Supporting Information s22

SUPPORTING INFORMATION

Fire management, climate change and their interacting effects on birds in complex

Mediterranean landscapes: dynamic distribution modelling for a model early-

successional species−the near-threatened Dartford Warbler (Sylvia undata)

Appendix 1 – Detailed description of the climate scenarios: Linking IPCC’s scenarios with MEDFIRE model simulations.

The IPCC’s Special Report on Emissions Scenarios (SRES) (IPCC 2000) describes the relationships between the forces driving GHG emissions and their evolution during the

21st century. The scenarios defined in the SRES range from fossil-fuel intensive to alternative futures involving rapid adaptation of new technologies. We selected A2 and

B2 scenarios as they describe a "regionalisation" leading to a heterogeneous world development opposed to "globalization" tending to a homogeneous world development described in the A1 and B1 storylines. A2a describes a highly heterogeneous future world with regionally oriented economies. The main driving forces are a high rate of population growth, increased energy use, land-use changes and slow technological change. The B2a is also regionally oriented but with a general evolution towards environmental protection and social equity.

In the MEDFIRE model different fire size distributions are used depending on the climatic severity of the year. Adverse years are characterized by a high number of weather risk days (Piñol et al. 1998). Therefore, the distribution of fire sizes corresponding to adverse years specifies a higher proportion of large wildfires compared to the distribution corresponding to normal (non-adverse) years (Brotons et al. 2013). The potential total area to be burnt is also drawn from a statistical distribution that differs between adverse and mild years.

In order to develop coherent and plausible climate scenarios in our fire simulations we need to define climatic treatments that can encompass possible future trends in fire regimes for the study area according to the IPCC-SRES climate scenarios (A2a and B2a

“regionalization” storylines). For this purpose, according to the methodology developed in De Cáceres et al. (in prep) we calculated a Cumulative soil water deficit (CSWD; in mm of water) index based on regional climatic records for the period 1980–2010 and determined which years could be considered as meteorologically adverse (Fig. 1).

Cumulative soil water deficit (CSWD; in mm of water) is defined as the average between the annual cumulative soil water deficit of the current and preceding years. We adopted a Thornthwaite-type (Thornthwaite and Mather 1955) approach to estimate

CSWD and calculated its value accounting for the effects of slope and aspect on potential evapotranspiration and within-catchment water redistribution. Historical records of total area burned and fire sizes were assembled for years of the 1975 – 1999 period (Díaz-Delgado et al. 2004; González-Olabarria and Pukkala 2007). Assuming that drier years imply lower fuel moisture and usually lead to larger impact of summer wildfires(Pausas and Paula 2012), we used a threshold of 270 mm in the CSWD regional average to separate years with ‘mild’ summer conditions and years having

‘adverse’ summer conditions (exceptionally dry years that can lead to very large convective fires). We then estimated the historical trend in the probability of having an adverse year, and used the resulting trend to define two climatic treatments: 1) A2: the probability of a year being adverse (Pad-yr) increases from 0.30 to 0.59 for time-slice 2050 (2040 and

2069); 2) B2: the probability of a year being adverse increases from 0.30 to 0.62 for time-slice 2050 (2040 and 2069).

Fig. 1. Historic (2000 – 2010) and predicted (2010 – 2100) sequence of cumulative soil water deficit

(regional averages) for IPCC-A2a and IPCC-B2a scenarios in Catalonia. The dashed line shows the reference value (270) considered as threshold that enabled us to define every year as adverse or mild. References

Brotons L, Aquilué N, de Cáceres M, et al. (2013) How fire history, fire suppression practices and climate change affect wildfire regimes in Mediterranean landscapes. PLoS One 8:e62392. doi: 10.1371/journal.pone.0062392

Díaz-Delgado R, Lloret F, Pons X (2004) Statistical analysis of fire frequency models for Catalonia (NE Spain , 1975 – 1998) based on fire scar maps from Landsat MSS data. Int J Wildl Fire 13:89–99.

González-Olabarria J-R, Pukkala T (2007) Characterization of forest fires in Catalonia (north-east Spain). Eur J For Res 126:421–429.

IPCC (2000) Special report on emission scenarios. A special report of Working Group III of the Intergovernmental Panel on Climate Change. 570.

Pausas JG, Paula S (2012) Fuel shapes the fire-climate relationship: evidence from Mediterranean ecosystems. Glob Ecol Biogeogr 21:1074–1082. doi: 10.1111/j.1466-8238.2012.00769.x

Piñol J, Terradas J, Lloret F (1998) Climate warming, wildfire hazard, and wildfire occurrence in coastal eastern Spain. Clim Change 38:345–357.

Thornthwaite CW, Mather JR (1955) The Water Balance. Publ. in Climatology, vol.8, no.l. C.W. Thornthwaite & Associates, Centerton, New Jersey.