The effect of towns on plant phenology, i.e. advancement of spring development compared with a rural environment, via the urban heat island (UHI) phenomenon, has been shown for many towns in many countries. This work combines experimental and observational methodology to provide a better and deeper view of climatic habitat in an urban context with a view to understanding the relationship between plant development and urban climate on the intra-urban scale (by taking into account town structure). A dense network of 17 meteorological stations was set up in Rennes, France, enabling us to identify and quantify climatic changes associated with the UHI. Meanwhile, phenological observations were made during early spring (March and April) in 2005 on Platanus acerifolia and Prunus cerasus to study the relationship between climatic and phenological data. The results show that there is both a climatic gradient and a developmental gradient corresponding to the type of urbanisation in the town of Rennes. The town influences plant phenology by reducing the diurnal temperature range and by increasing the minimum temperature as one approaches the town centre. The influence of ground cover type (plants or buildings) on development is also shown. The developmental phases of preflowering and flowering are influenced to differing extents by climatic variables. The period during which climatic variables are effective before a given developmental phase varies considerably. The preflowering phases are best correlated with the mean of the minimum air temperature for the 15-day period before the observation, whereas flowering appears to be more dependent on the mean of the daily diurnal temperature range for the 8 days preceding the observation.

Aim Species–area relationships (SARs) are fundamental scaling laws in ecology although their shape is still disputed. At larger areas, power laws best represent SARs. Yet, it remains unclear whether SARs follow other shapes at finer spatial grains in continuous vegetation. We asked which function describes SARs best at small grains and explored how sampling methodology or the environment influence SAR shape. Location Palaearctic grasslands and other non‐forested habitats. Taxa Vascular plants, bryophytes and lichens. Methods We used the GrassPlot database, containing standardized vegetation‐plot data from vascular plants, bryophytes and lichens spanning a wide range of grassland types throughout the Palaearctic and including 2,057 nested‐plot series with at least seven grain sizes ranging from 1 cm2 to 1,024 m2. Using nonlinear regression, we assessed the appropriateness of different SAR functions (power, power quadratic, power breakpoint, logarithmic, Michaelis–Menten). Based on AICc, we tested whether the ranking of functions differed among taxonomic groups, methodological settings, biomes or vegetation types. Results The power function was the most suitable function across the studied taxonomic groups. The superiority of this function increased from lichens to bryophytes to vascular plants to all three taxonomic groups together. The sampling method was highly influential as rooted presence sampling decreased the performance of the power function. By contrast, biome and vegetation type had practically no influence on the superiority of the power law. Main conclusions We conclude that SARs of sessile organisms at smaller spatial grains are best approximated by a power function. This coincides with several other comprehensive studies of SARs at different grain sizes and for different taxa, thus supporting the general appropriateness of the power function for modelling species diversity over a wide range of grain sizes. The poor performance of the Michaelis–Menten function demonstrates that richness within plant communities generally does not approach any saturation, thus calling into question the concept of minimal area.

Rewilding is emerging as a promising restoration strategy to enhance the conservation status of biodiversity and promote self-regulating ecosystems while re-engaging people with nature. Overcoming the challenges in monitoring and reporting rewilding projects would improve its practical implementation and maximize its conservation and restoration outcomes. Here, we present a novel approach for measuring and monitoring progress in rewilding that focuses on the ecological attributes of rewilding. We devised a bi-dimensional framework for assessing the recovery of processes and their natural dynamics through (i) decreasing human forcing on ecological processes and (ii) increasing ecological integrity of ecosystems. The rewilding assessment framework incorporates the reduction of material inputs and outputs associated with human management, as well as the restoration of natural stochasticity and disturbance regimes, landscape connectivity and trophic complexity. Furthermore, we provide a list of potential activities for increasing the ecological integrity after reviewing the evidence for the effectiveness of common restoration actions. For illustration purposes, we apply the framework to three flagship restoration projects in the Netherlands, Switzerland and Argentina. This approach has the potential to broaden the scope of rewilding projects, facilitate sound decision-making and connect the science and practice of rewilding.This article is part of the theme issue ‘Trophic rewilding: consequences for ecosystems under global change’.

International audienceContextLinear transportation infrastructures traverse and separate wildlife populations, potentially leading to their short- and long-term decline at local and regional scales. To attenuate such effects, we need wildlife crossings suitable for a wide range of species.ObjectivesWe propose a method for identifying the best locations for wildlife crossings along linear infrastructures so as to improve the connectivity of species with varying degrees of mobility and living in different habitats. We evaluate highway impacts on mammal species.MethodsThe study area is the Grésivaudan Valley, France. We used allometric relationships to create eight virtual species and model their connectivity networks, developing a nested method defining populations by daily travel distances and connecting them by dispersal. We tested the gain in connectivity for each species produced by 100 and 600 crossing locations respectively in crossable, i.e. with crossing infrastructures, and uncrossable highway scenarios. We identified the crossings that optimize the connectivity of the maximum number of species combining the results in multivariate analyses.ResultsHighly mobile species needing a large habitat area were the most sensitive to highways. The importance of locomotive performance in structuring the graphs decreased with highway impermeability. Depending on the species, the best locations improved connectivity by 0–10 and 2–75 % respectively in the crossable and uncrossable scenarios. Compromise locations were found for seven of the eight species in both scenarios.ConclusionsThis method could guide planners in identifying crossing locations to increase the connectivity of different species at regional scales over the long term