Earth and field observations underpin metapopulation dynamics in complex landscapes: Near-term study on carabids.

Understanding risks to biodiversity requires predictions of the spatial distribution of species adapting to changing ecosystems and, to that end, Earth observations integrating field surveys prove essential as they provide key numbers for assessing landscape-wide biodiversity scenarios. Here, we develop, and apply to a relevant case study, a method suited to merge Earth/field observations with spatially explicit stochastic metapopulation models to study the near-term ecological dynamics of target species in complex terrains. Our framework incorporates the use of species distribution models for a reasoned estimation of the initial presence of the target species and accounts for imperfect and incomplete detection of the species presence in the study area. It also uses a metapopulation fitness function derived from Earth observation data subsuming the ecological niche of the target species. This framework is applied to contrast occupancy of two species of carabids (Pterostichus flavofemoratus, Carabus depressus) observed in the context of a large ecological monitoring program carried out within the Gran Paradiso National Park (GPNP, Italy). Results suggest that the proposed framework may indeed exploit the hallmarks of spatially explicit ecological approaches and of remote Earth observations. The model reproduces well the observed in situ data. Moreover, it projects in the near term the two species' presence both in space and in time, highlighting the features of the metapopulation dynamics of colonization and extinction, and their expected trends within verifiable timeframes.

Predicting the vulnerability of seasonally-flooded wetlands to climate change across the Mediterranean Basin.

Wetlands have been declining worldwide over the last century with climate change becoming an additional pressure, especially in regions already characterized by water deficit. This paper investigates how climate change will affect the values and functions of Mediterranean seasonally-flooded wetlands with emergent vegetation. We simulated the future evolution of water balance, wetland condition and water volumes necessary to maintain these ecosystems at mid- and late- 21st century, in 229 localities around the Mediterranean basin. We considered future projections of the relevant climatic variables under two Representative Concentration Pathway scenarios assuming a stabilization (RCP4.5) or increase (RCP 8.5) of greenhouse gases emissions. We found similar increases of water deficits at most localities around 2050 under both RCP scenarios. By 2100, however, water deficits under RCP 8.5 are expected to be more severe and will impact all localities. Simulations performed under current conditions show that 97% of localities could have wetland habitats in good state. By 2050, however, this proportion would decrease to 81% and 68% under the RCP 4.5 and RCP 8.5 scenarios, respectively, decreasing further to 52% and 27% by 2100. Our results suggest that wetlands can persist with up to a 400 mm decrease in annual precipitation. Such resilience to climate change is attributed to the semi-permanent character of wetlands (lower evaporation on dry ground) and their capacity to act as reservoir (higher precipitation expected in some countries during winter). Countries at highest risk of wetland degradation and loss are Algeria, Morocco, Portugal and Spain. Degradation of wetlands with emergent vegetation will negatively affect their biodiversity and the services they provide by eliminating animal refuges and primary resources for industry and tourism. A sound strategy to preserve these wetlands would consist of proactive management to reduce non-climate stressors.

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts.

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.