Dataset Information

State-space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape.

ABSTRACT: Habitat loss is a major cause of species loss and is expected to increase. Loss of habitat is often associated with fragmentation of remaining habitat. Whether species can persist in fragmented landscapes may depend on their movement behavior, which determines their capability to respond flexibility to changes in habitat structure and spatial distribution of patches.Movement is frequently generalized to describe a total area used, or segmented to highlight resource use, often overlooking finer-scale individual behaviors. We applied hidden Markov models (HMM) to movement data from 26 eastern bettongs (Bettongia gaimardi) in fragmented landscapes. HMMs are able to identify distinct behavior states associated with different movement patterns and discover how these behaviors are associated with habitat features.Three distinct behavior states were identified and interpreted as denning, foraging, and fast-traveling. The probability of occurrence of each state, and of transitions between them, was predicted by variation in tree-canopy cover and understorey vegetation density. Denning was associated with woodland with low canopy cover but high vegetation density, foraging with high canopy cover but low vegetation density, and fast-traveling with low canopy cover and low vegetation density.Bettongs did move outside woodland patches, often fast-traveling through pasture and using smaller stands of trees as stepping stones between neighboring patches. Males were more likely to fast-travel and venture outside woodlands patches, while females concentrated their movement within woodland patches. Synthesis and applications: Our work demonstrates the value of using animal movement to understand how animals respond to variation in habitat structure, including fragmentation. Analysis using HMMs was able to characterize distinct habitat types needed for foraging and denning, and identify landscape features that facilitate movement between patches. Future work should extend the use of individual movement analyses to guide management of fragmented habitat in ways that support persistence of species potentially threatened by habitat loss.

SUBMITTER: Gardiner R

PROVIDER: S-EPMC6745662 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

State-space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape.

Gardiner Riana R Hamer Rowena R Leos-Barajas Vianey V Peñaherrera-Palma Cesar C Jones Menna E ME Johnson Chris C

Ecology and evolution 20190816 17

Habitat loss is a major cause of species loss and is expected to increase. Loss of habitat is often associated with fragmentation of remaining habitat. Whether species can persist in fragmented landscapes may depend on their movement behavior, which determines their capability to respond flexibility to changes in habitat structure and spatial distribution of patches.Movement is frequently generalized to describe a total area used, or segmented to highlight resource use, often overlooking finer-s ...[more]

PMID: 31534695

Similar Datasets

Project description:"Bottom-up" influences, that is, masting, plus population density and climate, commonly influence woodland rodent demography. However, "top-down" influences (predation) also intervene. Here, we assess the impacts of masting, climate, and density on rodent populations placed in the context of what is known about "top-down" influences. To explain between-year variations in bank vole Myodes glareolus and wood mouse Apodemus sylvaticus population demography, we applied a state-space model to 33 years of catch-mark-release live-trapping, winter temperature, and precise mast-collection data. Experimental mast additions aided interpretation. Rodent numbers in European ash Fraxinus excelsior woodland were estimated (May/June, November/December). December-March mean minimum daily temperature represented winter severity. Total marked adult mice/voles (and juveniles in May/June) provided density indices validated against a model-generated population estimate; this allowed estimation of the structure of a time-series model and the demographic impacts of the climatic/biological variables. During two winters of insignificant fruit-fall, 6.79 g/m2 sterilized ash seed (as fruit) was distributed over an equivalent woodland similarly live-trapped. September-March fruit-fall strongly increased bank vole spring reproductive rate and winter and summer population growth rates; colder winters weakly reduced winter population growth. September-March fruit-fall and warmer winters marginally increased wood mouse spring reproductive rate and September-December fruit-fall weakly elevated summer population growth. Density dependence significantly reduced both species' population growth. Fruit-fall impacts on demography still appeared after a year. Experimental ash fruit addition confirmed its positive influence on bank vole winter population growth with probable moderation by colder temperatures. The models show the strong impact of masting as a "bottom-up" influence on rodent demography, emphasizing independent masting and weather influences; delayed effects of masting; and the importance of density dependence and its interaction with masting. We conclude that these rodents show strong "bottom-up" and density-dependent influences on demography moderated by winter temperature. "Top-down" influences appear weak and need further investigation.

Project description:A new method has been developed to compute the probability that each amino acid in a protein sequence is in a particular secondary structural element. Each of these probabilities is computed using the entire sequence and a set of predefined structural class models. This set of structural classes is patterned after Jane Richardson's taxonomy for the domains of globular proteins. For each structural class considered, a mathematical model is constructed to represent constraints on the pattern of secondary structural elements characteristic of that class. These are stochastic models having discrete state spaces (referred to as hidden Markov models by researchers in signal processing and automatic speech recognition). Each model is a mathematical generator of amino acid sequences; the sequence under consideration is modeled as having been generated by one model in the set of candidates. The probability that each model generated the given sequence is computed using a filtering algorithm. The protein is then classified as belonging to the structural class having the most probable model. The secondary structure of the sequence is then analyzed using a "smoothing" algorithm that is optimal for that structural class model. For each residue position in the sequence, the smoother computes the probability that the residue is contained within each of the defined secondary structural elements of the model. This method has two important advantages: (1) the probability of each residue being in each of the modeled secondary structural elements is computed using the totality of the amino acid sequence, and (2) these probabilities are consistent with prior knowledge of realizable domain folds as encoded in each model. As an example of the method's utility, we present its application to flavodoxin, a prototypical alpha/beta protein having a central beta-sheet, and to thioredoxin, which belongs to a similar structural class but shares no significant sequence similarity.

Project description:Habitat selection theory suggests that when choosing breeding sites, animals should choose the best available habitat; however, studies show that individuals fail to choose habitats that maximize their fitness especially in drastically altered landscapes. Many studies have focused on selection at single scales, often using a single measure of fitness. However, links between habitat selection and fitness may vary depending on the spatial scale and measure of fitness, especially in situations where agricultural land use has altered the surrounding landscape.We examined multiscale habitat selection and fitness measures of the Bell's Vireo (Vireo bellii) and Willow Flycatcher (Empidonax traillii) using data collected in agriculturally fragmented landscapes.We found evidence for selection of nest sites with dense understory, larger patches, and increasing restored habitat cover and decreasing forest cover in the surrounding landscape.For both focal species, selection for dense understory significantly increased nest survival; however, there appeared to be no concurrent benefit for fledgling production. Selection for broader scale features positively influenced nest survival for the Willow Flycatcher with no concurrent benefit for fledgling production. The observed mismatches may be due to anthropogenic habitat fragmentation at broader scales or may represent reproductive trade-offs for a fitness benefit not measured in this study.Fine-scale habitat selection decisions by our focal species appear to match fitness outcomes, whereas habitat selection at broader scales only provided fitness benefits for the Willow Flycatcher. Though providing no fledgling production benefit, when combined with suitably dense nesting habitat, larger patches in landscapes with greater amounts of restored habitat cover for Bell's Vireo and lower amounts of forest cover for Willow Flycatcher will produce more fledglings per unit area than smaller patches in landscapes with less restored habitat and more forest cover, respectively, which could help inform conservation decisions for these at-risk species.

Project description:Most studies dealing with species distribution patterns on fragmented landscapes focus on the characteristics of habitat patches that influence local occurrence and abundance, but they tend to neglect the question of what drives colonization of previously unoccupied patches. In a study of the dryad butterfly, we combined classical approaches derived from metapopulation theory and landscape ecology to investigate the factors driving colonization from a recent refugium. In three consecutive transect surveys, we recorded the presence and numbers of imagos in 27 patches of xerothermic grassland and 26 patches of wet meadow. Among the predictors affecting the occurrence and abundance of the dryad, we considered environmental variables reflecting (i) habitat patch quality (e.g., goldenrod cover, shrub density, vegetation height); (ii) factors associated with habitat spatial structure (patch size, patch isolation and fragmentation); and (iii) features of patch surroundings (100-m buffers around patches) that potentially pose barriers or provide corridors. Patch colonization by the dryad was strongly limited by the distance from the species refugium in the region; there was a slight positive effect of shrub density in this respect. Butterfly abundance increased in smaller and more fragmented habitat patches; it was negatively impacted by invasive goldenrod cover, and positively influenced by the density of watercourses in patch surroundings. Nectar plant availability was positively related to species abundance in xerothermic grassland, while in wet meadow the effect was the reverse. We conclude that dryad colonization of our study area is very recent, since the most important factor limiting colonization was distance from the refugium, while the habitat quality of target patches had less relevance. In order to preserve the species, conservation managers should focus on enhancing the quality of large patches and should also direct their efforts on smaller and more fragmented ones, including those with relatively low resource availability, because such habitat fragments have an important role to play for specialist species.

Dataset Information

State-space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape.

Publications

State-space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets