Analysis of the Habitat Associations of a Hypothetical Beetle Species

2021 ◽  
pp. 117-134
Author(s):  
Joseph A. Veech
Keyword(s):  
Woody Debris ◽  
Canopy Cover ◽  
Habitat Associations ◽  
Beetle Species ◽  
Habitat Analysis ◽  
Oak Trees ◽  
Environmental Predictor ◽  
Components Analysis ◽  
Classification And Regression ◽  
Study Sites

A dataset for a hypothetical ground-dwelling beetle species is used to illustrate five methods of habitat analysis: (1) comparison of group means, (2) multiple linear regression, (3) multiple logistic regression, (4) classification and regression trees, and (5) principal components analysis. The dataset consists of abundance (counts of individuals) recorded in each of 100 small survey plots located throughout forested study sites. The following environmental predictor variables were measured in each plot: percentage canopy cover, depth of leaf litter, volume of woody debris, ratio of oak to non-oak trees, and soil type. Techniques for assessing normality of each variable and multicollinearity among variables are discussed and recommended prior to conducting the habitat analysis. Assumptions, strengths, and weaknesses of each method are discussed.

scholarly journals Habitat relationships of reptiles in pine beetle disturbed forests of Alabama, U.S.A. with guidelines for a modified drift-fence sampling method

2010 ◽  
Vol 56 (4) ◽  
pp. 411-420 ◽  
Author(s):  
W. B. Sutton ◽  
Y. Wang ◽  
C. J. Schweitzer
Keyword(s):  
Coarse Woody Debris ◽  
Woody Debris ◽  
Management Strategies ◽  
Canopy Cover ◽  
Habitat Associations ◽  
Dendroctonus Frontalis ◽  
Litter Depth ◽  
Drift Fence ◽  
Habitat Gradient ◽  
Pine Beetle

Abstract Understanding vertebrate habitat relationships is important to promote management strategies for the longterm conservation of many species. Using a modified drift fence method, we sampled reptiles and compared habitat variables within the William B. Bankhead National Forest (BNF) in Alabama, U.S.A from April 2005 to June 2006. We captured 226 individual reptiles representing 19 species during 564 total trap nights. We used canonical correspondence analysis to examine habitat associations for the reptiles sampled and we detected a distinct habitat gradient ranging from sites with greater litter depth and percent canopy cover to more open sites with greater woody, herbaceous, and coarse woody debris (CWD) coverage, and CWD volume. Little brown skinks Scincella lateralis and eastern worm snakes Carphophis a. amoenus were associated with sites with greater litter depth and canopy cover, whereas eastern fence lizards Sceloporus undulatus, copperheads Agkistrodon contortrix, and gray ratsnakes Pantherophis spiloides were associated with sites possessing greater CWD coverage and volume. We found that disturbances due to the southern pine beetle Dendroctonus frontalis were likely important for influencing reptile distributions through the creation of canopy gaps and fallen coarse woody debris. Compared to other studies, our modified drift-fence trap technique was successful for sampling larger snake species (66 snakes in 564 trap nights). We have also provided detailed schematics for constructing drift fence array and box traps used in this study.

Types of Data and the General Framework of Analysis

2021 ◽  
pp. 83-88
Author(s):  
Joseph A. Veech
Keyword(s):  
Statistical Tests ◽  
Spatial Scales ◽  
Activity Level ◽  
Environmental Data ◽  
Habitat Characteristics ◽  
Predictor Variables ◽  
Response Variable ◽  
Habitat Analysis ◽  
Environmental Predictor ◽  
Study Sites

For most habitat analyses, researchers typically collect and examine environmental data from the landscape scale (a few square kilometers to hundreds of square kilometers) all the way down to the scale of a microhabitat (tens of square meters). At the larger spatial extents, the data may be GIS-based such as spatially referenced land cover data. At smaller spatial scales, the data may be collected (variables measured) in the field at the study sites. Data for a habitat analysis are often based on randomly located and spatially delineated sampling or survey plots. The environmental data compose a set of a few to tens of predictor variables that are used in statistical tests for a relationship with the response variable that is typically species presence–absence, abundance (counts of individuals), or activity level. Depending on the spatial scale of analysis, predictor variables could represent different environmental variables such as vegetation structure, soil properties, and other characteristics of the substrate. Climate and weather variables are environmental, but they are not considered to be characteristics of the habitat. The formal habitat analysis consists of testing for a statistical relationship between the response variable and one or more environmental predictor variables so as to identify those variables that truly are habitat characteristics. A study of the habitat of the brown-throated sloth in Costa Rica is used to further explain the type of data used in characterizing the habitat of a species.

Statistical Methods for Analyzing Species–Habitat Associations

2021 ◽  
pp. 135-174
Author(s):  
Joseph A. Veech
Keyword(s):  
Negative Binomial ◽  
Function Analysis ◽  
Historical Context ◽  
Likelihood Estimation ◽  
Habitat Associations ◽  
Multivariate Techniques ◽  
Multiple Logistic Regression ◽  
Linear Modeling ◽  
Components Analysis ◽  
Classification And Regression

Six methods for statistically identifying and quantifying meaningful species–habitat associations are discussed. These are (1) comparison among group means (e.g. ANOVA), (2) multiple linear regression, (3) multiple logistic regression, (4) classification and regression trees, (5) multivariate techniques (principal components analysis and discriminant function analysis), and (6) occupancy modeling. Each method is described in statistical detail and associated terminology is explained. The example of habitat associations of a hypothetical beetle species (from Chapter 8) is used to further explain some of the methods. Assumption, strengths, and weaknesses of each method are discussed. Related statistical constructs and procedures such as the variance–covariance matrix, negative binomial distribution, generalized linear modeling, maximum likelihood estimation, and Bayes’ theorem are also explained. Some historical context is provided for some of the methods.

scholarly journals Habitat associations and conservation status of an endemic forest dwarf chameleon (Bradypodion sp.) from South Africa

Oryx ◽  
2006 ◽  
Vol 40 (2) ◽  
pp. 183-188 ◽  
Author(s):  
Walter J. Reisinger ◽  
Devi M. Stuart-Fox ◽  
Barend F.N. Erasmus
Keyword(s):  
South Africa ◽  
Conservation Status ◽  
Canopy Cover ◽  
Iucn Red List ◽  
Habitat Associations ◽  
Suitable Habitat ◽  
Area Of Occupancy ◽  
Forest Interior ◽  
Forest Remnants ◽  
Iucn Red List Criteria

We quantified habitat associations and evaluated the conservation status of a recently identified, undescribed species of dwarf chameleon, Bradypodion sp. nov. Dhlinza, endemic to scarp forest remnants in KwaZulu-Natal Province, South Africa. At the microhabitat scale the Dhlinza dwarf chameleon was found more often in forest gaps and near paths than highly disturbed edges or forest interior. Chameleon presence was not explained by forest physiognomic variables such as vine cover, shrub and tree density, or canopy cover. Presence near gaps may be better explained by the combined effects of the thermal microenvironment and food availability. The species is moderately common where it occurs, with estimated densities of 4.7, 8.7 and 29.7 individuals per ha within forest interior, edges and gaps respectively. At the landscape scale, the chameleon occurs only in three remnant forests: the Dhlinza, Entumeni and Ongoye Forests. The species' extent of occurrence was estimated to be 88 km2 and its area of occupancy 49 km2. Based on the small area of remaining suitable habitat, this species meets the requirements for categorization as Endangered according to IUCN Red List criteria.

Design and Statistical Issues Related to Habitat Analysis

2021 ◽  
pp. 95-116
Author(s):  
Joseph A. Veech
Keyword(s):  
Count Data ◽  
Detection Probability ◽  
Spatial Dispersion ◽  
Species Traits ◽  
Habitat Associations ◽  
Statistical Techniques ◽  
Focal Species ◽  
Habitat Analysis ◽  
Background Density ◽  
Statistical Issues

There are many different design and statistical issues that a researcher should consider when developing the data collection protocol or when interpreting results from a habitat analysis. One of the first considerations is simply the area to include in the study. This depends on the behavior (particularly mobility) of the focal species and logistical constraints. The amount of area also relates to the number of survey locations (plots, transects, or other) and their spatial placement. Survey data often include many instances of a species absent from a spatial sampling unit. These could be true absences or might represent very low species detection probability. There are different statistical techniques for estimating detection probability as well as analyzing data with a substantial proportion of zero-abundance values. The spatial dispersion of the species within the overall study area or region is never random. Even apart from the effect of habitat, individuals are often aggregated due to various environmental factors or species traits. This can affect count data collected from survey plots. Related to spatial dispersion, the overall background density of the species within the study area can introduce particular challenges in identifying meaningful habitat associations. Statistical issues such as normality, multicollinearity, spatial and temporal autocorrelation may be relatively common and need to be addressed prior to an analysis. None of these design and statistical issues presents insurmountable challenges to a habitat analysis.

scholarly journals Examination of the Arborsonic Decay Detector for Detecting Bacterial Wetwood in Red Oaks

2000 ◽  
Vol 24 (1) ◽  
pp. 6-10 ◽  
Author(s):  
Zical Xu ◽  
Theodor D. Leininger ◽  
James G. Williams ◽  
Frank H. Tainter
Keyword(s):  
South Carolina ◽  
Signal Amplitude ◽  
Red Oak ◽  
Ultrasound Wave ◽  
Limited Ability ◽  
Red Oaks ◽  
Oak Trees ◽  
Study Sites ◽  
Linear Regressions ◽  
Land Manager

Abstract The Arborsonic Decay Detector (ADD; Fujikura Europe Limited, Wiltshire, England) was used to measure the time it took an ultrasound wave to cross 280 diameters in red oak trees with varying degrees of bacterial wetwood or heartwood decay. Linear regressions derived from the ADD readings of trees in Mississippi and South Carolina with wetwood and heartwood decay yielded significantly different lines for some combinations and locations. The results of this study suggest that the ADD cannot yet be used to detect wetwood in oak trees with enough certainty to be of practical use to a forester or land manager. However, regression lines describing ADD readings of trees with wetwood at both study sites were located between those of healthy trees and decayed trees suggesting some, albeit limited, ability to differentiate wetwood trees. The use of ultrasound to detect bacterial wetwood in red oaks may be improved by designing a system that allows measurement of signal amplitude and evaluation of waveform patterns. The ability to successfully detect trees with heartwood decay was better, especially for trees with advanced decay. South. J. Appl. For. 24(1):6-10.

Influence of habitat and microhabitat on carabid (Coleoptera: Carabidae) assemblages in four stand types

2003 ◽  
Vol 135 (3) ◽  
pp. 337-357 ◽  
Author(s):  
J.L. Pearce ◽  
L.A. Venier ◽  
J. McKee ◽  
J. Pedlar ◽  
D. McKenney
Keyword(s):  
Coarse Woody Debris ◽  
Woody Debris ◽  
Habitat Associations ◽  
Litter Layer ◽  
Forest Types ◽  
Disturbed Habitat ◽  
Northwestern Ontario ◽  
Spruce Stands ◽  
Insight Into ◽  
Important Habitat

AbstractStudies based on presence/absence of a species may provide insight into habitat associations, allowing the distribution of species to be predicted across the landscape. Our objective was to characterize the carabid fauna in three mature boreal forest types (conifer, mixedwood, and deciduous) and a disturbed habitat (clearcut) to provide baseline data on the carabid species inhabiting the major forest types of boreal northwestern Ontario. Only spring-active carabids were considered for logistical reasons. We further identified the coarse woody debris structure and microhabitat characteristics within these stand types to try to refine our ability to predict the within-stand occurrence of carabids. We found the carabid composition of deciduous stands (mixedwood and aspen) similar and typical of the carabid fauna found in mixedwood forest in other nearby studies. The important feature of these forest types may be the presence of a deciduous leaf litter layer. In contrast, spruce stands contained fewer species and individuals and a distinct carabid fauna. As predicted, the clearcut habitats were dominated by open habitat species, although the fauna was dissimilar to what was recorded in clearcut habitats in other studies within northwestern Ontario. Coarse woody debris appeared to be an important habitat attribute for several carabid species in clearcut habitats.

Predicting the occurrence of an endangered reptile based on habitat attributes

2018 ◽  
Vol 24 (1) ◽  
pp. 12 ◽  
Author(s):  
Sarsha Gorissen ◽  
Ian R. C. Baird ◽  
Matthew Greenlees ◽  
Ahamad N. Sherieff ◽  
Richard Shine
Keyword(s):  
Soil Moisture ◽  
Surface Water ◽  
Gravid Female ◽  
Canopy Cover ◽  
Habitat Associations ◽  
Adult Males ◽  
Habitat Features ◽  
Blue Mountains ◽  
Digital Elevation ◽  
Dead Vegetation

The endangered Blue Mountains water skink (Eulamprus leuraensis), a habitat specialist known from approximately 60 threatened highland peat swamps, is the sole endemic vertebrate of the Blue Mountains region, Australia. We quantified the species’ habitat associations by surveying 10 such swamps annually for three years. We scored habitat features and trapped skinks, comparing habitat attributes of trap sites where skinks were and were not captured. The distribution of E. leuraensis was non-random: skinks were found at sites with high values for some variables (soil moisture, live vegetation, surface water, understorey density and numbers of burrows) and low values for others (dead vegetation, logs, rocks, bare ground, canopy cover, sunlight penetration and numbers of invertebrates), and were mostly found in sites that were close to surface water and far from trees and logs. Eulamprus leuraensis is widely distributed within swamps, with weak associations between microhabitat variation and skink presence. Skink abundance and mean body size were highest within swamp centres, decreasing towards the margins; larger skinks were found closer to water, gravid female skinks were found at wetter sites and juveniles occupied marginal habitat. Skinks were rarely recaptured >10 m from their original site, with adult males travelling further than adult females and juveniles. We developed a quick field detection method for managers to assess the likely presence of E. leuraensis using two habitat attributes (soil moisture and burrow abundance). We mapped the species’ known and predicted habitat using GIS spatial layers, including locality records, associated vegetation communities and digital elevation models.

Do bare-nosed wombat (Vombatus ursinus) mounds influence terrestrial macroinvertebrate assemblages in agricultural riparian zones?

2009 ◽  
Vol 57 (5) ◽  
pp. 329 ◽  
Author(s):  
Philip Borchard ◽  
Ian A. Wright ◽  
Clare McArthur
Keyword(s):  
Canopy Cover ◽  
Soil Surface ◽  
Macroinvertebrate Communities ◽  
Riparian Ecosystems ◽  
Macroinvertebrate Assemblages ◽  
Ecological Variability ◽  
Eastern Australia ◽  
Surrounding Landscape ◽  
Study Sites

Riparian ecosystems contain a complex mosaic of habitat structure types that can support distinct macroinvertebrate communities. Bare-nosed wombats (Vombatus ursinus) are often an integral component of agricultural riparian systems in south-eastern Australia. In these systems, wombats construct large burrow systems and mounds in the stream banks. Wombat mound structures vary markedly from the surrounding landscape and they may influence macroinvertebrate assemblages. We examined this ecosystem-engineering role of wombats as well as the ecological variability within our agricultural riparian study sites on the possible influence on macroinvertebrate assemblages. There were no detectable effects of wombat mounds on the richness or abundance of macroinvertebrates on the soil surface. At the site level, however, macroinvertebrate assemblages were most influenced by litter depth, upper canopy cover, cattle hoof prints and slope. The ecological variables within the study sites strongly affected macroinvertebrate assemblages. These findings reflect an influence of anthropogenic impact on communities of ground-dwelling invertebrates that have been found in other studies. It is possible that a finer resolution of taxa may highlight a unique pattern of macroinvertebrate use of wombat mounds.

scholarly journals Three Colopterus Beetle Species Carry the Oak Wilt Fungus to Fresh Wounds on Red Oak in Missouri

Plant Disease ◽  
2008 ◽  
Vol 92 (2) ◽  
pp. 270-275 ◽  
Author(s):  
Maya Hayslett ◽  
Jennifer Juzwik ◽  
Bruce Moltzan
Keyword(s):  
Abundant Species ◽  
Pathogen Transmission ◽  
Red Oak ◽  
Beetle Species ◽  
Vector Species ◽  
Oak Wilt ◽  
Ceratocystis Fagacearum ◽  
Oak Trees ◽  
The Family ◽  
Nitidulid Beetles

Beetles in the family Nitidulidae can transmit the oak wilt fungus, Ceratocystis fagacearum, to fresh wounds on healthy oak trees, leading to infection and disease development. Historically, nitidulid beetles have not been considered important vectors of the pathogen in Missouri. Studies were conducted in the spring of 2005 and 2006 to determine frequencies of nitidulid beetle species contaminated with C. fagacearum visiting fresh wounds on red oak trees in central Missouri. Colopterus truncatus, C. niger, and C. semitectus were the most abundant species collected from fresh wounds and the only species found to be contaminated with Ceratocystis fagacearum. Of 230 beetles assayed for C. fagacearum, 23 yielded the fungus. Contamination frequencies were higher for beetles collected in April than May; no beetles collected in June were contaminated. We hypothesize that Colopterus truncatus, C. niger, and C. semitectus are principal nitidulid beetle vector species in Missouri during spring. The risk for pathogen transmission by these beetles appears to be greatest in April and least in June.

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