Climate change: losing Greenland

Sea level rise drives increased tidal flooding frequency at tide gauges along the U.S. East and Gulf Coasts: Projections for 2030 and 2045

Tidal flooding is among the most tangible present-day effects of global sea level rise. Here, we utilize a set of NOAA tide gauges along the U.S. East and Gulf Coasts to evaluate the potential impact of future sea level rise on the frequency and severity of tidal flooding. Using the 2001–2015 time period as a baseline, we first determine how often tidal flooding currently occurs. Using localized sea level rise projections based on the Intermediate-Low, Intermediate-High, and Highest projections from the U.S. National Climate Assessment, we then determine the frequency and extent of such flooding at these locations for two near-term time horizons: 2030 and 2045. We show that increases in tidal flooding will be substantial and nearly universal at the 52 locations included in our analysis. Long before areas are permanently inundated, the steady creep of sea level rise will force many communities to grapple with chronic high tide flooding in the next 15 to 30 years.

How does climate change influence Arctic mercury?

Recent studies have shown that climate change is already having significant impacts on many aspects of transport pathways, speciation and cycling of mercury within Arctic ecosystems. For example, the extensive loss of sea-ice in the Arctic Ocean and the concurrent shift from greater proportions of perennial to annual types have been shown to promote changes in primary productivity, shift foodweb structures, alter mercury methylation and demethylation rates, and influence mercury distribution and transport across the ocean-sea-ice-atmosphere interface (bottom-up processes). In addition, changes in animal social behavior associated with changing sea-ice regimes can affect dietary exposure to mercury (top-down processes). In this review, we address these and other possible ramifications of climate variability on mercury cycling, processes and exposure by applying recent literature to the following nine questions; 1) What impact has climate change had on Arctic physical characteristics and processes? 2) How do rising temperatures affect atmospheric mercury chemistry? 3) Will a decrease in sea-ice coverage have an impact on the amount of atmospheric mercury deposited to or emitted from the Arctic Ocean, and if so, how? 4) Does climate affect air-surface mercury flux, and riverine mercury fluxes, in Arctic freshwater and terrestrial systems, and if so, how? 5) How does climate change affect mercury methylation/demethylation in different compartments in the Arctic Ocean and freshwater systems? 6) How will climate change alter the structure and dynamics of freshwater food webs, and thereby affect the bioaccumulation of mercury? 7) How will climate change alter the structure and dynamics of marine food webs, and thereby affect the bioaccumulation of marine mercury? 8) What are the likely mercury emissions from melting glaciers and thawing permafrost under climate change scenarios? and 9) What can be learned from current mass balance inventories of mercury in the Arctic? The review finishes with several conclusions and recommendations.

Missing and forbidden links in mutualistic networks

Ecological networks are complexes of interacting species, but not all potential links among species are realized. Unobserved links are either missing or forbidden. Missing links exist, but require more sampling or alternative ways of detection to be verified. Forbidden links remain unobservable, irrespective of sampling effort. They are caused by linkage constraints. We studied one Arctic pollination network and two Mediterranean seed-dispersal networks. In the first, for example, we recorded flower-visit links for one full season, arranged data in an interaction matrix and got a connectance C of 15 per cent. Interaction accumulation curves documented our sampling of interactions through observation of visits to be robust. Then, we included data on pollen from the body surface of flower visitors as an additional link 'currency'. This resulted in 98 new links, missing from the visitation data. Thus, the combined visit-pollen matrix got an increased C of 20 per cent. For the three networks, C ranged from 20 to 52 per cent, and thus the percentage of unobserved links (100 - C) was 48 to 80 per cent; these were assumed forbidden because of linkage constraints and not missing because of under-sampling. Phenological uncoupling (i.e. non-overlapping phenophases between interacting mutualists) is one kind of constraint, and it explained 22 to 28 per cent of all possible, but unobserved links. Increasing phenophase overlap between species increased link probability, but extensive overlaps were required to achieve a high probability. Other kinds of constraint, such as size mismatch and accessibility limitations, are briefly addressed.

Facing future climate change: is the past relevant?

From a socio-economic perspective, the 'sharp end' of climate research is very much about looking forward in time. As far as possible, we need to know what to expect and approximately when to expect it. However, it is argued here that our approach to climate change (including its scientific basis and its policy implications) is firmly linked to our understanding of the past. This is mainly due to the role played by palaeoclimate reconstructions in shaping our expectations of the climate system, in particular via their ability to test the accuracy of our climate models. Importantly, this includes the intuitive models that each of us carries around in our mind, as well as the more complex numerical models hiding inside supercomputers. It is through such models that palaeoclimate insights may affect the scientific and political judgements that we must make in the face of persistent and ultimately irreducible predictive uncertainty. Already we can demonstrate a great deal of confidence in our current understanding of the global climate system based specifically on insights from the geological record. If further advances are to be made effectively, climate models should take advantage of both past and present constraints on their behaviour, and should be given added credence to the extent that they are compatible with an increasingly rich tapestry of past climatic phenomena. Furthermore, palaeoclimate data should be accompanied by clearly defined uncertainties, and organized in arrays that are capable of speaking directly to numerical models, and their limitations in particular.