Multiple, coordinated goals and holistic actions are critical

Summary Climate and topography are among the most fundamental drivers of plant diversity. Here, we assessed the importance of climate and topography in explaining diversity patterns of species richness, endemic richness and endemicity on the landscape scale of an oceanic island and evaluated the independent contribution of climatic and topographic variables to spatial diversity patterns. We constructed a presence/absence matrix of perennial endemic and native vascular plant species (including subspecies) in 890 plots on the environmentally very heterogeneous island of La Palma, Canary Islands. Species richness, endemic richness and endemicity were recorded, interpolated and related to climate (i.e. variables describing temperature, precipitation, variability and climatic rarity) and topography (i.e. topographic complexity, solar radiation, geologic age, slope and aspect). We used multimodel inference, spatial autoregressive models, variance partitioning and linear regression kriging as statistical methods. Species richness is best explained by both climatic and topographic variables. Topographic variables (esp. topographic complexity and solar radiation) explain endemic richness, and climatic variables (esp. elevation/temperature and rainfall seasonality) explain endemicity. Spatial patterns of species richness, endemic richness and endemicity were in part geographically decoupled from each other. Synthesis. We identified several topography‐dependent processes ranging from evolutionary processes (micro‐refugia, in situ speciation, pre‐adaptation to rupicolous conditions, dispersal limitations) to human‐induced influences (introduced herbivores, fire, land use) that possibly shape the endemic richness pattern of La Palma. In contrast, climate mainly drives endemicity, which is connected to ecological speciation and specialization to local conditions. We highlight the importance of incorporating climatic variability into future studies of plant species diversity and endemism. The spatial incongruence in hot spots of species richness, endemic richness and endemicity emphasizes the need for an integrated conservation approach acknowledging different diversity measures to protect the complete spectrum of diversity. High‐elevation islands such as La Palma are highly suitable to study drivers of diversity and endemism, as they offer environmental gradients of continental magnitude on the landscape scale of a single climatic mini‐continent and a large array of in situ‐speciated endemics.

Although the role that Pleistocene glacial cycles have played in shaping the present biota of oceanic islands world‐wide has long been recognized, their geographical, biogeographical and ecological implications have not yet been fully incorporated within existing biogeographical models. Here we summarize the different types of impacts that glacial cycles may have had on oceanic islands, including cyclic changes in climate, shifts in marine currents and wind regimes and, especially, cycles of sea level change. The latter have affected geographical parameters such as island area, isolation and elevation. They have also influenced the configurations of archipelagos via island fusion and fission, and cycles of seamount emergence and submergence. We hypothesize that these sea level cycles have had significant impacts on the biogeographical processes shaping oceanic island biotas, influencing the rates and patterns of immigration and extinction and hence species richness. Here we provide a first step toward the development of a glacial‐sensitive model of island biogeography, representing the tentative temporal evolution of those biogeographical parameters during the last glacial cycle. From this reasoning we attempt to derive predictions regarding the imprint of sea level cycles on genetic, demographic or biogeographical patterns within remote island biotas.

We discuss the usefulness of the concept of Potential Natural Vegetation (PNV), which describes the expected state of mature vegetation in the absence of human intervention. We argue that it is impossible to model PNV because of (i) the methodological problems associated to its definition and (ii) the issues related to the ecosystems dynamics.We conclude that the approach to characterizing PNV is unrealistic and provides scenarios with limited predictive power. In places with a long-term human history, interpretations of PNV need to be very cautious, and explicit acknowledgement made of the limitations inherent in available data