Generation and analysis of the 2005 land cover map for Mexico using 250m MODIS data

Land cover plays a key role in global to regional monitoring and modeling because it affects and is being affected by climate change and thus became one of the essential variables for climate change studies. National and international organizations require timely and accurate land cover information for reporting and management actions. The North American Land Change Monitoring System (NALCMS) is an international cooperation of organizations and entities of Canada, the United States, and Mexico to map land cover change of North America's changing environment. This paper presents the methodology to derive the land cover map of Mexico for the year 2005 which was integrated in the NALCMS continental map. Based on a time series of 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) data and an extensive sample data base the complexity of the Mexican landscape required a specific approach to reflect land cover heterogeneity. To estimate the proportion of each land cover class for every pixel several decision tree classifications were combined to obtain class membership maps which were finally converted to a discrete map accompanied by a confidence estimate. The map yielded an overall accuracy of 82.5% (Kappa of 0.79) for pixels with at least 50% map confidence (71.3% of the data). An additional assessment with 780 randomly stratified samples and primary and alternative calls in the reference data to account for ambiguity indicated 83.4% overall accuracy (Kappa of 0.80). A high agreement of 83.6% for all pixels and 92.6% for pixels with a map confidence of more than 50% was found for the comparison between the land cover maps of 2005 and 2006. Further wall-to-wall comparisons to related land cover maps resulted in 56.6% agreement with the MODIS land cover product and a congruence of 49.5 with Globcover.

National and sub-national assessments of soil organic carbon stocks and changes: The GEFSOC modelling system

Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO, levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.

Seed dormancy and germination of Ficus lundellii and tropical forest restoration

We investigated seed dormancy and germination in Ficus lundellii Standl. (Moraceae), a native species of Mexico's Los Tuxtlas tropical rain forest. In an 8-h photoperiod at an alternating diurnal (16/8 h) temperature of 20/30 degrees C, germination was essentially complete (96%) within 28 days, whereas in darkness, all seeds remained dormant. Neither potassium nitrate (0.05-0.2%) applied continuously nor gibberellic acid applied either continuously (10-200 ppm) or as a 24 hour pretreatment (2000 ppm) induced germination in the dark. Germination in the light was not reduced by a 24-h hydrochloric acid (0.1-1%) pretreatment, but it was reduced both by a 24-h pretreatment with either H2O2 (0. 1-5 M) or 5% HCl, or by more than 5 days of storage at 40 degrees C (4.5% seed water content). In a study with a 2-dimensional temperature gradient plate, seeds germinated fully and rapidly in the light at a constant temperature of 30 degrees C, and fully but less rapidly in the light at alternating temperatures with low amplitudes (< 12 degrees C) about the optimal constant temperature. The base, optimal and ceiling temperatures for rate of germination were estimated as 13.8, 30.1 and 41.1 degrees C, respectively. In all temperature regimes, light was essential for the germination of F lundellii seeds.

Ultrastructural alterations in mesophyll and bundle sheath chloroplasts of two maize cultivars in response to chilling at high irradiance

Maize (Zea mays L.) seedlings of two cultivars (cv. Bastion adapted to W. Europe, and cv. Batan 8686 adapted to the highlands of Mexico), raised in a glasshouse (19-25 degrees C), were transferred to 4.5 or 9 degrees C at photon flux density (PPFD) of 950 mu mol m(-2) s(-1) with 10-h photoperiod for 58 h and then allowed to recover at 22 degrees C for 16 h (14 h dark and 2 h at PPFD of 180 mu mol m(-2) s(-1)). The ultrastructural responses after 4 h or 26 h at 4.5 degrees C were the disappearance of starch grains in the bundle sheath chloroplasts and the contraction of intrathylakoid spaces in stromal thylakoids of the mesophyll chloroplasts. At this time, bundle sheath chloroplasts of cv. Batan 8686 formed peripheral reticulum. Prolonged stress at 4.5 degrees C (50 h) caused plastid swelling and the dilation of intrathylakoid spaces, mainly in mesophyll chloroplasts. Bundle sheath chloroplasts of cv. Batan 8686 seedlings appeared well preserved in shape and structure. Batan 8686 had also higher net photosynthetic rates during chilling and recovery than Bastion. Extended leaf photobleaching developed during the recovery period after chilling at 4.5 degrees C. This was associated with collapsed chloroplast envelopes, disintegrated chloroplasts and very poor staining.

Cluster analysis of downscaled and explicitly simulated North Atlantic tropical cyclone tracks

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in US landfalling systems. Here we present a tentative study, which examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1° to 0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and sub-tropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity and power dissipation index in each cluster are documented for both configurations. Our results show that except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. We also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, we examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.

A novel satellite-based ocean monitoring system for Mexico

To analyze patterns in marine productivity, harmful algal blooms, thermal stress in coral reefs, and oceanographic processes, optical and biophysical marine parameters, such as sea surface temperature, and ocean color products, such as chlorophyll-a concentration, diffuse attenuation coefficient, total suspended matter concentration, chlorophyll fluorescence line height, and remote sensing reflectance, are required. In this paper we present a novel automatic Satellite-based Ocean Monitoring System (SATMO) developed to provide, in near real-time, continuous spatial data sets of the above-mentioned variables for marine-coastal ecosystems in the Gulf of Mexico, northeastern Pacific Ocean, and western Caribbean Sea, with 1 km spatial resolution. The products are obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images received at the Direct Readout Ground Station (located at CONABIO) after each overpass of the Aqua and Terra satellites. In addition, at the end of each week and month the system provides composite images for several ocean products, as well as weekly and monthly anomaly composites for chlorophyll-a concentration and sea surface temperature. These anomaly data are reported for the first time for the study region and represent valuable information for analyzing time series of ocean color data for the study of coastal and marine ecosystems in Mexico, Central America, and the western Caribbean.