Metacommunity theory suggests a potentially important role for dispersal in diversity maintenance at local, as well as regional, scales. In addition, propagule addition experiments have shown that dispersal often limits local diversity. However, actual dispersal rates into local communities and the contribution of immigrants to observed local diversity are poorly known. We present a new approach that partitions the diversity of a target community into dispersalmaintained and dispersal-independent components. Specifically, we quantify distances through space and time to the nearest potential seed source for naturally occurring recruits in target communities by using hierarchical data on species pools (local, site, region, and seed bank). Using this "recruit tag" approach, we found that dispersal contributed 29%-57% of the seedling diversity in perennial grasslands with different successional histories. However, both dispersal and seedling mortality remained remarkably constant, in absolute terms, over succession. The considerable loss of diversity over secondary succession (66%), therefore, could be understood only by considering how these processes interact with the decreasing disturbance rate (i.e., frequency of gaps) in later-successional sites. We conclude that a metacommunity perspective is relevant and necessary to understand the diversity and community assembly of this study system.
Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series even more exciting results especially about range shifts can be expected. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.
Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of vascular plants in permanent plots. With 79 datasets from five continents and 7789 vegetation time-series monitored for at least six years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.
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