Introduction
Disturbance regimes, characterized by disturbance intensities and frequencies (Keeley & Pausas, 2019; Safford, Hayward, Heller, & Wiens, 2012), modify the structure and function of forest ecosystems and their resilience to future disturbances (Bowd, Blanchard, McBurney, & Lindenmayer, 2021; Keeley & Pausas, 2019; McLauchlan et al., 2020; Quintero-Gradilla, Jardel- Peláez, Cuevas-Guzmán, García-Oliva, & Martínez-Yrizar, 2019). In recent years, disturbance regimes in forests worldwide have been altered by varying climate conditions (Bowd et al., 2021; Seidl et al., 2017), anthropogenic interactions (Bowd et al., 2021; Watson et al., 2018), pathogen attacks (Sturrock et al., 2011), invasive species (Wardle & Peltzer, 2017) and increased fire frequency (Bowd et al., 2021; Keeley & Pausas, 2019; Schoennagel et al., 2017; Seidl, Schelhaas, Rammer, & Verkerk, 2014). According to Seidl et al. (2017), future changes in disturbance are likely to be more prominent in coniferous forests and the boreal biome.
Especially in coniferous forests, fire plays an important role in regeneration processes, composition and forest structure (Ávila-Flores et al., 2014; Galicia, Potvin, & Messier, 2015; Quintero-Gradilla et al., 2019). However, the number of fires has increased and the annual area affected amounts to 3.4 million km2, corresponding to 2 % of the Earth's surface (World Wide for Nature & Boston Consulting Group, 2020). According to United Nations reports (United Nations Environment Programme [UNEP], 2022), the risk that wildfires represent to people and the environment is increasing due to several factors, including climate change.
Forest fires in Mexico are a frequent natural disturbance factor in temperate forests (González- Tagle, Schwendenmann, Jiménez Pérez, & Schulz, 2008; Quintero-Gradilla et al., 2019; Rodríguez-Trejo & Fulé, 2003; Yocom & Fulé, 2012). More than 6 016 fires occurred in Mexico only in 2021, with an affected area of more than 469 000 hectares (Comisión Nacional Forestal [CONAFOR], 2022). Frequent or severe forest fires could facilitate or promote land use change. Therefore, forest fragments are at high risk of disturbance, whether natural or anthropogenic. In this regard, in the region of Tamazula, Jalisco, there have been changes in land use for the establishment of avocado plantations during the last two decades (De la Vega-Rivera & Merino-Pérez, 2021). In the south part of the state, Cerro Prieto is surrounded by agricultural fields, where new avocado plantations are being established, putting forest resources and services at risk. These plantations have replaced forests in many parts and put their ecosystem service functions at risk (Barsimantov & Navia Antezana, 2012).
The increase in disturbances has caused multiple researchers to contribute results on forest reference conditions and the ecological role of fire in Mexican vegetation types (Ávila-Flores et al., 2014; Quintero-Gradilla et al., 2019; Rodríguez-Trejo & Fulé, 2003; Rubio Camacho, González Tagle, Benavides Solorio, Chávez Durán, & Xelhuantzi Carmona, 2017). Reconstructions of fire regimes in forests have increased significantly, due to the lack of climatological and forest fire records in extensive parts of the country (González Tagle, Avila Flores, Himmelsbach, & Cerano Paredes, 2020; Molina-Pérez et al., 2017; Yocom et al., 2010). Understanding past forest fire regimes allows the analysis or interpretation of current trends, a precondition for the development of strategies for the management and protection of forest resources.
Conifers are ideal for dendrochronological studies because many form well-defined growth rings (Escoto-García et al., 2017; Rodríguez-Trejo & Fulé, 2003). In Mexico, most of them grow in the sierras, which are characterized by diverse orographic conditions generating climate variations at a relatively small scale. This contributes to a great complexity of environmental conditions that complicates the characterization of a large-scale fire regime. In addition, in combination with anthropogenic disturbances, particular conditions are generated within forest areas, which offer a broad spectrum for the study of forest fire regimes (Molina-Pérez et al., 2017; Yocom et al., 2014). In the study area, the southeastern part of Jalisco, Pinus douglasiana Martínez is a long- lived species with a wide distribution that has good growth and provides good quality wood (Escoto-García et al., 2017); therefore, it is suitable for dendrochronological studies.
The objectives of this study were 1) to reconstruct the historical fire regime in the southeastern part of Jalisco, 2) to determine the seasonality of fire occurrence, and 3) to analyze the influence of climate on fire incidence. The hypotheses proposed were that the fire regime in forests dominated by P. douglasiana has remained unchanged in recent decades and that there is a significant relationship between fire frequency and precipitation patterns.
Materials and Methods
Study area
The study region belongs to the Sierra Madre Occidental located in the southeastern part of Jalisco. The study area is located in Cerro Prieto (Figure 1) in the municipality of Tamazula de Gordiano, which is dominated by a coniferous forest with the presence of P. douglasiana, Pinus devoniana Lindley, Pinus leiophylla Schiede ex Schltdl. & Cham. and Pinus oocarpa Shiede.
The climate of the area is Cw1 type, humid temperate with rainfall in summer (Garcia, 2014), mean annual temperature of 21.5 °C with average minimum temperature of 9.6 °C and average maximum temperature of 32.8 °C. The average annual precipitation is 822 mm, according to climate data for the period 1940-2020 obtained from the Climate Research Unit CRU TS version
4.03 (Harris, Osborn, Jones, & Lister, 2020). In the climogram, presented as Figure 2, two seasons are mainly appreciated: a warm-humid one from May to October and a temperate-dry one from November to April.
The forest area of interest has no fire record prior to 2015. Therefore, to reconstruct the fire records, live trees with well-defined fire scars were sampled. As a selection criterion, long-lived individuals with at least three fire scars were used.
Through Sentinel 2A satellite imagery, the Normalized Burn Ratio (NBR) for the study area from 2017 was determined. The NBR analysis is based on the comparison of satellite imagery before and after a fire. The reference image was taken in December or January (pre-fire) and the post- fire image was taken during the spring months (April and May). Finally, using Google Earth Engine (Petropoulos, Griffiths, & Kalivas, 2014) maps were produced (Figure 3) representing the presence of wildfires for the last six years (2017-2022). Fire severity was classified based on criteria established by the United States Geological Survey (USGS) from the differential NBR (dNBR) (Keeley, 2009).
Field methods
Sampling was selective in an area of about 20 ha (Figure 1) including remote areas, where forest roads and trails are used for access. Sampling was designed in this way to collect the greatest number of fire occurrence dates on trees with evidence of fire damage (Azpeleta Tarancón, Fulé, Sánchez Meador, Kim, & Padilla, 2018; Meunier & Shea, 2020). Part sections of dead (standing or felled) and live trees with well-preserved scars and as long-lived as possible were removed using a chainsaw (Sthil MS 361) (Yocom Kent, 2014). Geographic coordinates of the sampled
specimens were recorded for the spatial distribution representation using a map (Figure 1). A total of 35 fire-scarred samples were collected (34 from live trees and one from a dead tree).
Laboratory methods
Samples were air-dried and polished with 80 to 1200 sandpaper for better visualization of growth rings (González Tagle et al., 2020; Phipps, 1985). Each sample was predated by comparing and similarity of growth patterns and then determining the exact year of formation of each of the growth rings through the comparison of growth patterns called cross dating (Bunn, 2010). The width of each ring was measured with the VELMEX measurement system (USA) with an accuracy of 0.001 mm and Measure J2X software (VoorTech Consulting, 2021). A master chronology was developed based on the annual growths of P. douglasiana, which was also used as a reference for the correct dating of the scarred samples (Yocom et al., 2010). The quality of the dating was monitored with COFECHA software (Grissino-Mayer, 2001a). Fire seasonality was estimated based on the relative position of each of the scars in the annual ring, according to the following categories: early earlywood (EE), middle earlywood (ME), late earlywood (LE), latewood (L), and dormant (D). For practical purposes, scars were grouped into two periods: 1) spring (D + EE) and 2) summer (ME + LE + L) (Grissino-Mayer, 2001b).
Data analysis
Historical fire frequency was analyzed using the ‘burnr’ library in the R program version 4.0.4 (Malevich, Guiterman, & Margolis, 2018). The statistics generated by the program were: mean fire frequency interval (MFI), maximum and minimum intervals between fires, and Weibull mean probability interval (WMPI). The Weibull distribution, which has been used to describe fire regimes, is flexible, can fit asymmetric data sets, and provides a standard way of comparing fire regimes (Grissino-Mayer, 1999). For each statistical analysis, three filters were considered: 1) all scars; 2) 10 % or more of the scars recorded in all samples; and 3) 25 % or more of the scars recorded in all samples (Malevich et al., 2018; Yocom Kent, 2014). The latter allowed determining the intervals of the most extensive and severe fires. The relationship between climate variability and fires was determined by the superposed epoch analysis (SEA) of the ‘burnr’ package in R (Malevich et al., 2018). In general, information about past climate conditions is preserved in historical records and indicators called proxies, which show evidence that can be used to infer climate (Luckman, 2013).
As climate proxies, we used 1) winter precipitation for the area, data obtained using CRU TS Climate Research Unit version 4.03 (Harris et al., 2020), 2) the Palmer Drought Severity Index (PDSI; Stahle et al., 2016), and 3) the Pacific Decadal Oscillation Index (PDO; National Centers for Environmental Information [NCEI], 2021). All proxies were compared for the year of the fire, five years before the fire, and two years after the fire (Malevich et al., 2018).
Results and Discussion
Fire records
In total, 114 scars were successfully dated to the exact year of formation. The scars correspond to 30 samples from living trees (86 %), one sample from a dead tree (3 %) and four samples (11 %) where it was impossible to date scars due to decay.
The fire record was reconstructed for the period 1945-2011, because the study trees showed no evidence of fire between 1807 and 1944 (137 years). The first scar was identified in 1945 and the last one in 2011; for this 66-year period, 14 fires were detected corresponding to the analysis of 100 % of scars. Table 1 shows that, for the 10 % filter of the scars determined in all samples, the period of record includes the years 1962 to 2011 (49 years) with nine fires. The analysis applied with the 25 % filter showed six fires in the period 1979-2011 (32 years). According to Figure 4, three years accounted for 36 % of the scars recorded: 1988 (n = 22), 1996 (n = 19) and 2003 (n = 21). Based on the records of the Forest Management Unit (UMAFOR) 1404, the area was under management from 1945 to 1997; therefore, there is a high probability that the trees with older fire records were harvested. In addition, forest fire protection and control plans were implemented as documented in other studies in the Sierra Madre Occidental (Cerano-Paredes et al., 2015; Molina- Pérez et al., 2017).
Filters | 100% | 25% | 10% |
---|---|---|---|
Range of events | 1945-2011 | 1979-2011 | 1962-2011 |
Number of intervals | 13 | 5 | 8 |
MFI (years) | 5.1 | 6.4 | 6.1 |
WMPI (years) | 4.3 | 6.5 | 5 |
Minimum frequency interval between fires (years) | 1 | 3 | 1 |
Maximum frequency interval between fires (years) | 12 | 8 | 17 |
MFI: mean fire frequency interval; WMPI: Weibull median probability interval.
Seasonality of fires
For the study area, all scars (100 %) were located in the growth zone of early earlywood (EE); consequently, fires in the area occurred during the spring corresponding to the dry season (Figure 2). This same seasonality pattern is repeated in other areas of the Sierra Madre Occidental such as in Durango (Molina-Pérez et al., 2017), Jalisco (Cerano-Paredes et al., 2015) and Puebla (Cerano-Paredes et al., 2016), where 92.2 %, 98.3 % and 91.7 % of fires, respectively, occurred in the spring.
Historical fire regimes
The fire record for the period 1945-2011 was used to determine the frequency statistics. When considering 100 % scars, the mean fire frequency interval (MFI) was 5.1 years; for the 10 % filter, the MFI was 6.1 years; and for the 25 % filter, which represents the most extensive fires in the area, the MIF was 6.4 years (Table 1). The Weibull median probability interval (WMPI) was similar to the MFI showing the pattern of increasing as the filters were applied (Table 1). In short, the average fire return periods in the area were quite short (5.1 to 6.4 years); however, it is very likely that fire intensity was low, as has been determined in other studies along the Sierra Madre Occidental (Molina-Pérez et al., 2017; Sáenz-Ceja & Pérez-Salicrup, 2019). As a consequence, the frequent reduction of fuels in the area is promoted, which reduces the probability of large fires (Fulé et al., 2012) resulting in severe impacts to the forest, changing the structure and species composition ().
For all fire scars, a WMPI of 4.3 years was determined. Considering the filter of 10 % of fire scars, the WMPI was 5. For the most extensive fires (>25 %), the periods between fires were longer (6.5 years) than for the least extensive fires (Table 1). Contrary to that recorded in studies in similar forests in the Sierra Madre Oriental (Yocom et al., 2010, 2014), a clear interruption of fires is seen after 1940. Moreover, it is observed that the most extensive and severe fires occurred from 1979 onwards (Figure 4). This pattern of increase in fires and severity during the 1970s has also been recorded in Durango (Molina-Pérez et al., 2017) and Jalisco (Cerano-Paredes et al., 2015).
Fire-climate relationship
For the period from 1945 to 2011, which includes the most extensive events (filter 25 %), superposition epoch analyses (SEA) indicated that the reconstructed fires in the forests of southeastern part of Jalisco occurred during years with below-average precipitation values and negative PSDI values (Figure 5a and 5b); while three years prior to the fire, the proxies winter precipitation and PDO showed negative values (dry conditions) significantly (P < 0.05) (Figure 5a and 5c). PDSI also shows negative values three years prior; however, they are not significant (Figure 5b). Similar results have been documented in regions close to the study area, where the presence of fires was associated with below average precipitation values and wet conditions preceding the occurrence of fires (Cerano-Paredes et al., 2015; Fulé, Villanueva-Díaz, & Ramos- Gómez, 2005).
Most of the reconstructed fires for the 1944-2011 period were recorded under below-average winter precipitation conditions (10 of 14 fires, 75 %; Figure 6a) and in dry periods of the PDSI
(10 of 14 fires, 75 %; Figure 6b). For the PDO index, half of the events were recorded under negative conditions mainly between 1940 and 1980. This is consistent with variations in the magnitude of this phenomenon usually prevailing over several decades (Mantua, Hare, Zhang, Wallace, & Francis, 1997). Fires between 1940 and 1980 developed in a combination of low winter precipitation and negative PDO values (Figure 6a and 6c). The effects of this combination have been documented as conditions that favor the occurrence of wildfires in Mexico (Cerano- Paredes et al., 2019). The consequences of the combination of certain weather phenomena (PDO, PDSI and winter precipitation) are usually more important in the formation of periods with greater abnormality in weather patterns than in comparison with single weather events (Pavia, Graef, & Reyes, 2006).
Conclusions
The forest fire regime in the southeastern part of Jalisco is considered frequent, of low intensity and unchanged in the last four decades. Therefore, the first hypothesis is confirmed that the fire regime in forests dominated by Pinus douglasiana has not changed; the relationship between fire frequency and precipitation patterns in the area is also significant. Previous drought conditions had a significant influence on the occurrence of fires. This information is very important for the recognition of periods with a higher probability of fire occurrence. To maintain these characteristics, fire management is essential, including monitoring and management of forest fuels to prevent large forest fires. In addition, it is important to raise awareness among people in forest areas about the use of fire and the risks it poses to forests.