Search NASA⌕ Search

SEARCH · Search NASA

Results for “bioclimatic gradient”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

The bioclimatic extent and pattern of the cold edge of the boreal forest: the circumpolar taiga-tundra ecotone

Current configurations of forest structure at the cold edge of the boreal may help understand the future of ecosystem functioning in high northern latitudes. The circumpolar biome boundary at the boreal (taiga) forest and tundra interface is an ecological transition zone (taiga-tundra ecotone; TTE) experiencing changes that affect its forest structure. We accounted for the TTE's horizontal forest structure with an estimate of its extent and pattern as represented by tree canopy cover (TCC). We quantified TCC patterns with an algorithm that describes its spatial gradient, and summarized landscape patterns of structure to represent heterogeneity, capturing abrupt, diffuse, and uniform forest at mesoscales. We used these landscape patterns to constrain the spatial extent of sparse and open canopy forest, and non-forest (forest-adjacent) edge that defines the TTE extent. The resulting map of the TTE extent is based on forest structure spatial patterns resolved at 30 m, highlights structural variability across landscapes, and helps distinguish tundra from boreal domains. We classified 14 594 landscapes as those associated with the TTE within a circumpolar bioclimatic envelope (11.575 million km2), where 44.83% of the area of these landscapes were forest and non-forest edge, yet 36.43% contributed to the TTE extent. We report the overall extent of the TTE (3.032 million km2) across North America and Greenland (53%), and Eurasia (47%), where 0.697 million km2 is non-forest edge, 0.549 million km2 is sparse forest, and 1.787 million km2 is open canopy forest. Diffuse forest landscapes dominate the TTE (79%), and abrupt landscapes (~19%) indicate portions of the TTE where sparse forest and non-forest edge are the prevailing structural patterns. This account of the TTE quantifies the area of the cold edge of the boreal forest where previous global estimates show high discrepancies, and can help target monitoring and prediction of circumpolar dynamics.

Paul M Montesano↗

Simulation of Avifauna Distributions Using Remote Sensing

Remote sensing has proved a fruitful tool for understanding the distribution and functioning of plant communities at multiple scales and to understand their coupling to bioclimatic and anthropogenic factors. But a similar approach to understanding the distribution and abundance of bird species as well as many other animal organisms is lacking. The increasing need for such understanding is evident with the recent examples of threats to human health via avian vector transmission and the increasing emphasis on global conservation biology. From experimental observations we know that species richness tends to track biological or environmental gradients. In this paper, we explore the fundamental idea that thermal and water-relation environments of birds, as estimated from satellite data and biophysical models, can define the constraints on their Occurrences and richness. We develop individual bird energy budget models and use these models to define the climate space niche of birds. Using satellite data assimilation products to drive our models, we disperse a distribution of virtual or actual bird species across the landscape in accordance to the limits expressed by their climate space niche. Here, we focus on the North American summer breeding season and give two examples to illustrate our approach. The first is a tundra loving bird, e.g. corresponding to the Culidris genus, and a second genus example, Myiurchus, that corresponds to arid or semi-arid regions. We define these birds in terms of their basic physiology and morphological characteristics, construct avian energetic simulations to predict their allowable metabolic ranges and climate space limits.

Smith, James A.↗