Assessing Distribution Patterns, Extent, and Current Condition of Northwest Mexico Mangroves

This study contributes to the worldwide effort to update the status of mangroves, assessing a large mangrove distribution area in Mexico by analyzing Landsat MSS from the early 1970s and TM imagery from 2005. Four states (Baja California Sur, Sonora, Sinaloa, and Nayarit) integrate the northwest region of Mexico, where the mangrove area was estimated to be around 180,000 ha on both dates, with a reduction of about 2% by 2005. Nayarit by itself had a large decrease (>10,000 ha), while the other states increased their mangrove extent from 4 to 15%. However, this increase was probably a consequence of improved satellite capabilities in 2005 rather than mangrove expansion. Mangrove condition, measured through a normalized difference vegetation index (NDVI), was categorized into four types based in the index value distributions. Type 1, representing the poorest condition, included values below the first quartile (Q1), while Type 4, the best condition, was indicated by values above Q3. One of the intermediate categories (Type 3) was dominant, accounting for >40% of the total mangrove surface in both the 1970s and 2005. Mangrove systems in northwest Mexico have different conditions of stress, and thus different management strategies should be identified to preserve and maintain those systems.

[1]  F. J. García-Haro,et al.  Acerca de los índices de vegetación , 1997 .

[2]  U. Mehlig Phenology of the red mangrove, Rhizophora mangle L., in the Caeté Estuary, Pará, equatorial Brazil , 2006 .

[3]  Jinfei Wang,et al.  Mapping Disturbances in a Mangrove Forest Using Multi-Date Landsat TM Imagery , 2001, Environmental management.

[4]  Jorge Soberón,et al.  La Comisión Nacional para el Conocimiento y Uso de la Biodiversidad , 1993 .

[5]  P. Mumby,et al.  A review of remote sensing for the assessment and management of tropical coastal resources , 1996 .

[6]  N. Holbrook,et al.  The role of freezing in setting the latitudinal limits of mangrove forests. , 2007, The New phytologist.

[7]  A. C. Ellis,et al.  Remote sensing techniques for mangrove mapping , 1998 .

[8]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[9]  D. Alongi Mangrove forests: Resilience, protection from tsunamis, and responses to global climate change , 2008 .

[10]  Halina T. Kobryn,et al.  Assessing the extent of mangrove change caused by Cyclone Vance in the eastern Exmouth Gulf, northwestern Australia , 2008 .

[11]  J. R. Jensen,et al.  Remote Sensing of Mangrove Wetlands: Relating Canopy Spectra to Site-Specific Data , 1996 .

[12]  Assessment of landscape changes and their effects on the San Blas estuarine system, Nayarit (Mexico), through Landsat imagery analysis , 2006 .

[13]  C. Berlanga-Robles,et al.  On the reliability of the data of the extent of mangroves: A case study in Mexico , 2008 .

[14]  C. Vaiphasa Remote sensing techniques for mangrove mapping , 2006 .

[15]  M. Hansen,et al.  Integrated tools for natural resources inventories in the 21st century , 2000 .

[16]  S. Fortuna,et al.  Status and trends in mangrove area extent worldwide , 2003 .