Pine straw yields and economic benefits when added to traditional wood products in loblolly, longleaf and slash pine stands

Paper presented at the 12th North American Agroforesty Conference, which was held June 4-9, 2011 in Athens, Georgia.In Ashton, S. F., S.W. Workman, W.G. Hubbard and D.J. Moorhead, eds. Agroforestry: A Profitable Land Use. Proceedings, 12th North American Agroforestry Conference, Athens, GA, June 4-9, 2011.Many forest landowners have the opportunity to manage their loblolly, longleaf and slash pine stands for pine straw (fresh undecomposed needles; the litter layer) for additional revenues. Pine straw is used primarily as mulch in landscaping and has grown in revenues paid to landowners from $15.5 million in 1999 to$81 million in 2009 in Georgia. Pine straw is typically sold by the acre or by the bale. Selling pine straw by the acre is advantageous for absentee landowners. Selling pine straw by the bale can generate more annual income but bale counts need to be accurate and bale size must be clearly defined. Recent (2005-09) per acre revenues range from $50 to$125/year. Rectangular (13x13x28 inches) bale prices range from $0.25 to$0.40 for loblolly, $0.50 to$1.25 for longleaf, and $0.50 to$0.65 for slash pine in Georgia. Per rake yields from loblolly stands tend to be 15 to 30% greater (150 to 425 bales/acre) than slash (120 to 375 bales/acre) and longleaf pine (100 to 350 bales/acre). Pine straw raking starts at canopy closure continuing to the first thinning, generating from $300/acre to over$1000/acre in new income.E. David Dickens (1), David J. Moorhead (1), Charles T. Bargeron (1),and Bryan C. McElvany (2) ; 1. Warnell School of Forestry & Natural Resources. 2. College of Agriculture & Environmental Sciences, The University of Georgia, Statesboro, Tifton, and Soperton, GA.Includes bibliographical references

Forest Resources Digital Information System

Forestry Images, the digitized documented forest health image archive, was developed with the aim to gather, create, maintain, and distribute digital information as tools to enhance and complement information exchange and educational activities. The Forestry Images System exists under the umbrella of Bugwood Network (Bargeron, Douce, & Moorhead, 2000). The increased volume of images and its usage statistics required major changes to enhance the system access, better content management, and security. The enhanced system is standard compliant based on recommendations from the World Wide Web Consortium (W3C) and the U.S. government Section 508

Invasive species risk assessments need more consistent spatial abundance data

Spatial abundance information is a critical component of invasive plant risk assessment. While spatial occurrence data provide important information about potential establishment, abundance data are necessary to understand invasive species’ populations, which ultimately drive environmental and economic impacts. In recent years, the collective efforts of numerous management agencies and public participants have created unprecedented spatial archives of invasive plant occurrence, but consistent information about abundance remains rare. Here, we develop guidelines for the collection and reporting of abundance information that can add value to existing data collection efforts and inform spatial ecology research. In order to identify the most common methods used to report abundance, we analyzed over 1.6 million invasive plant records in the Early Detection and Distribution Mapping System (EDDMapS). Abundance data in some form are widely reported, with 58.9% of records containing qualitative or quantitative information about invasive plant cover, density, or infested area, but records vary markedly in terms of standards for reporting. Percent cover was the most commonly reported metric of abundance, typically collected in bins of trace (25%). However, percent cover data were rarely reported along with an estimate of area, which is critical for ensuring accurate interpretation of reported abundance data. Infested area is typically reported as a number with associated units of square feet or acres. Together, an estimate of both cover and infested area provides the most robust and interpretable information for spatial research and risk assessment applications. By developing consistent metrics of reporting for abundance, collectors can provide much needed information to support spatial models of invasion risk

Climate Change, Carbon Dioxide, and Pest Biology, Managing the Future: Coffee as a Case Study

The challenge of maintaining sufficient food, feed, fiber, and forests, for a projected end of century population of between 9–10 billion in the context of a climate averaging 2–4 °C warmer, is a global imperative. However, climate change is likely to alter the geographic ranges and impacts for a variety of insect pests, plant pathogens, and weeds, and the consequences for managed systems, particularly agriculture, remain uncertain. That uncertainty is related, in part, to whether pest management practices (e.g., biological, chemical, cultural, etc.) can adapt to climate/CO2 induced changes in pest biology to minimize potential loss. The ongoing and projected changes in CO2, environment, managed plant systems, and pest interactions, necessitates an assessment of current management practices and, if warranted, development of viable alternative strategies to counter damage from invasive alien species and evolving native pest populations. We provide an overview of the interactions regarding pest biology and climate/CO2; assess these interactions currently using coffee as a case study; identify the potential vulnerabilities regarding future pest impacts; and discuss possible adaptive strategies, including early detection and rapid response via EDDMapS (Early Detection & Distribution Mapping System), and integrated pest management (IPM), as adaptive means to improve monitoring pest movements and minimizing biotic losses while improving the efficacy of pest control

Lights, Camera...Citizen Science: Assessing the Effectiveness of Smartphone-based Video Training in Invasive Plant Identification dataset

The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphone-based applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional “in-person” training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three training models: 1) in-person, 2) app-based video, and 3) app-based text/images in the context of invasive plant identification in Massachusetts. Encouragingly, we find that participants who received video training were as successful at invasive plant identification as those trained in-person, while those receiving just text/images were less successful. This finding has implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is impractical. This file is the raw data that accompanies the PLoS article.https://scholarworks.umass.edu/eco_datasets/1000/thumbnail.jp

Lights, camera…citizen science: assessing the effectiveness of smartphone-based video training in invasive plant identification.

The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphone-based applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional "in-person" training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three training models: 1) in-person, 2) app-based video, and 3) app-based text/images in the context of invasive plant identification in Massachusetts. Encouragingly, we find that participants who received video training were as successful at invasive plant identification as those trained in-person, while those receiving just text/images were less successful. This finding has implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is impractical

Sample screenshot images from the Outsmart App.

<p>Sample screenshot images from the Outsmart App.</p

Percent correctly identified by the five species investigated.

<p>Percent correctly identified by the five species investigated.</p

Percent correct by training type and plant ID experience.

<p>Percent correct by training type and plant ID experience.</p