Notes on the Biology of \u3ci\u3eSaperda Imitans\u3c/i\u3e Infesting Wind-Damaged Black Cherry in Allegheny Hardwood Stands

This paper reports observations made on the life history and biology of Saperda imitans Felt & Joutel in black cherry, Prunus serotina Ehrh. S. imitans was the principle longhorned beetle (Coleoptera: Cerambycidae) reared from bolts collected from 68 wind-thrown black cherry at the Kane Experimental Forest in northwestern Pennsylvania. It was also the only species that overwintered in the sapwood/outer heartwood, and thus impacted the commercial value of these trees. Gaurotes cyanipennis (Say) was the only other cerambycid reared from caged bolts taken from wind-thrown black cherry. The cerambycids Stenocorus vittiger (Randall), Arthophylax attenuatus (Haldman), G. cyanipennis, Neoclytus acuminatus acuminatus (F.), Clytus ruricola (Olivier), Cyrtophorus verrucosus (Olivier), and Astylopsis macula (Say) were captured in ethanol-baited Lindgren® funnel traps placed in wind-thrown stands, but were not reared from cherry logs. S. imitans was not caught in these traps and apparently it is not attracted to ethanol baits. Neither S. imitans nor G. cyanipennis were reared from completely uprooted trees (dead) or trees with a major portion of the root system still embedded in soil (live). Preferred hosts were black cherry with moist phloem and epicormic branches with \u3c25% live foliage (dying). The density of S. imitans galleries was similar for dying trees in each of three diameter classes; 20-30 cm, \u3e30-40 cm, \u3e40cm. Samples taken from the upper half of the first 5 m of black cherry boles had a higher density of galleries than did those from the lower half. The beetle was recovered in low numbers from branches \u3c10 cm in basal diameter. S. imitans is univoltine and in 2007 peak emergence of adults occurred from late May to early June. Results identified the condition of wind-damaged black cherry most susceptible to an infestation of S. imitans. This information can be used to establish salvage priorities following a weather event such as this

Key issues in rigorous accuracy assessment of land cover products

© 2019 Accuracy assessment and land cover mapping have been inexorably linked throughout the first 50 years of publication of Remote Sensing of Environment. The earliest developers of land-cover maps recognized the importance of evaluating the quality of their maps, and the methods and reporting format of these early accuracy assessments included features that would be familiar to practitioners today. Specifically, practitioners have consistently recognized the importance of obtaining high quality reference data to which the map is compared, the need for sampling to collect these reference data, and the role of an error matrix and accuracy measures derived from the error matrix to summarize the accuracy information. Over the past half century these techniques have undergone refinements to place accuracy assessment on a more scientifically credible footing. We describe the current status of accuracy assessment that has emerged from nearly 50 years of practice and identify opportunities for future advances. The article is organized by the three major components of accuracy assessment, the sampling design, response design, and analysis, focusing on good practice methodology that contributes to a rigorous, informative, and honest assessment. The long history of research and applications underlying the current practice of accuracy assessment has advanced the field to a mature state. However, documentation of accuracy assessment methods needs to be improved to enhance reproducibility and transparency, and improved methods are required to address new challenges created by advanced technology that has expanded the capacity to map land cover extensively in space and intensively in time

Does Landowner Awareness and Knowledge Lead to Sustainable Forest Management? A Vermont Case Study

Family forest owners control 40% of forestland in the United States. Timber harvesting on family forests represents a critical component of the nation\u27s wood supply. We examined how awareness and knowledge translated into actual forest management practices. We conducted field surveys on 59 family forest properties, coupled with a landowner survey designed to measure landowner engagement. We determined that engaged landowners implemented silviculture and Best Management Practices at a higher level than their less engaged counterparts. Improvement was needed across the board. Forestry Extension professionals should continue to promote and re-enforce awareness and knowledge among landowners

Good practices for estimating area and assessing accuracy of land change

The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs. Statistically robust and transparent approaches for assessing accuracy and estimating area of change are critical to ensure the integrity of land change information. We provide practitioners with a set of “good practice” recommendations for designing and implementing an accuracy assessment of a change map and estimating area based on the reference sample data. The good practice recommendations address the three major components: sampling design, response design and analysis. The primary good practice recommendations for assessing accuracy and estimating area are: (i) implement a probability sampling design that is chosen to achieve the priority objectives of accuracy and area estimation while also satisfying practical constraints such as cost and available sources of reference data; (ii) implement a response design protocol that is based on reference data sources that provide sufficient spatial and temporal representation to accurately label each unit in the sample (i.e., the “reference classification” will be considerably more accurate than the map classification being evaluated); (iii) implement an analysis that is consistent with the sampling design and response design protocols; (iv) summarize the accuracy assessment by reporting the estimated error matrix in terms of proportion of area and estimates of overall accuracy, user's accuracy (or commission error), and producer's accuracy (or omission error); (v) estimate area of classes (e.g., types of change such as wetland loss or types of persistence such as stable forest) based on the reference classification of the sample units; (vi) quantify uncertainty by reporting confidence intervals for accuracy and area parameters; (vii) evaluate variability and potential error in the reference classification; and (viii) document deviations from good practice that may substantially affect the results. An example application is provided to illustrate the recommended process

Sample-based estimation of tree cover change in haiti using aerial photography:Substantial increase in tree cover between 2002 and 2010

Recent studies have used high resolution imagery to estimate tree cover and changes in natural forest cover in Haiti. However, there is still no rigorous quantification of tree cover change accounting for planted or managed trees, which are very important in Haiti’s farming systems. We estimated net tree cover change, gross loss, and gross gain in Haiti between 2002 and 2010 from a stratified random sample of 400 pixels with a systematic sub-sample of 25 points. Using 30 cm and 1 m resolution images, we classified land cover at each point, with any point touching a woody plant higher than 5 m classified as tree crown. We found a net increase in tree crown cover equiva-lent to 5.0 ± 2.3% (95% confidence interval) of Haiti’s land area. Gross gains and losses amounted to 9.0 ± 2.1% and 4.0 ± 1.3% of the territory, respectively. These results challenge, for the first time with empirical evidence, the predominant narrative that portrays Haiti as experiencing ongoing forest or tree cover loss. The net gain in tree cover quantified here represents a 35% increase from 2002 to 2010. Further research is needed to determine the drivers of this substantial net gain in tree cover at the national scale

Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite imagery and other ancillary spatial data. Different analysts interpreting the same spatial unit will not always agree on the land cover class label that should be assigned. Two approaches for accommodating interpreter variability when estimating the area are simple averaging (SA) and latent class modeling (LCM). This study compares agreement between area estimates obtained from SA and LCM using reference data obtained by seven trained, professional interpreters who independently interpreted an annual time series of land cover reference class labels for 300 sampled Landsat pixels. We also compare the variability of the LCM and SA area estimates over different numbers of interpreters and different subsets of interpreters within each interpreter group size, and examine area estimates of three land cover classes (forest, developed, and wetland) and three change types (forest gain, forest loss, and developed gain). Differences between the area estimates obtained from SA and LCM are most pronounced for the estimates of wetland and the three change types. The percent area estimates of these rare classes were usually greater for LCM compared to SA, with the differences between LCM and SA increasing as the number of interpreters providing the reference data increased. The LCM area estimates generally had larger standard deviations and greater ranges over different subsets of interpreters, indicating greater sensitivity to the selection of the individual interpreters who carried out the reference class labeling

Contrasting tree-cover loss and subsequent land cover in two neotropical forest regions: sample-based assessment of the Mexican Yucatán and Argentine Chaco

The neotropical-forest’s northern and southern extremes, covering the Mexican Yucatán and the Argentine Chaco, have among the highest rates of recent tree-cover loss in the biome. This study contrasts the character of loss in these regions, estimating proportions of types of loss and subsequent land cover. It is based on two-stage probability sampling design and field and satellite-image surveys. All estimates include uncertainties, which could be further reduced via model-assisted estimation or additional sampling. This approach can be replicated in other regions to estimate types of loss and associated land cover from a definitive, in-situ perspective. The character of loss in the two areas differed greatly. That in the Yucatán was 54% temporary, mostly under fallow or selectively logged, while that in the Chaco was 85% permanent, split nearly equally between crops and pasture. These data contribute to a quantitative basis for studies of socio-economic drivers of neotropical deforestation.Fil: Krylov, Alexander. University of Maryland; Estados UnidosFil: Steininger, Marc K.. University of Maryland; Estados UnidosFil: Hansen, Matthew C.. University of Maryland; Estados UnidosFil: Potapov, Peter V.. University of Maryland; Estados UnidosFil: Stehman, Stephen V.. State University of New York; Estados UnidosFil: Gost, Allison. University of Maryland; Estados UnidosFil: Noel, Jacob. University of Maryland; Estados UnidosFil: Talero Ramirez, Yamile. University of Maryland; Estados UnidosFil: Tyukavina, Alexandra. University of Maryland; Estados UnidosFil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ellis, Edward A.. Universidad Veracruzana; MéxicoFil: Ellis, Peter. The Nature Conservancy. Global Lands; Estados Unido

Global Trends of Forest Loss Due to Fire From 2001 to 2019

Forest fires contribute to global greenhouse gas emissions and can negatively affect public health, economic activity, and provision of ecosystem services. In boreal forests, fires are a part of the ecosystem dynamics, while in the humid tropics, fires are largely human-induced and lead to forest degradation. Studies have shown changing fire dynamics across the globe due to both climate and land use change. However, global trends in fire-related forest loss remain uncertain due to the lack of a globally consistent methodology applied to high spatial resolution data. Here, we create the first global 30-m resolution satellite-based map of annual forest loss due to fire. When producing this map, we match the mapped area of forest loss due to fire to the reference area obtained using a sample-based unbiased estimator, thus enabling map-based area reporting and trend analysis. We find an increasing global trend in forest loss due to fire from 2001 to 2019, driven by near-uniform increases across the tropics, subtropical, and temperate Australia, and boreal Eurasia. The results quantify the increasing threat of fires to remaining forests globally and may improve modeling of future forest fire loss rates under various climate change and development scenarios