Long-term ecological studies are critical for providing key insights in ecology, environmental change, natural resource management and biodiversity conservation. In this paper, we briefly discuss five key values of such studies. These are: (1) quantifying ecological responses to drivers of ecosystem change; (2) understanding complex ecosystem processes that occur over prolonged periods; (3) providing core ecological data that may be used to develop theoretical ecological models and to parameterize and validate simulation models; (4) acting as platforms for collaborative studies, thus promoting multidisciplinary research; and (5) providing data and understanding at scales relevant to management, and hence critically supporting evidence-based policy, decision making and the management of ecosystems. We suggest that the ecological research community needs to put higher priority on communicating the benefits of long-term ecological studies to resource managers, policy makers and the general public. Long-term research will be especially important for tackling large-scale emerging problems confronting humanity such as resource management for a rapidly increasing human population, mass species extinction, and climate change detection, mitigation and adaptation. While some ecologically relevant, long-term data sets are now becoming more generally available, these are exceptions. This deficiency occurs because ecological studies can be difficult to maintain for long periods as they exceed the length of government administrations and funding cycles. We argue that the ecological research community will need to coordinate ongoing efforts in an open and collaborative way, to ensure that discoverable long-term ecological studies do not become a long-term deficiency. It is important to maintain publishing outlets for empirical field-based ecology, while simultaneously developing new systems of recognition that reward ecologists for the use and collaborative sharing of their long-term data sets. Funding schemes must be re-crafted to emphasize collaborative partnerships between field-based ecologists, theoreticians and modellers, and to provide financial support that is committed over commensurate time frames.

A general understanding of biological invasions will provide insights into fundamental ecological and evolutionary problems and contribute to more efficient and effective prediction, prevention and control of invasions. We review recent papers that have proposed conceptual frameworks for invasion biology. These papers offer important advances and signal a maturation of the field, but a broad synthesis is still lacking. Conceptual frameworks for invasion do not require invocation of unique concepts, but rather should reflect the unifying principles of ecology and evolutionary biology. A conceptual framework should incorporate multicausality, include interactions between causal factors and account for lags between various stages. We emphasize the centrality of demography in invasions, and distinguish between explaining three of the most important characteristics by which we recognize invasions: rapid local population increase, monocultures or community dominance, and range expansion. As a contribution towards developing a conceptual synthesis of invasions based on these criteria, we outline a framework that explicitly incorporates consideration of the fundamental ecological and evolutionary processes involved. The development of a more inclusive and mechanistic conceptual framework for invasion should facilitate quantitative and testable evaluation of causal factors, and can potentially lead to a better understanding of the biology of invasions.

Summary1. Schedules of survival, growth and reproduction are key life-history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population *Correspondence author. E-mails: salguero@demogr.mpg.de; compadre-contact@demogr.mpg.de † Joint senior author. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. 2015, 103, 202-218 doi: 10.1111/1365-2745.12334 growth or decline, such data help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change and how to develop successful management tools for endangered or invasive species. Journal of Ecology2. Matrix population models summarize the life cycle components of survival, growth and reproduction, while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have direct biological interpretations, facilitating comparisons among populations and species. 3. Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer-reviewed and grey literature, and thus remain inaccessible for synthetic analysis. Here, we introduce the COMPADRE Plant Matrix Database version 3.0, an opensource online repository containing 468 studies from 598 species world-wide (672 species hits, when accounting for species studied in more than one source), with a total of 5621 matrices. COMPADRE also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices. 4. Synthesis. Large collections of data allow broad questions to be addressed at the global scale, for example, in genetics (GENBANK), functional plant ecology (TRY, BIEN, D3) and grassland community ecology (NUTNET). Here, we present COMPADRE, a similarly data-rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions.

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Biodiversity is declining in many local communities while also becoming increasingly homogenized across space. Experiments show that local plant species loss reduces ecosystem functioning and services, but the role of spatial homogenization of community composition and the potential interaction between diversity at different scales in maintaining ecosystem functioning remains unclear, especially when many functions are considered (ecosystem multifunctionality). We present an analysis of eight ecosystem functions measured in 65 grasslands worldwide. We find that more diverse grasslands-those with both species-rich local communities (α-diversity) and large compositional differences among localities (β-diversity)-had higher levels of multifunctionality. Moreover, α- and β-diversity synergistically affected multifunctionality, with higher levels of diversity at one scale amplifying the contribution to ecological functions at the other scale. The identity of species influencing ecosystem functioning differed among functions and across local communities, explaining why more diverse grasslands maintained greater functionality when more functions and localities were considered. These results were robust to variation in environmental drivers. Our findings reveal that plant diversity, at both local and landscape scales, contributes to the maintenance of multiple ecosystem services provided by grasslands. Preserving ecosystem functioning therefore requires conservation of biodiversity both within and among ecological communities.

Eutrophication is a widespread environmental change that usually reduces the stabilizing effect of plant diversity on productivity in local communities. Whether this effect is scale dependent remains to be elucidated. Here, we determine the relationship between plant diversity and temporal stability of productivity for 243 plant communities from 42 grasslands across the globe and quantify the effect of chronic fertilization on these relationships. Unfertilized local communities with more plant species exhibit greater asynchronous dynamics among species in response to natural environmental fluctuations, resulting in greater local stability (alpha stability). Moreover, neighborhood communities that have greater spatial variation in plant species composition within sites (higher beta diversity) have greater spatial asynchrony of productivity among communities, resulting in greater stability at the larger scale (gamma stability). Importantly, fertilization consistently weakens the contribution of plant diversity to both of these stabilizing mechanisms, thus diminishing the positive effect of biodiversity on stability at differing spatial scales. Our findings suggest that preserving grassland functional stability requires conservation of plant diversity within and among ecological communities.

Prescribed burning is a commonly applied management tool, and there has been considerable debate over the efficacy of its application. We review data relating to the effectiveness of prescribed burning in Australia. Specifically, we address two questions: (1) to what extent can fuel reduction burning reduce the risk of loss of human life and economic assets posed from wildfires? (2) To what extent can prescribed burning be used to reduce the risk of biodiversity loss? Data suggest that prescribed burning can achieve a reduction in the extent of wildfires; however, at such levels, the result is an overall increase in the total area of the landscape burnt. Simulation modelling indicates that fuel reduction has less influence than weather on the extent of unplanned fire. The need to incorporate ecological values into prescribed burning programmes is becoming increasingly important. Insufficient data are available to determine if existing programs have been successful. There are numerous factors that prevent the implementation of better prescribed burning practices; most relate to a lack of clearly defined, measurable objectives. An adaptive risk management framework combined with enhanced partnerships between scientists and fire-management agencies is necessary to ensure that ecological and fuel reduction objectives are achieved.

Explaining variation in population growth rates is fundamental to predicting population dynamics and population responses to environmental change. In this study, we used matrix population models, which link birth, growth and survival to population growth rate, to examine how and why population growth rates vary within and among 50 terrestrial plant species. Population growth rates were more similar within species than among species; with phylogeny having a minimal influence on among-species variation. Most population growth rates decreased over the observation period and were negatively autocorrelated between years; that is, higher than average population growth rates tended to be followed by lower than average population growth rates. Population growth rates varied more through time than space; this temporal variation was due mostly to variation in post-seedling survival and for a subset of species was partly explained by response to environmental factors, such as fire and herbivory. Stochastic population growth rates departed from mean matrix population growth rate for temporally autocorrelated environments. Our findings indicate that demographic data and models of closely related plant species cannot necessarily be used to make recommendations for conservation or control, and that post-seedling survival and the sequence of environmental conditions are critical for determining plant population growth rate.