Abstract
Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.
Highlights
Invasive weeds substantially reduce forage production and biodiversity in grasslands worldwide [1,2,3,4,5,6], eroding their value for grazing and conservation [2, 7,8,9,10]
Individual digitized color infra-red (CIR) images provided clues about weed patch distribution that could be used by land managers in preliminary assessments to identify suspect areas to investigate on Mapping invasive weed dynamics at landscape scale the ground
In March CIR images, for example, vegetation patches associated with foragedominated ground truth points (Fig 2A, green circles) generally appeared greener than those associated with weed-dominated points (Fig 2A, red circle)
Summary
Invasive weeds substantially reduce forage production and biodiversity in grasslands worldwide [1,2,3,4,5,6], eroding their value for grazing and conservation [2, 7,8,9,10]. Despite continuous effort and resource investment [2, 11,12,13,14], control of invasive grassland weeds remains a persistent challenge in part because of the logistical demands of detecting and monitoring infestations. These approaches demand landscape-scale perspectives on the mechanisms underlying invasive species spread and persistence over time [17, 18]. Most studies on the effects of management on invasive species are conducted at the much smaller scale of 1-m2 plots. Such small plots can assess local responses to management but provide only a limited picture of landscape heterogeneity. Unless embedded within larger landscape assessments, small plots cannot readily quantify expansion, contraction, and persistence of invaded patches over time
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