4 results — topic: mountain ecosystems

Dataset

Data for Context-dependent biotic interactions control plant abundance across altitudinal environmental gradients, 2014, 2016, Colorado, USA.

Many biotic interactions influence community structure, yet most distribution models for plants have focused on plant competition or used only abiotic variables to predict plant abundance. Furthermore, biotic interactions are commonly context-dependent across abiotic gradients. For example, plant-pl

Joshua S Lynn, Melanie R Kazenel, Stephanie N Kivlin2021DOI: 10.6073/pasta/953d0af267ddb6a0ddb970bff3218a61
Dataset

Phenology of selected cavity-nesting Hymenoptera and flowering plant taxa in the Colorado Rocky Mountains from 2008 to 2010.

Data come from fourteen sites in the West Elk Mountains of Colorado, USA. The study aimed to identify the factors regulating phenology of plants and cavity-nesting insects, and to determine the likelihood of asynchrony between flowering and pollinator emergence under climate change. Numbers of flowe

Rocky Mountain Biological Laboratory, Ecological Society of America, Jessica Forrest2021
Dataset

Data for Lynn et al. “Soil microbes that may accompany climate warming increase alpine plant production”

Climate change is causing species with non-overlapping ranges to come in contact, and a key challenge is to predict the consequences of such species re-shuffling. Experiments on plants have focused largely on novel competitive interactions; other species interactions, such as plant-microbe symbioses

Lynn, J.S, D.A. Duarte, J.A. Rudgers2020DOI: 10.6073/pasta/7c493a1d737f81905a41a81630695f14
Dataset

Plant composition data from 67 grassland sites of the Upper Gunnison Basin, CO, USA, 2014

Here, we deposit data from a vegetation survey conducted in 2014. The data was collected to document current vegetation patterns in the region, parameterize species distribution models, and assess community turnover in flower color. The survey was conducted in the Upper Gunnison Basin and the enviro

Lynn, J.S, M.R. Kazenel, S.N. Kivlin2020DOI: 10.6073/pasta/f0050c1cfe11a5f78e7bd736c8d6f6ee