Fragmentary Blue: Resolving the Rarity Paradox in Flower Colors

Blue is a favored color of many humans. While blue skies and oceans are a common visual experience, this color is less frequently observed in flowers. We first review how blue has been important in human culture, and thus how our perception of blue has likely influenced the way of scientifically evaluating signals produced in nature, including approaches as disparate as Goethe’s Farbenlehre, Linneaus’ plant taxonomy, and current studies of plant-pollinator networks. We discuss the fact that most animals, however, have different vision to humans; for example, bee pollinators have trichromatic vision based on UV-, Blue-, and Green-sensitive photoreceptors with innate preferences for predominantly short-wavelength reflecting colors, including what we perceive as blue. The subsequent evolution of blue flowers may be driven by increased competition for pollinators, both because of a harsher environment (as at high altitude) or from high diversity and density of flowering plants (as in nutrient-rich meadows). The adaptive value of blue flowers should also be reinforced by nutrient richness or other factors, abiotic and biotic, that may reduce extra costs of blue-pigments synthesis. We thus provide new perspectives emphasizing that, while humans view blue as a less frequently evolved color in nature, to understand signaling, it is essential to employ models of biologically relevant observers. By doing so, we conclude that short wavelength reflecting blue flowers are indeed frequent in nature when considering the color vision and preferences of bees.publishedVersio

Upscaling biodiversity: estimating the species–area relationship from small samples

The challenge of biodiversity upscaling, estimating the species richness of a large area from scattered local surveys within it, has attracted increasing interest in recent years, producing a wide range of competing approaches. Such methods, if successful, could have important applications to multi‐scale biodiversity estimation and monitoring. Here we test 19 techniques using a high quality plant data set: the GB Countryside Survey 1999, detailed surveys of a stratified random sample of British landscapes. In addition to the full data set, a set of geographical and statistical subsets was created, allowing each method to be tested on multiple data sets with different characteristics. The predictions of the models were tested against the “true” species–area relationship for British plants, derived from contemporaneously surveyed national atlas data. This represents a far more ambitious test than is usually employed, requiring 5–10 orders of magnitude in upscaling. The methods differed greatly in their performance; while there are 2,326 focal plant taxa recorded in the focal region, up‐scaled species richness estimates ranged from 62 to 11,593. Several models provided reasonably reliable results across the 16 test data sets: the Shen and He and the Ulrich and Ollik models provided the most robust estimates of total species richness, with the former generally providing estimates within 10% of the true value. The methods tested proved less accurate at estimating the shape of the species–area relationship (SAR) as a whole; the best single method was Hui's Occupancy Rank Curve approach, which erred on average by <20%. A hybrid method combining a total species richness estimate (from the Shen and He model) with a downscaling approach (the Šizling model) proved more accurate in predicting the SAR (mean relative error 15.5%) than any of the pure upscaling approaches tested. There remains substantial room for improvement in upscaling methods, but our results suggest that several existing methods have a high potential for practical application to estimating species richness at coarse spatial scales. The methods should greatly facilitate biodiversity estimation in poorly studied taxa and regions, and the monitoring of biodiversity change at multiple spatial scales

What Ecological Factors Shape Species-Area Curves in Neutral Models?

Understanding factors that shape biodiversity and species coexistence across scales is of utmost importance in ecology, both theoretically and for conservation policies. Species-area relationships (SARs), measuring how the number of observed species increases upon enlarging the sampled area, constitute a convenient tool for quantifying the spatial structure of biodiversity. While general features of species-area curves are quite universal across ecosystems, some quantitative aspects can change significantly. Several attempts have been made to link these variations to ecological forces. Within the framework of spatially explicit neutral models, here we scrutinize the effect of varying the local population size (i.e. the number of individuals per site) and the level of habitat saturation (allowing for empty sites). We conclude that species-area curves become shallower when the local population size increases, while habitat saturation, unless strongly violated, plays a marginal role. Our findings provide a plausible explanation of why SARs for microorganisms are flatter than those for larger organisms

Geographic changes in the Aegean Sea since the Last Glacial Maximum : Postulating biogeographic effects of sea-level rise on islands

In order to assess how the last sea level rise affected the Aegean archipelago, we quantified the magnitude andrate of geographic change for the Aegean islands during the last sea-level-rise episode (21 kyr BP–present)with a spatially explicit geophysical model. An island-specific Area-Distance-Change (ADC) typology was constructed,with higher ADC values representing a higher degree of change. The highest fragmentation rates ofthe Aegean archipelago occurred in tandem with the largest rates of sea-level-rise occurring between 17 kyrand 7 kyr ago. Sea-level rise resulted in an area loss for the Aegean archipelago of approximately 70%. Spatiotemporaldifferences in sea-level changes across the Aegean Sea and irregular bathymetry produced a variety of islandsurface-area loss responses, with area losses ranging from 20% to N90% per island. In addition, sea-levelrise led to increased island isolation, increasing distances of islands to continents to N200% for some islands.Wediscuss howrates of area contractions and distance increasesmay have affected biotas, their evolutionary historyand genetics. Five testable hypotheses are proposed to guide future research. We hypothesize that islandswith higher ADC-values will exhibit higher degrees of community hyper-saturation, more local extinctions, largergenetic bottlenecks, higher genetic diversity within species pools, more endemics and shared species on continentalfragments and higher z-values of the power-law species-area relationship. The developed typology andthe quantified geographic response to sea-level rise of continental islands, as in the Aegean Sea, present an idealresearch framework to test biogeographic and evolutionary hypotheses assessing the role of rates of area and distancechange affecting biota