology are variable. The goals of this paper are twofold. First, we summarize recent contributions related to connectivity gradients and graph signal processing, and attempt a clarification of the terminology and methods used in the field, while pointing out current methodological limitations. Second, we discuss the perspective that the functional relevance of connectivity gradients could be fruitfully exploited by considering them as graph Fourier bases of brain activity.

Woody species richness and turnover in expanding Mediterranean forests: a story of landscape legacies influenced by climatic aridity

The current expansion of forests in Europe is expected to be affected by transient colonization credits (i.e. species deficits compared to long-established forests), especially due to plant species with limited dispersal ability. We aimed to disentangle the role of forest connectivity and climatic aridity in the assembly of woody plant communities present in expanding Mediterranean forests by studying species with different types of dispersal. We used a space-for-time approach in recent (post 1980), middle-aged (1956–1980) and long-established forests (pre-1956) along an aridity and forest connectivity gradient in NE Spain. We recorded woody canopy and understory species and classified them as either vertebrate-, non-vertebrate- or human-dispersed species (i.e., crops). Species turnover between forests of different ages was limited to particular species and did not give rise to colonization credits determined by plant dispersal type. Connectivity and aridity drove understory richness in a similar way in forests of different ages. Within this general pattern, non-vertebrate-dispersed species were especially promoted by benign conditions. Sites with high forest connectivity had either the richest or the most impoverished understories given, respectively, low or high aridity. Thus, the rescue effect was modulated by aridity, which acted as a limiting factor. Mediterranean forest richness and composition are strongly dependent on climatic constraints and the ‘rescue effects’ (connectivity) originating in surrounding forest areas. These two factors shape the composition of expanding forests in different ways depending on the ability of species to disperse.