Further clarifying the competition–performance relation: reply to D. W. Johnson et al. (2012)

In their commentary, D. W. Johnson, Johnson, and Roseth (2012) provided some laudatory statements about our article, but they also expressed a number of concerns. The concerns focus on the following issues: types and definitions of competition, our choice of control group, the nature of performance-approach and performance-avoidance goals, the comprehensiveness of the opposing processes model, and performance-approach goals and constructive competition. We respond to each of these issues in turn and conclude with a statement regarding working to build an integrative model of the competition–performance relation (and beyond).

Response to comment on “The response of vegetation on the Andean flank in western Amazonia to Pleistocene climate change” – M.L. Cárdenas et al., Science 331, 1055 (25 February 2011)”.

Puyasena et al. question our interpretation of climate-driven vegetation change on the Andean flank in western Amazonia during the middle Pleistocene and suggest that the use of Podocarpus spp. as a proxy of past climate change should be reassessed. We defend our assertion that vegetation change at the Erazo study site was predominantly driven by climate change due to concomitant changes recorded by multiple taxa in the fossil record.

Effect of uncertainty in surface mass balance--elevation feedback on projections of the future sea level contribution of the Greenland ice sheet

We apply a new parameterisation of the Greenland ice sheet (GrIS) feedback between surface mass balance (SMB: the sum of surface accumulation and surface ablation) and surface elevation in the MAR regional climate model (Edwards et al., 2014) to projections of future climate change using five ice sheet models (ISMs). The MAR (Modèle Atmosphérique Régional: Fettweis, 2007) climate projections are for 2000–2199, forced by the ECHAM5 and HadCM3 global climate models (GCMs) under the SRES A1B emissions scenario. The additional sea level contribution due to the SMB– elevation feedback averaged over five ISM projections for ECHAM5 and three for HadCM3 is 4.3% (best estimate; 95% credibility interval 1.8–6.9 %) at 2100, and 9.6% (best estimate; 95% credibility interval 3.6–16.0 %) at 2200. In all results the elevation feedback is significantly positive, amplifying the GrIS sea level contribution relative to the MAR projections in which the ice sheet topography is fixed: the lower bounds of our 95% credibility intervals (CIs) for sea level contributions are larger than the “no feedback” case for all ISMs and GCMs. Our method is novel in sea level projections because we propagate three types of modelling uncertainty – GCM and ISM structural uncertainties, and elevation feedback parameterisation uncertainty – along the causal chain, from SRES scenario to sea level, within a coherent experimental design and statistical framework. The relative contributions to uncertainty depend on the timescale of interest. At 2100, the GCM uncertainty is largest, but by 2200 both the ISM and parameterisation uncertainties are larger. We also perform a perturbed parameter ensemble with one ISM to estimate the shape of the projected sea level probability distribution; our results indicate that the probability density is slightly skewed towards higher sea level contributions.