Large Elevational Gradient Research Articles

Elevational patterns in the vascular flora of a highly diverse region in southern Mexico

We examined general and family-specific patterns of vascular plant richness along a large elevational gradient (0–3,670 m a.s.l.), assessed the continuity of these patterns and analysed their potential underlying causes in a high diversity region of the Sierra Madre del Sur, Oaxaca, Mexico. We used a vascular plant database constructed previously. The gradient was divided into 18 200-m elevation belts. To examine elevational patterns of richness, we used both observed and estimated (interpolated) species richness, as well as genus and family observed richness, for each belt. A generalised linear model (GLM) was used to assess the effect of altitude on area-corrected species richness (standard area = 100 km2), and a numerical classification of the elevational belts based on species richness was performed. Overall, richness at the three taxonomic levels decreased with elevation, but some individual families departed from this pattern. A sharp drop in species richness was observed at 1,800 m, and the dendrogram separated two elevational floristic groups at this elevation. The GLM revealed a significant negative effect of elevation on species richness. Despite this overall decreasing pattern for vascular plants along this extensive gradient, an examination of some family-specific patterns revealed the existence of other elevation–diversity relationships, indicating taxon-specific responses to elevation. The most noticeable discontinuity in species richness, at ca. 1,800 m, is likely related to a critical temperature isocline.

Seasonal habitat use and selection by grizzly bears in Northern British Columbia

AbstractWe defined patterns of habitat use and selection by female grizzly bears (Ursus arctos) in the Besa‐Prophet watershed of northern British Columbia. We fitted 13 adult females with Geographic Positioning System (GPS) radio‐collars and monitored them between 2001 and 2004. We examined patterns of habitat selection by grizzly bears relative to topographical attributes and 3 potential surrogates of food availability: land‐cover class, vegetation biomass or quality (as measured by the Normalized Difference Vegetation Index), and selection value for prey species themselves (moose [Alces alces], elk [Cervus elaphus], woodland caribou [Rangifer tarandus], Stone's sheep [Ovis dalli stonei]). Although vegetation biomass and quality, and selection values for prey were important in seasonal selection by some individual bears, land‐cover class, elevation, aspect, and vegetation diversity most influenced patterns of habitat selection across grizzly bears, which rely on availability of plant foods and encounters with ungulate prey. Grizzly bears as a group avoided conifer stands and areas of low vegetation diversity, and selected for burned land‐cover classes and high vegetation diversity across seasons. They also selected mid elevations from what was available within seasonal ranges. Quantifying relative use of different attributes helped place selection patterns within the context of the landscape. Grizzly bears used higher elevations (1,595 ± 31 m SE) in spring and lower elevations (1,436 ± 27 m) in fall; the range of average elevations used among individuals was highest (500 m) during the summer. During all seasons, grizzly bears most frequented aspects with high solar gain. Use was distributed across 10 land‐cover classes and depended on season. Management and conservation actions must maintain a diverse habitat matrix distributed across a large elevational gradient to ensure persistence of grizzly bears as levels of human access increase in the northern Rocky Mountains. © 2011 The Wildlife Society.

Niche breadth, rarity and ecological characteristics within a regional flora spanning large environmental gradients

AbstractAim Species specialization, which plays a fundamental role in niche differentiation and species coexistence, is a key biological trait in relation to the responses of populations to changing environments. Species with a limited niche breadth are considered to experience a higher risk of extinction than generalist species. This work aims to measure the degree of specialization in the regional flora of the French Alps and test whether species specialization is related to species rarity and ecological characteristics.Location This study was conducted in the French Alps region, which encompasses a large elevational gradient over a relatively limited area (26,000 km2).Methods Specialization was estimated for approximately 1200 plant species found in the region. Given the inherent difficulty of pinpointing the critical environmental niche axes for each individual species, we used a co‐occurrence‐based index to estimate species niche breadths (specialization index). This comprehensive measurement included crucial undetermined limiting niche factors, acting on both local and regional scales, and related to both biotic and abiotic interactions. The specialization index for each species was then related to a selection of plant typologies such as Grime strategies and Raunkiaer life‐forms, and to two measurements of plant rarity, namely regional area of occupancy and local abundance.Results Specialist species were mainly found in specific and harsh environments such as wetlands, cold alpine habitats and dry heathlands. These species were usually geographically restricted but relatively dominant in their local communities. Although none of the selected traits were sufficient predictors of specialization, pure competitors were over‐represented amongst generalist species, whereas stress‐tolerant species tended to be more specialized.Main conclusions Our results suggest that co‐occurrence‐based indices of niche breadth are a satisfactory method for inferring plant specialization using large species samples across very heterogeneous environments. Our results are an empirical validation of the tolerance–dominance trade‐off and also provide interesting insights into the long‐standing question of which biological properties characterize species with narrow niche breadth that are potentially threatened by global changes in the environment.

Assessing the effects of climate change on the phenology of European temperate trees

Modelling phenology is crucial to assess the impact of climate change on the length of the canopy duration and the productivity of terrestrial ecosystems. Focusing on six dominant European tree species, the aims of this study were (i) to examine the accuracy of different leaf phenology models to simulate the onset and ending of the leafy season, with particular emphasis on the putative role of chilling to release winter bud dormancy and (ii) to predict seasonal shifts for the 21st century in response to climate warming. Models testing and validation were done for each species considering 2 or 3 years of phenological observations acquired over a large elevational gradient (1500 m range, 57 populations). Flushing models were either based solely on forcing temperatures (1-phase models) or both on chilling and forcing temperatures (2-phases models). Leaf senescence models were based on both temperature and photoperiod. We show that most flushing models are able to predict accurately the observed flushing dates. The 1-phase models are as efficient as 2-phases models for most species suggesting that chilling temperatures are currently sufficient to fully release bud dormancy. However, our predictions for the 21st century highlight that chilling temperature could be insufficient for some species at low elevation. Overall, flushing is expected to advance in the next decades but this trend substantially differed between species (from 0 to 2.4 days per decade). The prediction of leaf senescence appears more challenging, as the proposed models work properly for only two out of four deciduous species, for which senescence is expected to be delayed in the future (from 1.4 to 2.3 days per decade). These trends to earlier spring leafing and later autumn senescence are likely to affect the competitive balance between species. For instance, simulations over the 21st century predict a stronger lengthening of the canopy duration for Quercus petraea than for Fagus sylvatica, suggesting that shifts in the elevational distributions of these species might occur.

A North American regional reanalysis climatology of the Haines Index

A warm-season (May through October) Haines Index climatology is derived using 32-km regional reanalysis temperature and humidity data from 1980 to 2007. We compute lapse rates, dewpoint depressions, Haines Index factors A and B, and values for each of the low-, mid- and high-elevation variants of the Haines Index. Statistical techniques are used to investigate the spatial and temporal variability of the index across North America. The new climatology is compared with a previous climatology derived from 2.5° (~280 km) global reanalysis data. Maps from the two climatologies are found to be very similar for most of North America. The largest differences appear along the eastern coastline and in regions of large elevation gradients, where the orography in the 32-km climatology is better resolved than that of the 2.5° climatology. In coastal areas of eastern North America and where there is steeply sloping terrain, the new climatology can augment the information from the 2.5° climatology to help analyse the performance and interpret the results of the Haines Index in these regions. A linear trend analysis of the total number of high-Haines Index days occurring in each warm season reveals no significant linear trends over the 28-year data period.

Contrasting patterns in elevational diversity between microorganisms and macroorganisms

Aim Data and analyses of elevational gradients in diversity have been central to the development and evaluation of a range of general theories of biodiversity. Elevational diversity patterns have, however, been severely understudied for microbes, which often represent decomposer subsystems. Consequently, generalities in the patterns of elevational diversity across different trophic levels remain poorly understood. Our aim was to examine elevational gradients in the diversity of macroinvertebrates, diatoms and bacteria along a stony stream that covered a large elevational gradient. Location Laojun Mountain, Yunnan province, China. Methods The sampling scheme included 26 sites spaced at elevational intervals of 89 m from 1820 to 4050 m elevation along a stony stream. Macroinvertebrate and diatom richness were determined based on the morphology of the specimens. Taxonomic richness for bacteria was quantified using a molecular fingerprinting method. Over 50 environmental variables were measured at each site to quantify environmental variables that could correlate with the patterns of diversity. We used eigenvector-based spatial filters with multiple regressions to account for spatial autocorrelation. Results The bacterial richness followed an unexpected monotonic increase with elevation. Diatoms decreased monotonically, and macroinvertebrate richness showed a clear unimodal pattern with elevation. The unimodal richness pattern for macroinvertebrates was best explained by the mid-domain effect (r2 = 0.72). The diatom richness was best explained by the variation in nutrient supply, and the increase in bacterial richness with elevation may be related to an increased carbon supply. Main conclusions We found contrasting patterns in elevational diversity among the three studied multi-trophic groups comprising unicellular and multicellular aquatic taxa. We also found that there may be fundamental differences in the mechanisms underlying these species diversity patterns.

Infra‐red thermometry of alpine landscapes challenges climatic warming projections

AbstractRough mountain terrain offers climatic conditions (niches) to plants and animals poorly represented by conventional climate station data. However, the extent to which actual temperatures deviate from those of the freely circulating atmosphere had never been assessed at a landscape level. Here, we quantify thermal life conditions across topographically rich mountain terrain by using a combination of thermal (IR) imagery of surface temperature with data from a large number of miniature data loggers buried at 3 cm soil depth. The data obtained from six alpine (Alps) and arctic‐alpine slopes (Norway, Sweden, Svalbard) evidence persistent root zone temperatures of 2–4 K above air temperature during summer. Surface temperatures show strong positive (2–9 K) and negative (3–8 K) deviations from air temperature on bright days and clear nights, respectively. As to be expected, south oriented slopes are warmer than west and north slopes but microclimatic variation on clear sky days was strong within all slopes, with 8.4±2.5 K (mean±SD) surface temperature differences persisting over several hours per day along horizontal (i.e., equal elevation) transects. Life conditions of alpine organisms are thus strongly decoupled from conditions in the free atmosphere and cannot reliably be inferred from climate station data in both, temperate and arctic latitudes. Microtopography can mimic temperature differences of large elevational (or latitudinal) gradients over very short horizontal distances. This is important in the context of climate change because it shows that species do not necessarily need to climb several hundred meters in elevation to escape the warmth. Quite often, few meters of horizontal shift will do. For plants unable to, or too slow to adapt to a warmer climate, thermal microhabitat mosaics offer both refuge habitats as well as stepping stones as atmospheric temperatures rise.

Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States

AbstractSpatial climate data sets of 1971–2000 mean monthly precipitation and minimum and maximum temperature were developed for the conterminous United States. These 30‐arcsec (∼800‐m) grids are the official spatial climate data sets of the U.S. Department of Agriculture. The PRISM (Parameter‐elevation Relationships on Independent Slopes Model) interpolation method was used to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States. PRISM calculates a climate–elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell. Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain. Surface stations used in the analysis numbered nearly 13 000 for precipitation and 10 000 for temperature. Station data were spatially quality controlled, and short‐period‐of‐record averages adjusted to better reflect the 1971–2000 period.PRISM interpolation uncertainties were estimated with cross‐validation (C‐V) mean absolute error (MAE) and the 70% prediction interval of the climate–elevation regression function. The two measures were not well correlated at the point level, but were similar when averaged over large regions. The PRISM data set was compared with the WorldClim and Daymet spatial climate data sets. The comparison demonstrated that using a relatively dense station data set and the physiographically sensitive PRISM interpolation process resulted in substantially improved climate grids over those of WorldClim and Daymet. The improvement varied, however, depending on the complexity of the region. Mountainous and coastal areas of the western United States, characterized by sparse data coverage, large elevation gradients, rain shadows, inversions, cold air drainage, and coastal effects, showed the greatest improvement. The PRISM data set benefited from a peer review procedure that incorporated local knowledge and data into the development process. Copyright © 2008 Royal Meteorological Society

Biogeography and Landscape-Scale Diversity of the Dominant Crenarchaeota of Soil

We surveyed the diversity of soil Archaea across a large scale elevational gradient of ecosystem types, from foothills forest to alpine tundra in the Front Range of the Rocky Mountains. We used a dilution technique to sequence the single most abundant archaeal 16S rDNA sequence in each of the 40 soil cores distributed across the gradient to compare our results to those of typical 16S clone library studies. We found a greater diversity of sequences than has typically been found in clone library studies from a single site or core, identifying sequences both from the Terrestrial Group and the FFSB Group at several sites. We did not observe any significant environmental correlates with the dominant sequence type, nor was there any relationship between the spatial distance between samples and the phylogenetic similarity of the dominant sequence types. Despite using a very different methodology, our collective results are in remarkably good agreement with other studies of soil Crenarchaeota in terms of the diversity and relative abundance of sequence types identified. We are able to identify two instances of very tightly clustered sequences which we suggest are the results of global selective sweeps-one closely related to SCA1145, an abundant globally distributed group within the Terrestrial Group of Crenarchaeota, and another nested within the more basal FFSB group of sequences. We replicated our sequence results at two levels: first, by repeating the dilution and PCR processes from the same soil core DNA extraction, and second, by performing a replicate DNA extraction from the same homogenized soil core sample. Pairs of sequences produced by the dilution replicates were significantly more similar than the pairs of sequences produced by the extraction replicates, suggesting that soil Crenarchaeota exists in highly localized and discrete clonal populations.

Effect of altitudinal migration within a watershed on the reproductive success of American dippers

Distinct changes occur in the distribution of American dipper (Cinclus mexicanus Swainson, 1827) populations during the breeding season. Small numbers of American dippers remain resident on the wintering site, while the majority of birds make short altitudinal movements upstream. Therefore, American dippers breed over large elevation gradients within a watershed, using both the main river and its associated tributaries. I hypothesized that altitudinal migration of American dippers would affect their timing of breeding and ultimately their productivity. Additionally, since the main river and its tributaries differ in habitat, elevation, and nesting substrates, I hypothesized that these variables would also influence American dipper breeding performance. In the Chilliwack watershed of British Columbia, Canada, I followed 99 pairs of American dippers: 23 in 1999, 40 in 2000, and 36 in 2001, of which approximately 65% were residents and 35% were migrants. Resident pairs on the lower elevation river initiated nests earlier and a greater proportion had second broods, contributing to slightly higher nest success and annual productivity compared with migrants on tributaries. Reduced productivity was primarily associated with later onset of breeding, which increased the likelihood that nests were lost to predation or flooding and reduced the probability of initiating a second clutch. Timing of breeding was affected by migratory status and year, but elevation and habitat did not directly influence breeding performance.

Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: an application over complex terrain in Austria

Using daily observations of temperature, precipitation, radiation, and humidity from 24 stations spanning a large elevation gradient in Austria, we tested several previously defined algorithms for estimating daily radiation and humidity. The estimation algorithms were first tested independently, and then combined, resulting in a combined algorithm for estimating both radiation and humidity that relies only on temperature and precipitation inputs. Mean absolute errors (MAE) for joint radiation and humidity estimates were 2.52 MJ m −2 per day and 85.6 Pa, respectively, close to values reported for the algorithm development studies. Biases were low: +0.02 MJ m −2 per day and +28.2 Pa for radiation and humidity, respectively. Initial results showed biases in estimated radiation related to horizon obstruction and snowpack. We amended the original algorithm, successfully eliminating these effects. Annual prediction MAE was weakly correlated with elevation, and annual bias was not correlated with elevation. Analysis of seasonal patterns in error-elevation relationships showed several periods with significant trends. Radiation MAE was slightly higher in mid-summer for higher elevations, and radiation biases were in general closer to zero throughout the spring and summer at higher elevations. Humidity estimates showed an increased MAE and positive bias at higher elevations in winter. We concluded that the effect of different temperature lapse rates for daily maximum and minimum temperature on the relationship between diurnal temperature range and atmospheric transmittance does not seriously impair predictions over steep elevation gradients in complex terrain.