This article will appear in the upcoming June issue of Rangelands, Volume 41, Issue 3 (June 2019).
Rangeland managers require timely, reliable, and easily interpretable information about their land to make informed decisions. One of the biggest challenges managers face is the high temporal variability in plant establishment, growth, and reproduction. Phenology data that describe the timing of plant seasonal stages can be used to design better management systems by adjusting the timing of grazing, fire, and other disturbances relative to the growth stage of key species; and they can be used in planning restoration activities such as herbicide applications or targeted grazing. Phenology observations are most informative when they are made consistently over time for focal plants using standardized protocols. Phenology data from field observations include plant status and percent of canopy with green leaves. For instance, field observations identify when new leaves have unfolded (for forage species), flowers have opened (as floral resources for pollinators), or ripe fruit or grains are present (for harvesting native grass seed). Estimates of percent canopy greenness are made via ocular estimates in the field or using digital cameras mounted at fixed locations (hereafter, phenocams).
Why monitor plant phenology? Phenology data are easier to collect than ever with standardized protocols for field observations and phenocam and satellite image processing tools. On-line tools make metric calculation simple while increasingly sophisticated algorithms are facilitating the integration of different sources of data. Phenocam greenness metrics also serve to link plant- or community-scale phenology observations collected in the field with those from satellite remote sensing.Phenocam data metrics can reveal plant species or functional groups contributing to satellite NDVI, thereby overcoming a limitation in the spatial resolution or granularity of satellite remote sensing in rangelands. In addition, phenocam image time-series can facilitate interpretation of rangeland monitoring data by placing data in the context of inter- and intra-annual weather variability.
Phenology metrics derived from phenocams and satellite remote sensing are key components of on-going research across the Long-Term Agroecosystem Research (LTAR) network. We anticipate that results from these integrated analyses will increasingly enable managers in the private and public sectors to target management interventions, including grazing, herbicide applications, and prescribed fire, with pinpoint accuracy in both space and time.
For more information, contact Dawn Browning at firstname.lastname@example.org
By: Dawn M. Browning, Keirith A. Snyder, and Jeffrey E. Herrick