Assessing agreement among alternative climate change projections to inform conservation recommendations in the contiguous United States

Abstract

Addressing uncertainties in climate vulnerability remains a challenge for conservation planning. We evaluate how confidence in conservation recommendations may change with agreement among alternative climate projections and metrics of climate exposure. We assessed agreement among three multivariate estimates of climate exposure (forward velocity, backward velocity, and climate dissimilarity) using 18 alternative climate projections for the contiguous United States. For each metric, we classified maps into quartiles for each alternative climate projections, and calculated the frequency of quartiles assigned for each gridded location (high quartile frequency = more agreement among climate projections). We evaluated recommendations using a recent climate adaptation heuristic framework that recommends emphasizing various conservation strategies to land based on current conservation value and expected climate exposure. We found that areas where conservation strategies would be confidently assigned based on high agreement among climate projections varied substantially across regions. In general, there was more agreement in forward and backward velocity estimates among alternative projections than agreement in estimates of local dissimilarity. Consensus of climate predictions resulted in the same conservation recommendation assignments in a few areas, but patterns varied by climate exposure metric. This work demonstrates an approach for explicitly evaluating alternative predictions in geographic patterns of climate change.

Figure 1

Conceptual framework proposed by Belote et al. that recommends conservation strategies be based on existing conservation value and projected climate vulnerability.

Figure 2

Mode of quartile in classified data of three climate vulnerability metrics and frequency of mode among 18 different projections for forward velocity (A,B), backward velocity (C,D), and climate dissimilarity (E,F). Maps B,D,F present an index of inter-simulation uncertainty for each climate metric, with areas of red indicating lower intermodel agreement and higher uncertainty.

Figure 3

Maps of inter-metric agreement (or disagreement), showing where the mode of three climate metrics (forward velocity, backward velocity, and climate dissimilarity) were in the lower (top map) or upper (bottom map) quartile. The Venn diagram legends show areas where zero, one, two, or all three metrics were assigned an area to the lower or upper quartiles. In the top map, gray indicates areas where no metrics were in the lower quartile, green indicates where only one of the metrics were assigned to the lower quartile mode, light blue areas indicates two metrics had a mode in lower quartile mode, and dark blue indicates that all three metrics were assigned to the lower quartile mode. In the bottom map, the same pattern is used to map metric agreement using orange (one metric assigned to upper quartile mode), red (two metrics), and black (all three metrics assigned to upper quartile mode).

Figure 4

Bivariate maps of conservation value and climate vulnerability using three climate metrics: forward velocity (A), backward velocity (B), and local climate dissimilarity (C).

Figure 5

Maps of locations occupying the four corners of the conceptual framework of Belote et al., based on forward velocity (top row), backward velocity (middle row), and climate dissimilarity (bottom row), with columns showing the winnowing that happens with increasingly stringent thresholds for climate model consensus, ranging from low at left to high at right: ≥5 (left-hand column), >10 (second column from left), >16 (third column from left), or 18 (right-hand column). Area of each corner is shown in Fig. 6.

Figure 6

Change in area (represented as the proportion of total mapped area of the contiguous U.S.) for the four corners (i.e., Low or High conservation value × Low or High climate Vulnerability) along gradients in confidence as measured by the frequency of quartile mode. Arrows along x-axis represent conditions mapped in Fig. 5.