Books on the topic 'Habitat selection analysis'

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1

Manly, Bryan F. J., 1944- and Manly, Bryan F. J., 1944-, eds. Resource selection by animals: Statistical design and analysis for field studies. 2nd ed. Dordrecht: Kluwer Academic Publishers, 2002.

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2

L, McDonald Lyman, and Thomas Dana L, eds. Resource selection by animals: Statistical design and analysis for field studies. London: Chapman & Hall, 1993.

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3

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : social analysis. [Toronto]: Ontario Waste Management Corporation, 1985.

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4

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : social analysis appendices. [Toronto]: Ontario Waste Management Corporation, 1985.

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5

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : economic base analysis. Toronto: Ontario Waste Management Corporation, 1985.

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6

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : municipal finance and services analysis. [Toronto]: Ontario Waste Management Corporation, 1985.

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7

Corporation, Ontario Waste Management. Site selection process: Phase 4A : selection of a preferred site(s) : site selection. Toronto: M.M. Dillon, 1986.

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8

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : transportation. [Toronto, Ont.]: Ontario Waste Management Corporation, 1985.

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9

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site : land use. [Toronto]: Ontario Waste Management Corporation, 1985.

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10

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : atmospheric considerations. [Toronto]: Ontario Waste Management Corporation, 1985.

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11

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : surface water. [Toronto]: Ontario Waste Management Corporation, 1985.

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12

Corporation, Ontario Waste Management. Site selection process: Phase 4A: selection of a preferred site(s) : generic risk assessment. [Toronto]: OWMC, 1985.

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13

Henderson, R. E. The Lower Clark Fork elk study: Final report 1985-1990 : the social structure and seasonal habitat selection of a northwest Montana elk population with an analysis of population characteristics, harvest rates, and survey techniques. Helena, Mont: Montana Dept. of Fish, Wildlife and Parks, 1993.

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14

Corporation, Ontario Waste Management. Site selection process: Phase 4A: technical appendix - existing biological conditions. [Toronto]: Ontario Waste Management Corporation, 1985.

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15

Veech, Joseph A. Habitat Ecology and Analysis. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198829287.001.0001.

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Habitat is crucial to the survival and reproduction of individual organisms as well as persistence of populations. As such, species-habitat relationships have long been studied, particularly in the field of wildlife ecology and to a lesser extent in the more encompassing discipline of ecology. The habitat requirements of a species largely determine its spatial distribution and abundance in nature. One way to recognize and appreciate the over-riding importance of habitat is to consider that a young organism must find and settle into the appropriate type of habitat as one of the first challenges of life. This process can be cast in a probabilistic framework and used to better understand the mechanisms behind habitat preferences and selection. There are at least six distinctly different statistical approaches to conducting a habitat analysis – that is, identifying and quantifying the environmental variables that a species most strongly associates with. 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 modelling. Each of these is lucidly explained and demonstrated by application to a hypothetical dataset. The strengths and weaknesses of each method are discussed. Given the ongoing biodiversity crisis largely caused by habitat destruction, there is a crucial and general need to better characterize and understand the habitat requirements of many different species, particularly those that are threatened and endangered.
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16

Wetzstein, Lia Joy. A demographic analysis of Peromyscus maniculatus populations in clear-cuts and forest stands: Are clear-cuts habitat sinks? 1993.

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17

Manly, B. F., L. McDonald, D. L. Thomas, Trent L. McDonald, and Wallace P. Erickson. Resource Selection by Animals: Statistical Design and Analysis for Field Studies. 2nd ed. Springer, 2002.

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18

Lofdahl, Katharine L. A quantitative genetic analysis of habitat selection behavior in the cactus-breeding species Drosophila mojavensis. 1985.

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19

Manly, Bryan F. J. Resource Selection by Animals: Statistical Design and Analysis for Field Studies. Manly B F McDonald L Thomas D L, 2010.

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20

Fogarty, Michael J., and Jeremy S. Collie. Fishery Ecosystem Dynamics. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198768937.001.0001.

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This book provides an integrated framework for the quantitative analysis of exploited aquatic ecosystems, tracing the critical linkages between fundamental ecological processes and their implications for sustainable resource management. Examples are drawn from freshwater and marine ecosystems throughout the world. Fishery ecosystems have historically been subject to a broad array of human interventions, ranging from large-scale removal of biomass to deliberate attempts at ecosystem engineering involving species introductions, habitat alteration, and selective reorganization of ecosystem structure. Traditional approaches to fisheries analysis and management focus on extraction of resources viewed in isolation from the broader ecosystem setting. Further, these approaches typically are predicated on assumptions of “well-behaved” dynamical properties characterized by stable equilibrium properties. This book explores a broader range of possibilities concerning human impacts on aquatic ecosystems. It places software tools in the hands of students and professionals in an electronic supplement. Modeling and statistical programs in R and other platforms are provided to assist in the transition from concept to practical application.
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21

Polis, Stéphane. The Scribal Repertoire of Amennakhte Son of Ipuy. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198768104.003.0005.

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This chapter investigates linguistic variation in the texts written by the Deir el-Medina scribe Amennakhte son of Ipuy in New Kingdom Egypt (Twentieth Dynasty; c. 1150 BCE). After a discussion of the challenge posed by the identification of scribes and authors in this sociocultural setting, I provide an overview of the corpus of texts that can tentatively be linked to this individual and justify the selection that has been made for the present study. The core of this paper is then devoted to a multidimensional analysis of Amennakhte’s linguistic registers. By combining the results of this section with a description of Amennakhte’s scribal habits—both at the graphemo-morphological and constructional levels—I test the possibility of using ‘idiolectal’ features to identify the scribe (or the author) of other texts stemming from the community of Deir el-Medina and closely related to Amennakhte.
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22

Wajdzik, Marek. Zmienność cech fenotypowych samców sarny europejskiej (Capreolus capreolus L.) na tle gospodarowania jej populacją w północno-zachodniej Małopolsce. Publishing House of the University of Agriculture in Krakow, 2019. http://dx.doi.org/10.15576/978-83-66602-45-8.

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The objective of the present work was to evaluate the individual quality of male European roe deer by statistical analysis of antler traits, craniometric characters, and age of hunter-harvested bucks. Those measurements enabled a reliable assessment of antler quality, changes in carcass weight with age and between hunting seasons, as well as phenotypic traits depending on habitat (percentage forest cover, geographic mesoregion). The work also aimed to assess the effectiveness of deer population management in the Cracow Region of the Polish Hunting Association and determine the potential of that population based on analysis of medal-quality roebucks harvested there over the past 10 years. The study involved data concerning roe deer in the 60 hunting districts comprising the Cracow Region for the 2008/2009-2017/2018 hunting seasons. The study material consisted of data concerning antlers from 8132 roebucks taken over that decade, such as the age of hunted roebucks, hunting district, hunt date, carcass weight, as well as the gross weight and form of antlers. A detailed evaluation of antler quality was conducted using records for 2874 individuals, including 284 medal-quality antlers, harvested in the 2014/2015-2016/2017 seasons. The trophies were evaluated in accordance with the criteria of the International Council for Game and Wildlife Conservation (CIC) and were subjected to craniometric analysis. For a comprehensive examination of roe deer quality in the Cracow Region, the study analyzed gamekeeping data, that is, annual hunting plans of the Polish Hunting Association, for the period 2008/2009-2017/2018. Several gamekeeping indicators were calculated based on those data to evaluate the effects of roe deer management and gamekeeping practices. The studied antler traits (mean beam length, antler weight and volume, CIC scores) as well as carcass weight culminated in 6-year-old individuals. In turn cra-niometric traits (skull length and width) increased significantly until the 4th year of life, while the width of pedicles increased throughout the life of the individual. The development of antlers over time was characterized by a declining rate of growth for all the analyzed parameters. The highest growth rate (more than 100%) was found between the second and third years of life in terms of antler weight and volume, as well as front tine length. Antler quality in terms of overall CIC scores was to the greatest extent affected by weight and volume. The combined contribution of these factors increased with age, and ranged from 63.9% in the youngest individuals to 74.6% in the oldest ones. Within the study area, the individual quality of roe deer varied depending on the forest cover and mesoregion. Roebucks with the lowest carcass and antler weight occurred in hunting districts with a forest cover exceeding 40%, while the highest values of those parameters were found in districts with 5% forest cover or less. In open-land areas, the share of medal-quality roebucks in the total number of harvested males was higher, at approx. 5%, as compared to 1.29% in the woodlands. The carcass and antler weight of roebucks taken in the Cracow Region was higher than that of roebucks harvested in western Poland, similar to the Kielce Region, and lower than that for the Lublin and Krosno Regions, which is in keeping with Bergmann's ecogeographical rule. Analysis of carcass weight throughout the hunting season showed that the most pronounced rutting activity was observed for individuals 6 years of age and older, which lost as much as 6% of their weight. Over the ten-year period of study, the roebucks harvested using a uniform set of selection criteria revealed an increase in mean carcass weight as well as antler weight and form, which indicates appropriate management of the roe deer population in the examined hunting region.
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