Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering approach does not acknowledge that the influence of surrounding landscape features should diminish with distance, and it does not yield an estimate of the unknown scale parameters.
Objectives
The purpose of this paper is to present an approach that allows for statistical inference about the scales at which landscape variables affect abundance.
Methods
Our method uses smoothing kernels to average landscape variables around focal sites and uses maximum likelihood to estimate the scale parameters of the kernels and the effects of the smoothed variables on abundance. We assessed model performance using a simulation study and an avian point count dataset.
Results
The simulation study demonstrated that estimators are unbiased and produce correct confidence interval coverage except in the rare case in which there is little spatial autocorrelation in the landscape variable. Canada warbler abundance was more highly correlated with site-level measures of NDVI than landscape-level NDVI, but the reverse was true for elevation. Canada warbler abundance was highest when elevation in the surrounding landscape, defined by an estimated Gaussian kernel, was between 1300 and 1400 m.
Conclusions
Our method provides a rigorous way of formally estimating the scales at which landscape variables affect abundance, and it can be embedded within most classes of statistical models.
Urbanization can affect the density of hosts, altering patterns of infection risk in wildlife. Most studies examining associations between urbanization and host-parasite interactions have focused on vertebrate wildlife that carry zoonotic pathogens, and less is known about responses of other host taxa, including insects.
Objectives
Here we ask whether urban development predicts infection by a protozoan, Ophyrocystis elektroscirrha, in three populations of monarchs (Danaus plexippus): migratory monarchs in northeastern U.S., non-migratory monarchs in southeastern coastal U.S., and non-migratory monarchs in Hawaii.
Methods
We used impervious surface and developed land cover classes from the National Land Cover Database to derive proportional measures of urban development and an index of land cover aggregation at two spatial scales. Parasite data were from previous field sampling (Hawaii) and a citizen science project focused on monarch infection in North America.
Results
Proportional measures of urban development predicted greater infection prevalence for non-migratory monarchs sampled in the southern coastal U.S. and Hawaii, but not in the northern U.S. Aggregations of low intensity development, dominated by single-family housing, predicted greater infection prevalence in monarchs from the northern and southern coastal U.S. populations, but predicted lower infection prevalence in Hawaii.
Conclusions
Because natural habitats have been reduced by land-use change, plantings for monarchs in residential areas and urban gardens has become popular among the public. Mechanisms that underlie higher infection prevalence in urban landscapes remain unknown. Further monitoring and experimental studies are needed to inform strategies for habitat management to lower infection risk for monarchs.
A thorough understanding of a population’s ecology requires knowledge of the relationship between habitat use, resource use and demographic parameters. We undertook an empirical investigation of habitat use, resource use and demography in a population of common ravens (Corvus corax), a species widely distributed throughout the Northern Hemisphere. The abundance of ravens is increasing in many parts of western North America, which represents a conservation concern since predation by ravens is thought to contribute to the decline of several sensitive species. We defined resources as the suite of physical and biological components in the environment that led to occupancy of a particular place by ravens. The home ranges of breeding and nonbreeding ravens contained similar proportions of resources, but breeding ravens used more edges, roads, forest, clearcuts, and towns than nonbreeders. We detected no differences in survival between the sexes, but breeding ravens survived at higher rates than nonbreeders, due to exclusion by breeding ravens from those resources positively associated with survival. Raven use of mature forests and anthropogenic land use types was positively associated with survival. Breeding raven use of clearcuts and patchy areas contributed to increased reproduction, but the use of clearcuts along with the use of roads was negatively associated with survival due to illegal shooting. Greater insight into the demography of synanthropic species such as the common raven will enable managers to make informed decisions for protecting biodiversity. This study is the first to consider the demographic consequences of habitat use and resource use for both nonbreeding and breeding common ravens. 相似文献
Landscape patterns created by natural disturbance such as windstorms can affect forest regeneration, carbon cycling, and other ecological processes.
Objectives
We develop a method for remotely measuring tornado damage severity and describe landscape-scale patterns of tornado damage. We examine the extent and distribution of damage severity and gaps created by tornadoes, and examine how topographic variation can influence tornado damage severity.
Methods
Focusing on two April 2011 tornadoes that struck the Chattahoochee National Forest (CNF) in Georgia and the Great Smoky Mountains (GSM) in Tennessee, we used supervised classification of aerial photographs to map damage severity. We report the extent and distribution of damage severity from each track and characterize patterns of damage using FragStats. Using topographic overlays, we test hypotheses regarding how physiographic features such as valleys and ridges affect tornado damage severity.
Results
Tornado damage severity estimates were significantly correlated with ground-truth measurements. The 64-km CNF track damaged 1712 ha (>25 % severity), while the 26-km GSM track damaged 1407 ha. Tornado damage severity was extremely variable and frequency of gap sizes drastically decreased with size, with many small gaps and few very large gaps, consistent with other types of wind damage. Damage severity declined as tornadoes ascended ridges and increased as they descended ridges. This effect was more consistent on shallow slopes relative to steeper slopes.
Conclusions
This study outlines an objective methodology for remotely characterizing tornado damage severity. The results from this study fill an important gap in ecological understanding of the spatial components of the forest tornado disturbance regime.
