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Beta diversity quantifies spatial and/or temporal variation in species composition. It is comprised of two distinct components, species replacement and nestedness, which derive from opposing ecological processes. Using Scotland as a case study and a β-diversity partitioning framework, we investigate temporal replacement and nestedness patterns of coastal grassland species over a 34-yr time period. We aim to 1) understand the influence of two potentially pivotal processes (climate and land-use changes) on landscape-scale (5 × 5 km) temporal replacement and nestedness patterns, and 2) investigate whether patterns from one β-diversity component can mask observable patterns in the other. We summarised key aspects of climate driven macro-ecological variation as measures of variance, long-term trends, between-year similarity and extremes, for three important climatic predictors (minimum temperature, water-balance and growing degree-days). Shifts in landscape-scale heterogeneity, a proxy of land-use change, was summarised as a spatial multiple-site dissimilarity measure. Together, these climatic and spatial predictors were used in a multi-model inference framework to gauge the relative contribution of each on temporal replacement and nestedness patterns. Temporal β-diversity patterns were reasonably well explained by climate change but weakly explained by changes in landscape-scale heterogeneity. Climate was shown to have a greater influence on temporal nestedness than replacement patterns over our study period, linking nestedness patterns, as a result of imbalanced gains and losses, to climatic warming and extremes respectively. Important climatic predictors (i.e. growing degree-days) of temporal β-diversity were also identified, and contrasting patterns between the two β-diversity components revealed. Results suggest climate influences plant species recruitment and establishment processes of Scotland's coastal grasslands, and while species extinctions take time, they are likely to be facilitated by climatic perturbations. Our findings also highlight the importance of distinguishing between different components of β-diversity, disentangling contrasting patterns than can mask one another. [ABSTRACT FROM AUTHOR]

Species absent from a community but with the potential to establish (dark diversity) are an important, yet rarely considered component of habitat-specific species pools. Quantifying this component remains a challenge as dark diversity cannot be observed directly and must be estimated. Here, we empirically test whether species ecological requirements or species co-occurrences provide accurate estimates of dark diversity., We used two spatially nested independent datasets, one comprising 3033 samples of coastal grassland vegetation from 4 m2 and 200 m2 plots from Scotland, UK, and another comprising 780 samples of forest vegetation plots from 30 m2 and 500 m2 plots from Switzerland. Dark diversity for each of the smaller scaled plots was estimated through investigating the degree of (i) similarity in ecological requirements (measured as Ellenberg values); and (ii) co-occurrence likelihood. Estimates were validated using species from the larger spatial scales. Estimates were further validated using observations from all larger scale plots surrounding a focal assemblage within a 2 km (Scottish grassland) and 10 km (Swiss forest) radius., The co-occurrence method was shown to be more accurate resulting in far fewer negative mismatches (i.e. species observed but not predicted), as well as higher proportions of observed and predicted species, relative to the Ellenberg method. Of the species observed in the large-scale samples, 18% were estimated as part of the smaller scale dark diversity via the co-occurrence approach relative to 8% for the Ellenberg method for both the Scottish and Swiss data, respectively. These values increased to 67% & 60% and 32% & 35%, respectively, across all observations within a 2 km (Scottish grasslands) and 10 km (Swiss forests) radius., The study demonstrates that dark diversity for a community can be successfully estimated using readily available data, through exploring species co-occurrence patterns. This work substantiates that habitat-specific species pools can be accurately quantified and should prove valuable for understanding underlying community processes and improving our knowledge of the mechanisms governing species co-existence. [ABSTRACT FROM AUTHOR]