scholarly journals Assessment of Rusty Blackbird Habitat Occupancy in the Long Range Mountains of Newfoundland, Canada Using Forest Inventory Data

Diversity ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 340
Author(s):  
Kathleen K. E. Manson ◽  
Jenna P. B. McDermott ◽  
Luke L. Powell ◽  
Darroch M. Whitaker ◽  
Ian G. Warkentin
Keyword(s):  
Future Research ◽  
Breeding Ecology ◽  
Forest Resource ◽  
Population Declines ◽  
Inventory Data ◽  
Red Squirrels ◽  
Habitat Occupancy ◽  
Resource Inventory ◽  
Forest Resource Inventory ◽  
Rusty Blackbird

Rusty blackbirds (Euphagus carolinus), once common across their boreal breeding distribution, have undergone steep, range-wide population declines. Newfoundland is home to what has been described as one of just two known subspecies (E. c. nigrans) and hosts some of the highest known densities of the species across its extensive breeding range. To contribute to a growing body of literature examining rusty blackbird breeding ecology, we studied habitat occupancy in Western Newfoundland. We conducted 1960 point counts across a systematic survey grid during the 2016 and 2017 breeding seasons, and modeled blackbird occupancy using forest resource inventory data. We also assessed the relationship between the presence of introduced red squirrels (Tamiasciurus hudsonicus), an avian nest predator, and blackbird occupancy. We evaluated 31 a priori models of blackbird probability of occurrence. Consistent with existing literature, the best predictors of blackbird occupancy were lakes and ponds, streams, rivers, and bogs. Red squirrels did not appear to have a strong influence on blackbird habitat occupancy. We are among the first to model rusty blackbird habitat occupancy using remotely-sensed landcover data; given the widespread availability of forest resource inventory data, this approach may be useful in conservation efforts for this and other rare but widespread boreal species. Given that Newfoundland may be a geographic stronghold for rusty blackbirds, future research should focus on this distinct population.

scholarly journals Forest Site and Type Variability in ALS-Based Forest Resource Inventory Attribute Predictions over Three Ontario Forest Sites

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 226 ◽  
Author(s):  
Karin van Ewijk ◽  
Paul Treitz ◽  
Murray Woods ◽  
Trevor Jones ◽  
John Caspersen
Keyword(s):  
Prediction Accuracy ◽  
Forest Type ◽  
Stem Density ◽  
Forest Site ◽  
Forest Resource ◽  
Forest Types ◽  
Resource Inventory ◽  
Forest Resource Inventory ◽  
Forest Attributes ◽  
The Impact

Over the last decade, spatially-explicit modeling of landscape-scale forest attributes for forest inventories has greatly benefitted from airborne laser scanning (ALS) and the area-based approach (ABA) to derive wall-to-wall maps of these forest attributes. Which ALS-derived metrics to include when modeling forest inventory attributes, and how prediction accuracies vary over forest types depends largely on the structural complexity of the forest(s) being studied. Hence, the purpose of this study was to (i) examine the usefulness of adding texture and intensity metrics to height-based ALS metrics for the prediction of several forest resource inventory (FRI) attributes in one boreal and two Great Lakes, St. Lawrence (GLSL) forest region sites in Ontario and (ii) quantify and compare the site and forest type variability within the context of the FRI prediction accuracies. Basal area (BA), quadratic mean diameter-at-breast height (QMD), and stem density (S) were predicted using the ABA and a nonparametric Random Forests (RF) regression model. At the site level, prediction accuracies (i.e., expressed as RMSE (Root Mean Square Error), bias, and R2) improved at the three sites when texture and intensity metrics were included in the predictor set, even though no significant differences (p > 0.05) could be detected using the nonparametric RMANOVA test. Stem density benefitted the most from the inclusion of texture and intensity, particularly in the GLSL sites (% RMSE improved up to 6%). Combining site and forest type results indicated that improvements in site level predictions, due to the addition of texture and intensity metrics to the ALS predictor set, were the result of changes in prediction accuracy in some but not all forest types present at a site and that these changes in prediction accuracy were site and FRI attribute specific. The nonparametric Kruskal–Wallis test indicated that prediction errors between the different forest types were significantly different (p ≤ 0.01). In the boreal site, prediction accuracies for conifer forest types were higher than for deciduous and mixedwoods. Such patterns in prediction accuracy among forest types and FRI attributes could not be observed in the GLSL sites. In the Petawawa Research Forest (PRF), we did detect the impact of silvicultural treatments especially on QMD and S predictions.

scholarly journals A comparison of forest resource inventory, provincial land cover maps and field surveys for wildlife habitat analysis in the Great Lakes – St. Lawrence forest

2010 ◽  
Vol 86 (1) ◽  
pp. 77-86 ◽  
Author(s):  
Andrea J. Maxie ◽  
Karen F. Hussey ◽  
Stacey J. Lowe ◽  
Kevin R. Middel ◽  
Bruce A. Pond ◽  
...  
Keyword(s):  
Land Cover ◽  
Forest Cover ◽  
Satellite Image ◽  
Wildlife Habitat ◽  
Forest Resource ◽  
Habitat Analysis ◽  
Resource Inventory ◽  
Forest Resource Inventory ◽  
Land Cover Maps ◽  
Forest Cover Types

In a portion of central Ontario, Canada we assessed the classification agreement between field-based estimates of forest stand composition and each of two mapped data sources used in wildlife habitat studies, the Forest Resource Inventory (FRI) and satellite-image derived Provincial Land Cover (PLC). At two study areas, Algonquin Provincial Park (APP) and Wildlife Management Unit 49 (WMU49), we surveyed 119 forest stands and 40 water and wetland stands. Correspondence levels between FRI and field classifications were 48% in APP and 44% in WMU49 when assessing six forest cover types. With only four simplified forest cover types, levels improved to 77% in APP and 63% in WMU49. Correspondence between PLC and field classifications for three forested stand types was approximately 63% in APP and 55% in WMU49. Because of the poor to moderate level of correspondence we detected between map and field classifications, we recommend that care be exercised when FRI or PLC maps are used in forest and wildlife research and management planning. Key words: forest resource inventory, FRI, provincial land cover, PLC, Landsat Thematic Mapper, map accuracy, map correspondence, map agreement, Ontario, wildlife habitat

A gap analysis of tree species representation in the protected areas of the Canadian boreal forest: applying a new assemblage of digital Forest Resource Inventory data

2015 ◽  
Vol 45 (2) ◽  
pp. 163-173 ◽  
Author(s):  
Steven G. Cumming ◽  
C. Ronnie Drever ◽  
Mélina Houle ◽  
John Cosco ◽  
Pierre Racine ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Protected Areas ◽  
Tree Species ◽  
Rare Species ◽  
Gap Analysis ◽  
Forest Resource ◽  
Resource Inventory ◽  
Forest Resource Inventory ◽  
Boreal Shield ◽  
Canadian Boreal Forest

We undertook a gap analysis of how protected areas represent the tree-species diversity within the Canadian boreal forest, as measured from Forest Resource Inventory (FRI) maps. We used a new compilation of Forest Resource Inventory designed to support ecological analyses over large areas and across jurisdictional boundaries. The analysis was stratified into four analytical regions determined by terrestrial ecozones. We calculated the relative abundance of species within regions, developed rarity criteria, and evaluated the relative abundances and prevalence of rare species. We characterized representation gaps when the abundance of a tree species in protected areas within an analytical region differed markedly (by more than a factor of 2) from the expectation, calculated as the product of regional abundance and the proportional area protected. Most species were well represented in the most species-diverse region (n = 33), the Boreal Shield in eastern Canada, due apparently to a large number of relatively small protected areas in the southern part of the region. Some marked gaps existed in the more species-depauperate western zones, notably for montane conifers in the Boreal Plains. As is common for species abundance distributions, as few as five species accounted for 90% of total abundance in each zone. Relatively rare species were more numerous. Mostly associated with southern temperate or hemiboreal forests, these reached their highest prevalence and abundance in the managed forests of the Boreal Shield. Our work identified some gaps in representation in the protected areas network of Canada in western Canada, substantiates the use of species distribution mapping based on FRI data to inform conservation planning — including the identification of high conservation biodiversity elements for forest certification — and demonstrates the need for improved vegetation mapping in National Parks.

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