7 research outputs found
Effects of Short-term Soil Conditioning by Cheatgrass and Western Wheatgrass
The exotic grass Bromus tectorum (cheatgrass) is a ubiquitous invader in the western USA. Cheatgrass is a proficient competitor, frequently displacing native plants, forming monotypic stands and reducing biodiversity in ecosystems it invades. Our experiment tested whether short-term soil modification by cheatgrass and a predominant native grass, Pascopyrum smithii (western wheatgrass), affected subsequent growth of both species. We compared productivity of cheatgrass and western wheatgrass by harvesting aboveground biomass of plants grown in either cheatgrass- or western wheatgrass-conditioned soils over two simulated growing seasons. Results indicated that cheatgrass soils do not inhibit the productivity of the native grass, but do facilitate further growth of cheatgrass. Cheatgrass may alter soil characteristics, allowing it to invade other plant communities, but cheatgrass invaded soil did not inhibit growth of the native species studied here. This suggests that restoration with native species after control of cheatgrass may be possible
Asynchrony among local communities stabilises ecosystem function of metacommunities
Abstract
Temporal stability of ecosystem functioning increases the predictability and reliability of ecosystem services, and understanding the drivers of stability across spatial scales is important for land management and policy decisions. We used species-level abundance data from 62 plant communities across five continents to assess mechanisms of temporal stability across spatial scales. We assessed how asynchrony (i.e. different units responding dissimilarly through time) of species and local communities stabilised metacommunity ecosystem function. Asynchrony of species increased stability of local communities, and asynchrony among local communities enhanced metacommunity stability by a wide range of magnitudes (1â315%); this range was positively correlated with the size of the metacommunity. Additionally, asynchronous responses among local communities were linked with speciesâ populations fluctuating asynchronously across space, perhaps stemming from physical and/or competitive differences among local communities. Accordingly, we suggest spatial heterogeneity should be a major focus for maintaining the stability of ecosystem services at larger spatial scales
Global change effects on plant communities are magnified by time and the number of global change factors imposed
Global change drivers (GCDs) are expected to alter community structure and consequently, the services that ecosystems provide. Yet, few experimental investigations have examined effects of GCDs on plant community structure across multiple ecosystem types, and those that do exist present conflicting patterns. In an unprecedented global synthesis of over 100 experiments that manipulated factors linked to GCDs, we show that herbaceous plant community responses depend on experimental manipulation length and number of factors manipulated. We found that plant communities are fairly resistant to experimentally manipulated GCDs in the short term (<10 y). In contrast, long-term (â„10 y) experiments show increasing community divergence of treatments from control conditions. Surprisingly, these community responses occurred with similar frequency across the GCD types manipulated in our database. However, community responses were more common when 3 or more GCDs were simultaneously manipulated, suggesting the emergence of additive or synergistic effects of multiple drivers, particularly over long time periods. In half of the cases, GCD manipulations caused a difference in community composition without a corresponding species richness difference, indicating that species reordering or replacement is an important mechanism of community responses to GCDs and should be given greater consideration when examining consequences of GCDs for the biodiversityâecosystem function relationship. Human activities are currently driving unparalleled global changes worldwide. Our analyses provide the most comprehensive evidence to date that these human activities may have widespread impacts on plant community composition globally, which will increase in frequency over time and be greater in areas where communities face multiple GCDs simultaneously
Tundra Trait Team:a database of plant traits spanning the tundra biome
Abstract
Motivation: The Tundra Trait Team (TTT) database includes fieldâbased measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and tradeâoffs, traitâenvironment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters.
Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density.
Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and subâAntarctic Marion Island. More than 99% of observations are georeferenced.
Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods.
Major taxa and level of measurement: Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species.
Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release