Breeding for worm resistance: a perspective

It has been well established that there is considerable genetic variability in resistance of domestic animals to nematode parasites. Utilization of this resource to reduce dependency on present parasite control methods will take place only if breeding for resistance is shown to be a profitable control strategy. Therefore, a cost/benefit analysis is needed, but most of the information required for that is still lacking.Resistance is a complex character and any selection criterion used in a selective breeding program can only cover part of all mechanisms involved. Moreover, one should take into consideration that it might be worthwhile to select animals for their capacity to overcome the pathogenic effects of infection rather than the infection itself.Selection criteria used in genetic experiments to date are too complicated to be practicable. There is a great need for simple and cheap procedures to identify genetically superior individuals. Genetic variability of resistance is large enough to allow a reasonable rate of progress to be obtained by practicable breeding programs. Furthermore, if major resistance genes could be identified, as is suggested by some work, a suitable breeding strategy would have an enormous impact.     

Carotenoid ornaments and the spandrels of physiology: a critique of theory to explain condition dependency

Even as numerous studies have documented that the red and yellow coloration resulting from the deposition of carotenoids serves as an honest signal of condition, the evolution of condition dependency is contentious. The resource trade-off hypothesis proposes that condition-dependent honest signalling relies on a trade-off of resources between ornamental display and body maintenance. By this model, condition dependency can evolve through selection for a re-allocation of resources to promote ornament expression. By contrast, the index hypothesis proposes that selection focuses mate choice on carotenoid coloration that is inherently condition dependent because production of such coloration is inexorably tied to vital cellular processes. These hypotheses for the origins of condition dependency make strongly contrasting and testable predictions about ornamental traits. To assess these two models, we review the mechanisms of production of carotenoids, patterns of condition dependency involving different classes of carotenoids, and patterns of behavioural responses to carotenoid coloration. We review evidence that traits can be condition dependent without the influence of sexual selection and that novel traits can show condition-dependent expression as soon as they appear in a population, without the possibility of sexual selection. We conclude by highlighting new opportunities for studying condition-dependent signalling made possible by genetic manipulation and expression of ornamental traits in synthetic biological systems.     

An efficient multivariate approach for estimating preference when individual observations are dependent

1. We discuss aspects of resource selection based on observing a given vector of resource variables for different individuals at discrete time steps. A new technique for estimating preference of habitat characteristics, applicable when there are multiple individual observations, is proposed. 2. We first show how to estimate preference on the population and individual level when only a single site- or resource component is observed. A variance component model based on normal scores in used to estimate mean preference for the population as well as the heterogeneity among individuals defined by the intra-class correlation. 3. Next, a general technique is proposed for time series of observations of a vector with several components, correcting for the effect of correlations between these. The preference of each single component is analyzed under the assumption of arbitrarily complex selection of the other components. This approach is based on the theory for conditional distributions in the multi-normal model. 4. The method is demonstrated using a data set of radio-tagged dispersing juvenile goshawks and their site characteristics, and can be used as a general tool in resource or habitat selection analysis.     

Using multilevel models to quantify heterogeneity in resource selection

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection. © 2011 The Wildlife Society.     

Application of random effects to the study of resource selection by animals

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.     

LANDSCAPE PROPORTIONS VERSUS MONTE CARLO SIMULATED HOME RANGES FOR ESTIMATING HABITAT AVAILABILITY

Abstract: Wildlife researchers often test whether animals use resources disproportionately relative to availability (i.e., selectively). However, the traditional estimate of availability at the landscape scale (resource proportions on the landscape) may be inaccurate and lead to false conclusions. We calculated the chance of falsely finding selection (type I error rate) when the traditional estimate of availability is used. True availability was estimated by Monte Carlo simulations with randomly located home ranges and compared to the traditional estimate to calculate type I error rates. Tests were conducted with α = 0.05 for different home-range sizes (1 to 1,000 km²) and 4 habitat patterns. Landscape proportions did not equal proportions of habitats in random home ranges (traditional estimate ≠ true availability). Type I error rates were ≥0.24 and increased with number of animals tested and decreased with home-range size and number of habitats. Therefore, researchers should use randomly located home ranges instead of landscape proportions to estimate availability at the landscape scale. We evaluated a goodness-of-fit test for comparing habitat proportions between randomly located home ranges and observed home ranges. Type I error rates for this method were ≤0.08, regardless of number of animals, home-range size, and number of habitats tested. We evaluated this method for 2 species with different home-range sizes and predicted habitat selection patterns: mountain lions (Puma concolor, ∼ 700 km², relatively nonselective) and mule deer (Odocoileus hemionus, ∼ 16 km², relatively selective). This method yielded results consistent with predictions, whereas the traditional method using landscape proportions to estimate availability did not. Randomly located, simulated home ranges are superior to landscape proportions for estimating availability.     

The attraction of the known: the importance of spatial familiarity in habitat selection in wapiti Cervus elaphus

Most studies of habitat selection by large herbivores focus on the resource availability and interactions with other species, but neglect the importance of an animal being familiar with an area due to past use. Yet, studies of the establishment and retention of territories, home ranges, birth sites, and feeding site choices in experimental settings have shown the importance of spatial familiarity at these scales. We used GPS locations of translocated wapiti Cervus elaphus , resource selection functions (RSF), and time-to-return to examine whether previous site use was important for selection of sites by wapiti in west-central Alberta. To construct RSFs, we used logistic regression that included spatial familiarity (presence of a previous GPS location within a 50-m radius) as well as estimates of herbaceous and shrub biomass, elevation, aspect, slope, and predation risk to wapiti from wolf predation, as dependent variables. We found that previous use had a strong positive relationship with subsequent site use, indicating that wapiti were not avoiding previously visited locations, as would be expected if memory of forage depletion (which we did not measure) determined response to familiar locations. Revisited sites were of higher quality, i.e. had more moderate terrain, higher forage, and lower predation risk, than sites that were not revisited, indicating that the selection of familiar locations was likely not the result of avoidance of unfamiliar locations. Finally, animals demonstrated preference for familiar locations that it had visited most recently, indicating that memory (which would decline with time) of higher site quality, rather than high quality alone, influenced selection for familiar locations. We conclude that spatial familiarity is important not only for large scale processes such as selection of home range and territory, but for smaller scale habitat selection and foraging as well.     

Competitive environments induce shifts in host fidelity

Recent models support the idea of sympatric speciation as a result of the joint effects of disruptive selection and assortative mating. We present experimental data, testing models of speciation through frequency‐dependent selection. We show that under high competition on a mixture of resources/hosts, strains of the Seed beetle, Callosobruchus maculatus, change their host fidelity and evolve a more generalistic behaviour in resource utilization among females. The change in host fidelity did not result in disruptive selection and was not followed by assortative mating. This means that only one of three fundamental prerequisites for sympatric speciation evolved as a result of the frequency‐dependent selection. We conclude that for this process to work, a shift to a novel food resource as a result of selection must also lead to a loss of preference for the original resource such that individuals are only able to use either one of the two.     

Are reward polymorphisms subject to frequency‐ and density‐dependent selection? Evidence from a monoecious species pollinated by deceit

Abstract Most deceit‐pollinated species involve floral dimorphisms characterized by the presence of rewarding male flowers and nonrewarding female flowers. It has been proposed that this polymorphism establishes the conditions for the action of frequency dependent selection (FDS). The tendency of foraging animals to aggregate in areas of high resource density suggests that pollination efficiency and fruit production may be positively influenced by flower density (density dependent selection, DDS). In this paper we offer a graphical model describing the effects of FDS and DDS on a monoecious species pollinated by deceit. We test the FDS and DDS assumptions and the predictions of the model using field observations and experimental populations of Begonia gracilis in which population sex ratio and flower density were controlled. We found a marked effect of both FDS and DDS on pollinator visitation, fruit‐set, and on the probability of female flowers to setting fruits. We conclude that these two types of selection have had a strong influence on the evolution of deceit‐pollinated species.     

Resource Selection by Translocated Three-Toed Box Turtles in Missouri

Abstract Resource selection is a multi-staged process of behavioral responses to various resource cues or stimuli. Previous research suggests some aspects of resource selection may be inherent (i.e., genetic predisposition) or based on early experience and that individuals respond to certain resource cues but not to others. In other words, resource selection may be based on a template that specifies which cues to use in the resource-selection process and the appropriate response to those cues. We used resource utilization functions (RUFs) to examine the resource-selection template of translocated three-toed box turtles (Terrapene carolina triunguis; hereafter turtles) and made comparisons to resident turtles. Translocated turtles, previously residents of a predominantly forested landscape with low edge-density, used forest openings, forest edges, and southwest-facing slopes before and after translocation to a fragmented site containing resident turtles. In contrast, resident turtles used forested areas and northeast-facing slopes within a predominantly open landscape with high edge-density. Our comparison of resource selection by translocated and resident turtles revealed population-specific resource selection and consistency in selection following translocation, which reinforces the idea of a resource-selection template and suggests that in the short-term box turtles may not adapt their predisposed behavior to local conditions. Thus, translocated animals may evaluate and respond to resource cues as if they were at the original site. Lack of site fidelity may result from individuals seeking additional resources to match their resource-selection template. Successful translocation of turtles may require an assessment of resource selection prior to translocation and development of management strategies that mitigate turtle response to translocation.     

At what spatial scales does resource selection vary? A case study of koalas in a semi‐arid region

The conservation of any species requires understanding and predicting the distribution of its habitat and resource use, including the effects of scale‐dependent variation in habitat and resource quality. Consequently, testing for resource selection at the appropriate scales is critical. We investigated how the resource selection process varies across scales, using koalas in a semi‐arid landscape of eastern Australia as a case study. We asked: at what scales does tree selection by koalas vary across regions? We tested the importance of the variation of our ecological predictors at the following scales: (i) the site‐scale (a stand of trees representing an individual koala's perception of local habitat); (ii) the landscape‐scale (10 × 10 km area representing a space within which a population of koalas exists); and (iii) a combination of these scales. We used a mixed‐modelling approach to quantify variation in selection of individual trees by koalas among sites and landscapes within a 1600 km² study area. We found that tree species, and tree height, were the most important factors influencing tree selection, and that their effect did not vary across scales. In contrast, preferences for trees of different condition, which is the state of tree canopy health, did vary across landscapes, indicating spatial variation in the selection of trees with respect to tree condition at the landscape‐scale, but not at the site‐scale. We conclude that resource selection processes can depend on the quality of those resources at different scales and their heterogeneous nature across landscapes, highlighting the consequence of scale‐dependent ecological processes. Designing studies that capture the heterogeneity in habitat and resources used by species that have an extensive distribution is an important prerequisite for effective conservation planning and management.     

Misclassified Resource Selection: Compositional Analysis and Unused Habitat

Abstract: During the past decade, compositional analysis (CA) has been used widely in animal—habitat and resource selection studies. Despite this popularity, CA has not been tested for potential systematic biases such as incorrect identification of preferred resources. We used computer-simulated data based on known habitat use and availability parameters to assess the potential for CA to incorrectly identify preferred habitat use. We consider in particular the situation when available habitat categories not used by all animals are included in the resource selection analysis, with substitution of a relatively small value, such as 0.01, for each 0% utilization value. Progressively larger misclassification-error*** rates in preferred habitat use resulted from substituting progressively smaller positive values for each 0% utilization of a habitat category.     

A new approach to assessing the space use behavior of macroinvertebrates by automated video tracking

1. Individual space and resource use are central issues in ecology and conservation. Recent technological advances such as automated tracking techniques are boosting ecological research in this field. However, the development of a robust method to track space and resource use is still challenging for at least one important ecosystem component: motile aquatic macroinvertebrates. The challenges are mostly related to the small body size and rapid movement of many macroinvertebrate species and to light scattering and wave signal interference in aquatic habitats.
2. We developed a video tracking method designed to reliably assess space use behavior among individual aquatic macroinvertebrates under laboratory (microcosm) conditions. The approach involves the use of experimental apparatus integrating a near infrared backlight source, a Plexiglas multi‐patch maze, multiple infrared cameras, and automated video analysis. It allows detection of the position of fast‐moving (~ 3 cm/s) and translucent individuals of small size (~ 5 mm in length, ~1 mg in dry weight) on simulated resource patches distributed over an experimental microcosm (0.08 m²).
3. To illustrate the adequacy of the proposed method, we present a case study regarding the size dependency of space use behavior in the model organism Gammarus insensibilis, focusing on individual patch selection, giving‐up times, and cumulative space used.
4. In the case study, primary data were collected on individual body size and individual locomotory behavior, for example, mean speed, acceleration, and step length. Individual entrance and departure times were recorded for each simulated resource patch in the experimental maze. Individual giving‐up times were found to be characterized by negative size dependency, with patch departure occurring sooner in larger individuals than smaller ones, and individual cumulative space used (treated as the overall surface area of resource patches that individuals visited) was found to scale positively with body size.
5. This approach to studying space use behavior can deepen our understanding of species coexistence, yielding insights into mechanistic models on larger spatial scales, for example, home range, with implications for ecological and evolutionary processes, as well as for the management and conservation of populations and ecosystems. Despite being specifically developed for aquatic macroinvertebrates, this method can also be applied to other small aquatic organisms such as juvenile fish and amphibians.

     

Considering ecological dynamics in resource selection functions

1.  Describing distribution and abundance is requisite to exploring interactions between organisms and their environment. Recently, the resource selection function (RSF) has emerged to replace many of the statistical procedures used to quantify resource selection by animals.
2.  A RSF is defined by characteristics measured on resource units such that its value for a unit is proportional to the probability of that unit being used by an organism. It is solved using a variety of techniques, particularly the binomial generalized linear model.
3.  Observing dynamics in a RSF – obtaining substantially different functions at different times or places for the same species – alerts us to the varying ecological processes that underlie resource selection.
4.  We believe that there is a need for us to reacquaint ourselves with ecological theory when interpreting RSF models. We outline a suite of factors likely to govern ecologically based variation in a RSF. In particular, we draw attention to competition and density-dependent habitat selection, the role of predation, longitudinal changes in resource availability and functional responses in resource use.
5.  How best to incorporate governing factors in a RSF is currently in a state of development; however, we see promise in the inclusion of random as well as fixed effects in resource selection models, and matched case–control logistic regression.
6.  Investigating the basis of ecological dynamics in a RSF will allow us to develop more robust models when applied to forecasting the spatial distribution of animals. It may also further our understanding of the relative importance of ecological interactions on the distribution and abundance of species.     

Inference in MCMC step selection models

Habitat selection models are used in ecology to link the spatial distribution of animals to environmental covariates and identify preferred habitats. The most widely used models of this type, resource selection functions, aim to capture the steady-state distribution of space use of the animal, but they assume independence between the observed locations of an animal. This is unrealistic when location data display temporal autocorrelation. The alternative approach of step selection functions embed habitat selection in a model of animal movement, to account for the autocorrelation. However, inferences from step selection functions depend on the underlying movement model, and they do not readily predict steady-state space use. We suggest an analogy between parameter updates and target distributions in Markov chain Monte Carlo (MCMC) algorithms, and step selection and steady-state distributions in movement ecology, leading to a step selection model with an explicit steady-state distribution. In this framework, we explain how maximum likelihood estimation can be used for simultaneous inference about movement and habitat selection. We describe the local Gibbs sampler, a novel rejection-free MCMC scheme, use it as the basis of a flexible class of animal movement models, and derive its likelihood function for several important special cases. In a simulation study, we verify that maximum likelihood estimation can recover all model parameters. We illustrate the application of the method with data from a zebra.     

Habitat selection and the value of information in heterogenous landscapes

Despite the wide usage of the term information in evolutionary ecology, there is no general treatise between fitness (i.e. density‐dependent population growth) and selection of the environment sensu lato. Here we 1) initiate the building of a quantitative framework with which to examine the relationship between information use in spatially heterogeneous landscapes and density‐dependent population growth, and 2) illustrate its utility by applying the framework to an existing model of breeding habitat selection. We begin by linking information, as a process of narrowing choice, to population growth/fitness. Second, we define a measure of a population's penalty of ignorance based on the Kullback–Leibler index that combines the contributions of resource selection (i.e. biased use of breeding sites) and density‐dependent depletion. Third, we quantify the extent to which environmental heterogeneity (i.e. mean and variance within a landscape) constrains sustainable population growth of unbiased agents. We call this the heterogeneity‐based fitness deficit, and combine this with population simulations to quantify the independent contribution of information‐use strategies to the total population growth rate. We further capitalize on this example to highlight the interactive effects of information between ecological scales when fear affects individual fitness through phenotypic plasticity. Informed breeding habitat selection moderates the demographic cost of fear commensurate with density‐dependent information use. Thus, future work should attempt to differentiate between phenotypic plasticity (i.e. acute fear) and demographic responses (i.e. chronic changes in population size). We conclude with a broader discussion of information in alternative contexts, and explore some evolutionary considerations for information use. We note how competition among individuals may constrain the information state among individuals, and the implications of this constraint under environmental change.     

Foraging strategies by omnivores: are black bears actively searching for ungulate neonates or are they simply opportunistic predators?

Omnivores feed on animals with dynamic distributions and on plants with static distributions. The search tactics they adopt will not only define the risk for the targeted prey, but also for other prey that may be consumed when encountered. The potential impact of omnivores on the dynamics of multi‐prey systems thus depends on resource selection and on the tactics used to find their prey. We present an approach that can clarify the foraging decisions of omnivores by combining analyses of habitat selection, local residency time, and interpatch movements. We use this framework to evaluate whether predation by omnivorous black bears on ungulate neonates resulted from an active search or from incidental encounters. We monitored 12 bears, 22 forest‐dwelling caribou, and 36 moose during calving seasons. We estimated the spatial patterns in relative occurrence probability of ungulate neonates using Resource Selection Functions (RSFs). We also mapped plant abundance from vegetation surveys. RSF were then built to assess the link between bear distribution and the distribution of these three food types (vegetation, moose calves, caribou fawns). We further evaluated the search tactic used by bears that led to this spatial dependency by exploring patterns of residency times and interpatch movements. Bears did not select areas with a high probability of encounter with neonates, but selected areas with abundant vegetation. Surprisingly, bears displayed shorter residency times in vegetation‐rich areas. The selection for vegetation‐rich areas was therefore achieved by moving preferentially, but frequently, between areas offering abundant vegetation. Such frequent interpatch movements could result in high rates of fortuitous encounters with neonates, even if bears are not actively searching for them. To mitigate the impacts of forest harvesting on threatened caribou populations, vegetation‐rich areas selected by bears (e.g. roadsides) should be segregated from large patches of mature conifer forest suitable for caribou.     

Density‐dependent,central‐place foraging in a grazing herbivore: competition and tradeoffs in time allocation near water

Optimal foraging theory addresses one of the core challenges of ecology: predicting the distribution and abundance of species. Tests of hypotheses of optimal foraging, however, often focus on a single conceptual model rather than drawing upon the collective body of theory, precluding generalization. Here we demonstrate links between two established theoretical frameworks predicting animal movements and resource use: central‐place foraging and density‐dependent habitat selection. Our goal is to better understand how the nature of critical, centrally placed resources like water (or minerals, breathing holes, breeding sites, etc.) might govern selection for food (energy) resources obtained elsewhere – a common situation for animals living in natural conditions. We empirically test our predictions using movement data from a large herbivore distributed along a gradient of water availability (feral horses, Sable Island, Canada, 2008–2013). Horses occupying western Sable Island obtain freshwater at ponds while in the east horses must drink at self‐excavated wells (holes). We studied the implications of differential access to water (time needed for a horse to obtain water) on selection for vegetation associations. Consistent with predictions of density‐dependent habitat selection, horses were reduced to using poorer‐quality habitat (heathland) more than expected close to water (where densities were relatively high), but were free to select for higher‐quality grasslands farther from water. Importantly, central‐place foraging was clearly influenced by the type of water‐source used (ponds vs. holes, the latter with greater time constraints on access). Horses with more freedom to travel (those using ponds) selected for grasslands at greater distances and continued to select grasslands at higher densities, whereas horses using water holes showed very strong density‐dependence in how habitat could be selected. Knowledge of more than one theoretical framework may be required to explain observed variation in foraging behavior of animals where multiple constraints simultaneously influence resource selection.     

Resource selection by Indiana bats during the maternity season

Little information exists on resource selection by foraging Indiana bats (Myotis sodalis) during the maternity season. Existing studies are based on modest sample sizes because of the rarity of this endangered species and the difficulty of radio-tracking bats. Our objectives were to determine resource selection by foraging Indiana bats during the maternity season and to compare resource use between pregnant and lactating individuals. We used an information theoretic approach with discrete choice modeling based on telemetry data to evaluate our hypotheses that land cover, percent canopy cover, distance to water, and prescribed fire affected the relative probability a point was used by a foraging Indiana bat. We fit models for individual bats and a population-level model based on all individuals with a random factor to account for differences in sample size among individuals. We radio-tracked 29 individuals and found variation in resource selection among individuals. However, among individuals with the same supported covariates, the magnitude and direction of the covariates were similar. Eighteen bats selected areas with greater canopy closure and 5 of 6 bats that had areas burned by low-intensity prescribed fire in their home range selected burned areas. Resource selection was related to land cover for 13 individuals; they selected forest and shrubland over agricultural land, which composed >50% of the landscape within 10 km. We found no support for our hypothesis that resource selection was related to individual reproductive condition or Julian date in our population-level model indicating habitat selection was not determined by reproductive status or date within the maternity season. Land use or forest management that greatly reduces canopy cover may have a negative impact on Indiana bat use. Maintaining forest cover in agricultural landscapes is likely critical to persistence of maternity colonies in these landscapes. Sites managed with low severity prescribed fire may be selected by some individuals because of reduced understory vegetation. © 2013 The Wildlife Society.     

重点生态功能区农户生计对环境资源的依赖性——以甘南高原为例

重点生态功能区承担着重要的生态系统服务供给功能,农户作为该区主要的经济活动主体,其对环境资源过度依赖会严重影响该区的生态环境质量,从而使生态系统服务功能受损。当前亟需深入探索重点生态功能区农户生计对环境资源的依赖性及其影响因素,为制定环境友好型区域发展政策提供借鉴。本研究以甘南高原为例,基于581份农户调查数据,分析了农户生计对环境资源的依赖度,并利用有序多分类Logistic回归模型识别了影响农户环境资源依赖度的因素。结果表明: 甘南高原农户生计对环境资源的依赖度较高,其主要体现在食物自给、生活用能、收入来源3个方面,依赖度分别为57.3%、56.9%和37.4%;不同类型农户生计对环境资源的依赖性存在显著差异,劳动力受教育水平较高及非农化水平较高的农户,对环境资源的依赖度较低,而抚养比系数较高的农户对环境资源的依赖度较高;家庭抚养比、劳动力受教育水平、家庭成员领导能力、外出打工人数占劳动力比重、生态政策、海拔等因素均对农户的环境资源依赖度有显著影响。其中,家庭抚养比、海拔对其具有正向影响,而外出打工人数占劳动力比重、劳动力受教育水平、家庭成员领导能力、生态政策等因素对其表现为负向影响。