Directional trends in species composition over time can lead to a widespread overemphasis of year‐to‐year asynchrony

Questions: Compensatory dynamics are described as one of the main mechanisms that increase community stability, e.g., where decreases of some species on a year‐to‐year basis are offset by an increase in others. Deviations from perfect synchrony between species (asynchrony) have therefore been advocated as an important mechanism underlying biodiversity effects on stability. However, it is unclear to what extent existing measures of synchrony actually capture the signal of year‐to‐year species fluctuations in the presence of long‐term directional trends in both species abundance and composition (species directional trends hereafter). Such directional trends may lead to a misinterpretation of indices commonly used to reflect year‐to‐year synchrony. Methods: An approach based on three‐term local quadrat variance (T3) which assesses population variability in a three‐year moving window, was used to overcome species directional trend effects. This “detrending” approach was applied to common indices of synchrony across a worldwide collection of 77 temporal plant community datasets comprising almost 7,800 individual plots sampled for at least six years. Plots included were either maintained under constant “control” conditions over time or were subjected to different management or disturbance treatments. Results: Accounting for directional trends increased the detection of year‐to‐year synchronous patterns in all synchrony indices considered. Specifically, synchrony values increased significantly in ~40% of the datasets with the T3 detrending approach while in ~10% synchrony decreased. For the 38 studies with both control and manipulated conditions, the increase in synchrony values was stronger for longer time series, particularly following experimental manipulation. Conclusions: Species’ long‐term directional trends can affect synchrony and stability measures potentially masking the ecological mechanism causing year‐to‐year fluctuations. As such, previous studies on community stability might have overemphasised the role of compensatory dynamics in real‐world ecosystems, and particularly in manipulative conditions, when not considering the possible overriding effects of long‐term directional trends

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

LOTVS: a global collection of permanent vegetation plots

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 plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 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

Functional traits trade-offs define plant population stability scross different biomes

Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species’ ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability

Directional trends in species composition over time can lead to a widespread overemphasis of year-to-year asynchrony

Questions. Compensatory dynamics are described as one of the main mechanisms that increase community stability, e.g., where decreases of some species on a year-to-year basis are offset by an increase in others. Deviations from perfect synchrony between species (asynchrony) have therefore been advocated as an important mechanism underlying biodiversity effects on stability. However, it is unclear to what extent existing measures of synchrony actually capture the signal of year-to-year species fluctuations in the presence of long-term directional trends in both species abundance and composition (species directional trends hereafter). Such directional trends may lead to a misinterpretation of indices commonly used to reflect year-to-year synchrony. Methods. An approach based on three-term local quadrat variance (T3) which assesses population variability in a three-year moving window, was used to overcome species directional trend effects. This "detrending" approach was applied to common indices of synchrony across a worldwide collection of 77 temporal plant community datasets comprising almost 7,800 individual plots sampled for at least six years. Plots included were either maintained under constant "control" conditions over time or were subjected to different management or disturbance treatments. Results. Accounting for directional trends increased the detection of year-to-year synchronous patterns in all synchrony indices considered. Specifically, synchrony values increased significantly in ~40% of the datasets with the T3 detrending approach while in ~10% synchrony decreased. For the 38 studies with both control and manipulated conditions, the increase in synchrony values was stronger for longer time series, particularly following experimental manipulation. Conclusions. Species' long-term directional trends can affect synchrony and stability measures potentially masking the ecological mechanism causing year-to-year fluctuations. As such, previous studies on community stability might have overemphasised the role of compensatory dynamics in real-world ecosystems, and particularly in manipulative conditions, when not considering the possible overriding effects of long-term directional trends

LOTVS: a global collection of permanent vegetation plots

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 plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 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

LOTVS: a global collection of permanent vegetation plots

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 plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 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