Tree Rings as Proxies of Historical Runoff in a National Park in Northern Mexico: A Major Ecosystem Service Provider

• Published in: Atmosphere 2023-08, Vol.14 (8), p.1199
• Main Authors: Villanueva-Díaz, José, Correa-Díaz, Arian, Castruita-Esparza, Luis Ubaldo, Gutiérrez-García, Jesús Valentín, Martínez-Sifuentes, Aldo Rafael, Reyes-Camarillo, Fátima del Rocío
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Anomalies; Aquifers; Basins; Bears; Biodiversity; bootstrap modeling; Conifers; Dendrochronology; Dendroclimatology; Ecosystem services; El Nino; El Nino phenomena; El Nino-Southern Oscillation event; ENSO indices; Environmental aspects; Groundwater; Groundwater recharge; Groundwater runoff; Hydrology; Management; National parks; National parks and reserves; PDO; Pine trees; Pinus leiophylla; Precipitation; Precipitation and runoff; Rivers; Runoff; Runoff patterns; Sea surface; Sea surface temperature; Sea surface temperature anomalies; Southern Oscillation; Stream discharge; Stream flow; Streamflow; streamflow reconstruction; Surface temperature; Temperature anomalies; Time series; Tree rings; tree-ring chronologies; Trends; Tributaries; Water; Water allocation
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos14081199

A dendrochronological network of conifers (Pinus leiophylla, Pinus cembroides, Pinus engelmannii) was developed in the Cumbres de Majalca National Park (CMNP) in Chihuahua, Mexico, to reconstruct historical runoff patterns and examine the impact of ocean–atmosphere phenomena. The CMNP plays a vital role as a runoff source for Conchos River tributaries and groundwater recharge for Chihuahua City and nearby populations. The ring-width chronologies displayed a common signal from 1859 to 2021, with the highest association found between P. engelmannii and P. leiophylla (r = 0.65) and the lowest between P. cembroides and P. engelmannii (r = 0.55). The first principal component explained 75.7% of the variance, and among the species, P. leiophylla exhibited the highest correlation (0.624, p < 0.05) with the accumulated streamflow records from the previous November to July, allowing the construction of a bootstrapped model for runoff reconstruction. The reconstructed streamflow spanned from 1859 to 2014, with an average of 2.732 × 108 m3. Periods of low runoff occurred in 1860–1880, 1940–1960, and 1994–2014, while extreme wet years with high runoff occurred in 1865, 1884, and 1987. The interannual streamflow variability correlated significantly with ENSO indices (SOI, MEI, TRI, and sea surface temperature anomalies), particularly during the winter–spring seasons, indicating that warm phases of the ENSO increased precipitation and runoff. The analysis of return periods revealed probabilities for specific runoff volumes, enabling stakeholders to use the information to develop effective strategies for sustainable water allocation and utilization in the region.