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SARAH M. LEWIS*, STEPHEN GROSS†,AXEL VISEL†‡, MAGGI KELLY* andWILLIAM MORROW§*University of California, 130 Mulford Hall #3114, Berkeley, CA 94720-3114, USA, †DOE Joint Genome Institute, WalnutCreek, CA USA, ‡Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720,USA, §Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USAAbstractIn the United States, renewable energy mandates calling for increased production of cellulosic biofuels willrequire a diversity of bioenergy feedstocks to meet growing demands. Within the suite of potential energy crops,plants within the genus Agave promise to be a productive feedstock in hot and arid regions. The potential distri-butions of Agave tequilana and Agave deserti in the United States were evaluated based on plant growth parame-ters identified in an extensive literature review. A geospatial suitability model rooted in fuzzy logic wasdeveloped that utilized a suite of biophysical criteria to optimize ideal geographic locations for this new crop,and several suitability scenarios were tested for each species. The results of this spatially explicit suitabilitymodel suggest that there is potential for Agave to be grown as an energy feedstock in the southwestern region ofthe United States – particularly in Arizona, California, and Texas – and a significant portion of these areas areproximate to existing transportation infrastructure. Both Agave species showed the highest state-level renewableenergy benefit in Arizona, where agave plants have the potential to contribute 4.8–9.6% of the states’ ethanolconsumption, and 2.5–4.9% of its electricity consumption, for A. deserti and A. tequilana, respectively. This analy-sis supports the feasibility of Agave as a complementary bioenergy feedstock that can be grown in areas tooharsh for conventional energy feedstocks.

Although remote sensing offers the ability to monitor wetland restoration, few have tested automated methods for quantifying vegetation change. We implemented a semiautomated technique using color infrared aerial photography and a common vegetation index, Normalized Difference Vegetation Index (NDVI), to document vegetation colonization in a restoring salt marsh. Change in vegetation over a period of 10 years was analyzed using a postclassification comparison technique where each image year was classified individually into vegetated and nonvegetated areas using NDVI thresholds and then differenced between years to identify areas of vegetation change. Vegetated and nonvegetated areas were identified using this technique, as were areas and time periods of vegetation change. By comparing classified NDVI imagery, we calculated that 90% of our study site was vegetated 10 years after restoration. This study demonstrated that high-resolution remotely sensed data can be analyzed with common geospatial software to monitor change in a rapidly vegetating wetland and that long time frames with yearly image acquisition are needed to quantify plant colonization rates. This method was effective at detecting change in vegetation over time in a variable tidal marsh environment using imagery that had inconsistent specifications and quality across years. Inconsistencies included interannual climate variation, phenology, and presence of algae, as well as differences in pixel size and image brightness. Our findings indicate that remote sensing is useful for postrestoration monitoring of tidal marsh ecosystems.

Question: Previous interpretations of the variance plot of paired quadrat variance method (PQV) have been incomplete. The objective of this study was to clarify the interpretation of PQV, and to shed additional light on how different quadrat variance methods can be used, in concert, to measure scale in transect data. Methods: We used artificial and real data to examine how the PQV method elucidates spatial pattern. Two-term local quadrat variance (TTLQV) and new local variance (NLV) methods, together with their three-term counterparts, were also applied to the same data sets, and the results from all methods were compared. Results: When the mean gap size equalled the mean patch size along a transect, the first peak of the variance of PQV, NLV and TTLQV corresponded with the gap size (or patch size). However, if the mean gap size and patch size were unequal, the variance plot of PQV displayed a flat-topped plateau, in which the first inflection represented the mean size of the smaller phase and the second inflection represented the mean size of the larger phase; TTLQV showed a clear peak and NLV displayed a distinct first peak while the second inflection was dampened. The results also indicated than the three-term versions of quadrat variance methods did not consistently outperform their two-term counterparts, and often confused the interpretation of scale. Conclusions: The quadrat variance methods associated with the patch-gap measurements were able to efficiently detect not only the size of patches, but also the size of gaps.

Whether tracking invasive species, assessing water quality, or monitoring the spread of disease, comprehensive data collection is a key component of sustainable natural resource management. Increasingly, fostering community-based monitoring is seen as a valuable way to augment data gathering and enhance public involvement in environmental management. However, growing quantities of data and increasing interest from the public and decision makers create technical data storage and access issues. Although not yet widely used in natural resource management, Web-based Geographic Information Systems (webGIS), a hybrid of GIS and Internet technologies, are a promising option for entering and storing heterogeneous datasets, indexed by location, and making them widely available in a visual, dynamic, and interactive format. Although webGIS has the potential to increase public participation in environmental management, there are technical, institutional, and social challenges to its implementation and usage that need to be addressed, including differential Internet access, training, and privacy.