Habitat fragmentation and reproductive success: a structural equation modelling approach

Using change trajectories to study the impacts of multi-annual habitat loss on fledgling production in an old forest specialist bird

The loss and subdivision of habitat into smaller and more spatially isolated units due to human actions has been shown to adversely affect species worldwide. We examined how changes in old forest cover during eight years were associated with the cumulative number of fledged offspring at the end of study period in Eurasian treecreepers (Certhia familiaris) in Central Finland. We were specifically interested in whether the initial level of old forest cover moderated this relation. We applied a flexible and powerful approach, latent growth curve modelling in a structural equation modeling (SEM) framework, to create trajectories describing changes in old forest cover through time, and studied how this change at both the territory core and landscape scales impacted fledging numbers. Our main finding was that at the territory core scale the negative impact of habitat loss on fledging numbers was lessened by the higher levels of initial forest cover, while no association was found at the landscape scale. Our study highlights a powerful, but currently under-utilised methodology among ecologists that can provide important information about biological responses to changes in the environment, providing a mechanistic way to study how land cover dynamics can affect species responses.

Urban Vegetative Cover Fragmentation in the U.S.: Associations With Physical Activity and BMI

INTRODUCTION

Urban vegetative cover provides a range of ecosystem services including contributions to human health and well-being. Urbanization exerts tremendous pressure on this natural resource, causing fragmentation and loss of urban greenspace. This study aimed to examine associations between vegetative cover fragmentation and physical activity and BMI at the county scale in the U.S. metropolitan statistical areas greater than 1 million in population.

METHODS

National Land Cover Database 2006 and Behavioral Risk Factor Surveillance System 2008 provided land cover and human health data, respectively. Analyses were performed in 2013 at the county scale where the health data were reported. Spearman rank correlation and stepwise and hierarchical regression models were applied to estimate relationships between land cover and health variables.

RESULTS

After controlling for median household income and race, greater forest edge density (β=0.272, p<0.05) and larger size of herbaceous patches (β=0.261, p<0.01) were associated with a higher percentage of participation in physical activity within counties. More connections between forest and developed area (β=0.37, p<0.01) and greater edge density of shrubland (β=0.646, p<0.001) were positively associated with a higher percentage of normal BMI (<25) within counties.

CONCLUSIONS

Forest land cover and some degree of fragmentation are associated with population physical activity. Future studies should examine how built environments and varying land cover configurations influence physical activity and weight status.