Alternative PAs from Marxan runs: (a) Additional PAs including the existing PAs (15.3% of total land area), (b) PAs without locking in the existing PAs (13.9% of total land area).

<p>Both Marxan runs targeted representing 15% of all species’ ranges, and the same BLM value applied to both Marxan runs.</p

Distribution of the protected areas with province names (left) and locations of surveyed occurrence points of South Korea (right).

<p>Distribution of the protected areas with province names (left) and locations of surveyed occurrence points of South Korea (right).</p

Comparisons between (a) additional PAs including existing PAs and (b) PAs without locking in the existing PAs as a function of average range elevation.

<p>In Figs 5a and 5b, species were grouped as a function of the average elevation of species’ range. We applied the Wilcoxon rank-sum test for each elevation class to compare the difference between the two (P ≤ 0.01 for all 10 elevation classes). Representation in additional PAs including existing PAs is significantly higher for species whose average elevation is higher than 200 m. The red point in each bar is the average percentage within group. In Figs 5c and 5d, species’ range captured in PAs were compared by species’ mean elevation ranges.</p

Average percentage of species’ ranges captured in the existing protected areas and in alternative PAs scenarios from Marxan results.

<p>Average percentage of species’ ranges captured in the existing protected areas and in alternative PAs scenarios from Marxan results.</p

Study flow diagram.

<p>After we ran the MARS SDM to model 2,297 plant species ranges, we used Marxan for running alternative conservation scenarios: 1) Marxan generated PAs with a total area equal to existing PAs; 2) potential additional PAs to increase the representation of plant species in two ways. We considered two extent targets that increase overall PAs: a doubling of the existing PAs’ area and an increase to 17% of the mainland area. We selected additional PAs to closely reach to these extent targets from the top scored areas of the summed solution of 100 Marxan runs for each case.</p

Sites and causes of puma mortalities in the eastern Peninsular Range, 1981–2013.

<p>Area depicted is generally east of Interstate 15, with the Parque to Park linkage noted. Inset shows location within California.</p

Proportions and numbers of radio collared pumas that died from different causes in Southern California study areas from 2001–2013.

<p>^a Mortalities secondary to depredation permits and vehicle strikes</p><p>differed between the two populations (P = 0.034; Fisher’s exact test).</p><p>Proportions and numbers of radio collared pumas that died from different causes in Southern California study areas from 2001–2013.</p

Results of the known-fate model (Program MARK) for survival (S) for radio collared pumas in southern California, USA.

<p>Results of the known-fate model (Program MARK) for survival (S) for radio collared pumas in southern California, USA.</p

Puma study area in southern California, USA, and regional context.

<p>The focal area of this study includes the Santa Ana Mountains and the eastern Peninsular Range. Inset shows location within California.</p

Variables related to time to death in the Cox proportional hazards model of survival of radio collared pumas in southern California, USA.

<p>*Covariates significant at P ≤ 0.05.</p><p>^aThe final model controlled for population and sex which were not significantly associated with time to mortality</p><p>^bOldest age class (>30 months old) designated as reference category.</p><p>^cYears 2007 and 2008 designated as reference category</p><p>Variables related to time to death in the Cox proportional hazards model of survival of radio collared pumas in southern California, USA.</p