Greg McDermid

A MULTI‐SCALE TEST OF THE FORAGE MATURATION HYPOTHESIS IN A PARTIALLY MIGRATORY UNGULATE POPULATION

The forage maturation hypothesis (FMH) proposes that ungulate migration is driven by selection for high forage quality. Because quality declines with plant maturation, but intake declines at low biomass, ungulates are predicted to select for intermediate forage biomass to maximize energy intake by following phenological gradients during the growing season. We tested the FMH in the Canadian Rocky Mountains by comparing forage availability and selection by both migrant and nonmigratory resident elk (Cervus elaphus) during three growing seasons from 2002-2004. First, we confirmed that the expected trade-off between forage quality and quantity occurred across vegetation communities. Next, we modeled forage biomass and phenology during the growing season by combining ground and remote-sensing approaches. The growing season started 2.2 days earlier every 1 km east of the continental divide, was delayed by 50 days for every 1000-m increase in elevation, and occurred 8 days earlier on south aspects. Migrant and resident selection for forage biomass was then compared across three spatial scales (across the study area, within summer home ranges, and along movement paths) using VHF and GPS telemetry locations from 119 female elk. Migrant home ranges occurred closer to the continental divide in areas of higher topographical diversity, resulting in migrants consistently selecting for intermediate biomass at the two largest scales, but not at the finest scale along movement paths. In contrast, residents selected maximum forage biomass across all spatial scales. To evaluate the consequences of selection, we compared exposure at telemetry locations of migrant and resident elk to expected forage biomass and digestibility. The expected digestibility for migrant elk in summer was 6.5% higher than for residents, which was corroborated with higher fecal nitrogen levels for migrants. The observed differences in digestibility should increase migrant elk body mass, pregnancy rates, and adult and calf survival rates. Whether bottom-up effects of improved forage quality are realized will ultimately depend on trade-offs between forage and predation. Nevertheless, this study provides comprehensive evidence that montane ungulate migration leads to greater access to higher-quality forage relative to nonmigratory congeners, as predicted by the forage maturation hypothesis, resulting primarily from large-scale selection patterns.

Linking ground-based to satellite-derived phenological metrics in support of habitat assessment

Changes in the timing of plant phenology are important indicators of inter-annual climatic variations and are a critical driver of food availability and habitat use for a range of species. A number of remote sensing techniques have recently been developed to observe vegetation cycles throughout the year, including the use of inexpensive visible spectrum digital cameras at the stand level and the use of high temporal frequency Advanced Very High Resolution Radiometer National Oceanic and Atmospheric Administration (AVHRR NOAA) and MODerate resolution Imaging Spectroradiometer (MODIS) imagery at a satellite scale. A fundamental challenge with using satellite data to track plant phenology, however, is the trade-off between the level of spatial detail and the revisit time provided by the sensor, and the ability to verify the interpretation of phenological activity. One way to address this challenge is to integrate remotely sensed observations obtained at different spatial and temporal scales to provide information that contains both high temporal density and fine spatial resolution observations. In this article, we compare measures of vegetation phenology observed from a network of ground-based cameras with satellite-derived measures of greenness derived from a fused broad (MODIS) and fine spatial (Landsat) scale satellite data set. We derive and compare three key indicators of phenological activity including the start date of green-up, start date of senescence and length of growing season from both a ground-based camera network and 30 m spatial resolution synthetic Landsat scenes. Results indicate that although field-based estimates, generally, predicted an earlier start and end of the vegetation season than the fused satellite observations, highly significant relationships were found for the prediction of the start (R 2 = 0.65), end (R 2 = 0.72) and length (R 2 = 0.70) of the growing season across all sites. We conclude that some predictable bias exists however unlike visual field measures of the collected data represent both a spectral and a visual archive for later use.

DESIGN AND INSTALLATION OF A CAMERA NETWORK ACROSS AN ELEVATION GRADIENT FOR HABITAT ASSESSMENT

Developments in distributed sensing, web camera image databases, and automated data visualization and analysis, among other emerging opportunities, have resulted in a suite of new techniques for monitoring habitat at many different scales. Data from these networks can provide important information on the timing of plant phenology with implications for habitat status and condition. In this article, we describe the design and deployment of a small network of cameras established along an elevation gradient in western Alberta, Canada, with the purpose of developing a more comprehensive understanding of seasonal phenophases and the reproductive timing of understory forest vegetation. During an eight-month period in 2009, over 6,700 images were acquired across seven sites throughout the growing season, providing a rich dataset documenting phenological activity of both the under- and overstory forest components. Strong elevation and climate responses were observed. A mathematical function was fitted to the data to demonstrate the capacity to capture phenological trends. This article demonstrates the utility of these types of relatively inexpensive, portable systems for monitoring seasonal vegetation development and change at high temporal resolutions across landscapes.

Environmental, biological and anthropogenic effects on grizzly bear body size: temporal and spatial considerations

BackgroundIndividual body growth is controlled in large part by the spatial and temporal heterogeneity of, and competition for, resources. Grizzly bears (Ursus arctos L.) are an excellent species for studying the effects of resource heterogeneity and maternal effects (i.e. silver spoon) on life history traits such as body size because their habitats are highly variable in space and time. Here, we evaluated influences on body size of grizzly bears in Alberta, Canada by testing six factors that accounted for spatial and temporal heterogeneity in environments during maternal, natal and ‘capture’ (recent) environments. After accounting for intrinsic biological factors (age, sex), we examined how body size, measured in mass, length and body condition, was influenced by: (a) population density; (b) regional habitat productivity; (c) inter-annual variability in productivity (including silver spoon effects); (d) local habitat quality; (e) human footprint (disturbances); and (f) landscape change.ResultsWe found sex and age explained the most variance in body mass, condition and length (R2 from 0.48–0.64). Inter-annual variability in climate the year before and of birth (silver spoon effects) had detectable effects on the three-body size metrics (R2 from 0.04–0.07); both maternal (year before birth) and natal (year of birth) effects of precipitation and temperature were related with body size. Local heterogeneity in habitat quality also explained variance in body mass and condition (R2 from 0.01–0.08), while annual rate of landscape change explained additional variance in body length (R2 of 0.03). Human footprint and population density had no observed effect on body size.ConclusionsThese results illustrated that body size patterns of grizzly bears, while largely affected by basic biological characteristics (age and sex), were also influenced by regional environmental gradients the year before, and of, the individual’s birth thus illustrating silver spoon effects. The magnitude of the silver spoon effects was on par with the influence of contemporary regional habitat productivity, which showed that both temporal and spatial influences explain in part body size patterns in grizzly bears. Because smaller bears were found in colder and less-productive environments, we hypothesize that warming global temperatures may positively affect body mass of interior bears.

A Simple Transformation for Visualizing Non-seasonal Landscape Change From Dense Time Series of Satellite Data

We present the Change, Aftereffect, and Trend (CAT) transform for visualizing and analyzing landscape dynamics from dense, multi-annual satellite vegetation index (VI) time series. The transform compresses a temporally detailed, multi-annual VI dataset into three new variables capturing change events and trends occurring within that period. First, peak annual greenness is extracted from each year. Then a series of simple calculations generate the three CAT variables: 1) Change: the maximum interannual absolute difference in peak greenness between consecutive years; 2) Aftereffect: the mean peak greenness after Change occurred; and 3) Trend: the slope of a linear regression applied to the entire annual peak greenness time series. We demonstrate the CAT transform by applying it to a MODIS 16-day 250-m normalized difference VI (NDVI) dataset covering the province of Alberta, Canada, for 2001 through 2011. We find that the CAT variables capture much of the non-seasonal change in the original NDVI time series. When displayed as an RGB color composite (the CAT image), the transform provides a striking visualization of both drastic and gradual decadal-scale landscape dynamics. Its application to quantitative analyses is demonstrated by an urban sprawl case study conducted around the city of Calgary, Alberta, where a simple decision-tree-based classification of the CAT transform variables was superior to a bitemporal, image-differencing approach. The simple yet powerful CAT transform is easily applicable to other study areas and datasets, and could foster a wider usage and understanding of the many archived high-temporal-resolution satellite datasets currently available.