Integrating drone imagery with existing rangeland monitoring programs.

The recent availability of small and low-cost sensor carrying unmanned aerial systems (UAS, commonly known as drones) coupled with advances in image processing software (i.e., structure from motion photogrammetry) has made drone-collected imagery a potentially valuable tool for rangeland inventory and monitoring.

Beyond greenness: Detecting temporal changes in photosynthetic capacity with hyperspectral reflectance data.

Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant photosynthesis. Spectral vegetation indices are widely used as proxies for vegetation greenness and to estimate state variables such as vegetation cover and leaf area index. However, the capacity of green leaves to take up carbon can change throughout the season.

Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile.

Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems.

Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests.

Leaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments.

Land Use and Environmental Variability Impacts on the Phenology of Arid Agro-Ecosystems.

The overexploitation of water resources in arid environments often results in abandonment of large extensions of agricultural lands, which may (1) modify phenological trends, and (2) alter the sensitivity of specific phenophases to environmental triggers. In Mexico, current governmental policies subsidize restoration efforts, to address ecological degradation caused by abandonments; however, there is a need for new approaches to assess their effectiveness. Addressing this, we explore a method to monitor and assess (1) land surface phenology trends in arid agro-ecosystems, and (2) the effect of climatic factors and restoration treatments on the phenology of abandoned agricultural fields.

Spatial, temporal, and density-dependent components of habitat quality for a desert owl.

Spatial variation in resources is a fundamental driver of habitat quality but the realized value of resources at any point in space may depend on the effects of conspecifics and stochastic factors, such as weather, which vary through time. We evaluated the relative and combined effects of habitat resources, weather, and conspecifics on habitat quality for ferruginous pygmy-owls (Glaucidium brasilianum) in the Sonoran Desert of northwest Mexico by monitoring reproductive output and conspecific abundance over 10 years in and around 107 territory patches. Variation in reproductive output was much greater across space than time, and although habitat resources explained a much greater proportion of that variation (0.

Fine scale spatial urban land cover factors associated with adult mosquito abundance and risk in Tucson, Arizona.

It is currently unclear what role microhabitat land cover plays in determining the seasonal spatial distribution of Aedes aegypti and Culex quinquefasciatus, disease vectors of dengue and West Nile Virus, respectively, in Tucson, AZ. We compared mosquito abundance to sixteen land cover variables derived from 2010 NAIP multispectral data and 2008 LiDAR height data. Mosquitoes were trapped with 30-9 traps from May to October of 2010 and 2011.

Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data.

This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002.