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Monitoring the impact of grazing on rangeland conservation easements using MODIS vegetation indicesTsalyuk, M.; Kelly, M.; Koy, K.; Getz, W. M.; Scott, Butterfield, H. (Society for Range Management, 2015-03)Monitoring the effects of grazing on rangelands is crucial for ensuring sustainable rangeland ecosystem function and maintaining its conservation values. Residual dry matter (RDM), the dry grass biomass left on the ground at the end of the grazing season, is a commonly used proxy for rangeland condition in Mediterranean climates. Moderate levels of RDM are correlated with soil stability, forage production, wildlife habitat, and diversity of native plants. Therefore RDM is widely monitored on rangeland conservation properties. Current ground-based methods for RDM monitoring are expensive, are labor intensive, and provide information in the fall, after the effects of grazing have already occurred. In this paper we present a cost-effective, rapid, and robust methodology to monitor and predict RDM using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. We performed a time series analysis of three MODIS-based vegetation indices (VIs) measured over the period 2000-2012: Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (FPAR). We examined the correlation between the four VIs and fall RDM measured at The Nature Conservancy's Simon Newman Ranch in central California. We found strong and significant correlations between maximum VI values in late spring and RDM in the fall. Among the VIs, LAI values had the most significant correlation with fall RDM. MODIS-based multivariate models predicted up to 63% of fall RDM. Importantly, maximum and sum VIs values were significantly higher in management units with RDM levels in compliance with RDM conservation easement terms compared with units out of compliance. On the basis of these results, we propose a management model that uses time series analysis of MODIS VIs to predict forage quantities, manage stocking rates, and monitor rangeland easement compliance. This model can be used to improve monitoring of rangeland conservation by providing information on range conditions throughout the year. © 2015 Society for Range Management. Published by Elsevier Inc. All rights reserved.
Testing a Remote Sensing-Based Interactive System for Monitoring Grazed Conservation LandsFord, L. D.; Butterfield, H. S.; Van, Hoorn, P. A.; Allen, K. B.; Inlander, E.; Schloss, C.; Schuetzenmeister, F.; Tsalyuk, M. (Society for Range Management, 2017-10)Many public agencies and land trusts that manage grazing lands are interested in using remote sensing technologies to make their monitoring programs more efficient but lack the expertise to do so. In California annual grasslands, using remote sensing is especially challenging because the dominant vegetation is not detectable by standard technologies at a key time of year for monitoring. The Nature Conservancy of California (TNC) has developed RDMapper, an easy-to-use web-based tool that uses satellite-based productivity estimates, rainfall records, and compliance history to identify management units at risk of being below the required level of residual dry matter (RDM). TNC successfully used RDMapper in 2015 and 2016 to predict compliance across approximately 47,000 hectares of conservation easement grasslands, while reducing monitoring costs by 42%. We also applied RDMapper on six non-TNC properties (approximately 5,700 hectares) owned by two public agencies. We correctly predicted RDM compliance on 74% of the management units and found the method to be successful overall, with several challenges mainly relating to meeting RDMapper's data requirements. Our study illuminated potential benefits, hurdles, and best practices for landowners interested in using RDMapper to increase monitoring efficiency, and made recommendations to improve it. Adding RDMapper to conventional monitoring toolkits could be game-changing for public lands management agencies that currently struggle to manage vast grasslands. © 2017 The Society for Range Management