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1. Fundamental ecological research is both intrinsically interesting and provides the basic knowledge required to answer applied questions of importance to the management of the natural world. The 100th anniversary of the British Ecological Society in 2013 is an opportune moment to reflect on the current status of ecology as a science and look forward to high-light priorities for future work. 2. To do this, we identified 100 important questions of fundamental importance in pure ecology. We elicited questions from ecologists working across a wide range of systems and disciplines. The 754 questions submitted (listed in the online appendix) from 388 participants were narrowed down to the final 100 through a process of discussion, rewording and repeated rounds of voting. This was done during a two-day workshop and thereafter. 3. The questions reflect many of the important current conceptual and technical pre-occupations of ecology. For example, many questions concerned the dynamics of environmental change and complex ecosystem interactions, as well as the interaction between ecology and evolution. 4. The questions reveal a dynamic science with novel subfields emerging. For example, a group of questions was dedicated to disease and micro-organisms and another on human impacts and global change reflecting the emergence of new subdisciplines that would not have been foreseen a few decades ago. 5. The list also contained a number of questions that have perplexed ecologists for decades and are still seen as crucial to answer, such as the link between population dynamics and life-history evolution. 6. Synthesis. These 100 questions identified reflect the state of ecology today. Using them as an agenda for further research would lead to a substantial enhancement in understanding of the discipline, with practical relevance for the conservation of biodiversity and ecosystem function.

AIM: The variation in species composition among sites, or beta diversity, can be decomposed into replacement and richness difference. A debate is ongoing in the literature concerning the best ways of computing and interpreting these indices. This paper first reviews the historical development of the formulae for decomposing dissimilarities into replacement, richness difference and nestedness indices. These formulae are presented for species presence–absence and abundance using a unified algebraic framework. The indices decomposing beta play different roles in ecological analysis than do beta‐diversity indices. INNOVATION: Replacement and richness difference indices can be interpreted and related to ecosystem processes. The pairwise index values can be summed across all pairs of sites; these sums form a valid decomposition of total beta diversity into total replacement and total richness difference components. Different communities and study areas can be compared: some may be dominated by replacement, others by richness/abundance difference processes. Within a region, differences among sites measured by these indices can then be analysed and interpreted using explanatory variables or experimental factors. The paper also shows that local contributions of replacement and richness difference to total beta diversity can be computed and mapped. A case study is presented involving fish communities along a river. MAIN CONCLUSIONS: The different forms of indices are based upon the same functional numerators. These indices are complementary; they can help researchers understand different aspects of ecosystem functioning. The methods of analysis used in this paper apply to any of the indices recently proposed. Further work, based on ecological theory and numerical simulations, is required to clarify the precise meaning and domain of application of the different forms. The forms available for presence–absence and quantitative data are both useful because these different data types allow researchers to answer different types of ecological or biogeographic questions.

1. Although there is ample support for positive species richness–productivity relationships in planted grassland experiments, a recent 48‐site study found no diversity–productivity relationship (DPR) in herbaceous communities. Thus, debate persists about diversity effects in natural versus planted systems. Additionally, current knowledge is weak regarding the influence of evenness on the DPRs, how DPRs are affected by the variation in life‐history traits among constituent species in polycultures and how DPRs differ among biomes. The impacts of these factors on DPRs in forest ecosystems are even more poorly understood. 2. We performed a meta‐analysis of 54 studies to reconcile DPRs in forest ecosystems. We quantified the net diversity effect as log effect size [ln(ES)], the log ratio of the productivity in polycultures to the average of those in monocultures within the same type of mixture, site condition and stand age of each study. The first use of a boosted regression tree model in meta‐analysis, a useful method to partition the effects of multiple predictors rather than relying on vote‐counting of individual studies, unveiled the relative influences of individual predictors. 3. Global average ln(ES) was 0.2128, indicating 23.7% higher productivity in polycultures than monocultures. The final model explained 21% of the variation in ln(ES). The predictors that substantially accounted for the explained variation included evenness (34%), heterogeneity of shade tolerance (29%), richness (13%) and stand age (15%). In contrast, heterogeneity of nitrogen fixation and growth habits, biome and stand origin (naturally established versus planted) contributed negligibly (each ≤ 4%). Log effect size strongly increased with evenness from 0.6 to 1 and with richness from 2 to 6. Furthermore, it was higher with heterogeneity of shade tolerance and generally increased with stand age. 4. Synthesis. Our analysis is, to our knowledge, the first to demonstrate the critical role of species evenness, richness and the importance of contrasting traits in defining net diversity effects in forest polycultures. While testing the specific mechanisms is beyond the scope of our analysis, our results should motivate future studies to link richness, evenness, contrasting traits and life‐history stage to the mechanisms that are expected to produce positive net biodiversity effects such as niche differentiation, facilitation and reduced Janzen–Connell effects.

The relationship between stomatal conductance (gₛ) and leaf water potential (Ψₗ) is key to the understanding of plant function under changing climate. The variability among tree species gave rise to selection towards either of two contrasting water management types: isohydric or anisohydric. This study explores the variability of gₛ to Ψₗ across tree species. Curves of gₛ(Ψₗ) were collected from the scientific literature for 70 woody plant species. The data set is comprised of angiosperm and gymnosperm species from all major forest biomes. The hypothesis that curves from different tree species diverge between isohydric and anisohydric behaviours was tested. Species‐specific curves formed a continuum, rather than dichotomy between isohydric and anisohydric, as confirmed by distribution models. Alternatively, the water potential at 50% of the maximum gₛ (Ψgₛ50) was used to quantitatively compare between species. A major difference emerged among xylem anatomy classes whereby ring‐porous species had higher absolute gₛ at Ψₗ < −2 MPa than diffuse‐porous and coniferous species. A positive, linear correlation was shown between Ψgₛ50 and Ψₗ at 50% loss of xylem conductivity. The results suggest that stomatal sensitivity to leaf water potential strongly relates to xylem characteristics. The use of Ψgₛ50 offers a quantitative alternative to the current, yet biased, distinction between isohydric and anisohydric species.

It is clear that the majority of flowering plants are pollinated by insects and other animals, with a minority utilising abiotic pollen vectors, mainly wind. However there is no accurate published calculation of the proportion of the ca 352 000 species of angiosperms that interact with pollinators. Widely cited figures range from 67% to 96% but these have not been based on firm data. We estimated the number and proportion of flowering plants that are pollinated by animals using published and unpublished community-level surveys of plant pollination systems that recorded whether each species present was pollinated by animals or wind. The proportion of animal-pollinated species rises from a mean of 78% in temperate-zone communities to 94% in tropical communities. By correcting for the latitudinal diversity trend in flowering plants, we estimate the global number and proportion of animal pollinated angiosperms as 308 006, which is 87.5% of the estimated species-level diversity of flowering plants. Given current concerns about the decline in pollinators and the possible resulting impacts on both natural communities and agricultural crops, such estimates are vital to both ecologists and policy makers. Further research is required to assess in detail the absolute dependency of these plants on their pollinators, and how this varies with latitude and community type, but there is no doubt that plant-pollinator interactions play a significant role in maintaining the functional integrity of most terrestrial ecosystems.

1. The study of plant-pollinator interactions in a network context is receiving increasing attention. This approach has helped to identify several emerging network patterns such as nestedness and modularity. However, most studies are based only on qualitative information, and some ecosystems, such as deserts and tropical forests, are underrepresented in these data sets. 2. We present an exhaustive analysis of the structure of a 4-year plant-pollinator network from the Monte desert in Argentina using qualitative and quantitative tools. We describe the structure of this network and evaluate sampling completeness using asymptotic species richness estimators. Our goal is to assess the extent to which the realized sampling effort allows for an accurate description of species interactions and to estimate the minimum number of additional censuses required to detect 90% of the interactions. We evaluated completeness of detection of the community-wide pollinator fauna, of the pollinator fauna associated with each plant species and of the plant-pollinator interactions. We also evaluated whether sampling completeness was influenced by plant characteristics, such as flower abundance, flower life span, number of interspecific links (degree) and selectiveness in the identity of their flower visitors, as well as sampling effort. 3. We found that this desert plant-pollinator network has a nested structure and that it exhibits modularity and high network-level generalization. 4. In spite of our high sampling effort, and although we sampled 80% of the pollinator fauna, we recorded only 55% of the interactions. Furthermore, although a 64% increase in sampling effort would suffice to detect 90% of the pollinator species, a fivefold increase in sampling effort would be necessary to detect 90% of the interactions. 5. Detection of interactions was incomplete for most plant species, particularly specialists with a long flowering season and high flower abundance, or generalists with short flowering span and scant flowers. Our results suggest that sampling of a network with the same effort for all plant species is inadequate to sample interactions. 6. Sampling the diversity of interactions is labour intensive, and most plant-pollinator networks published to date are likely to be undersampled. Our analysis allowed estimating the completeness of our sampling, the additional effort needed to detect most interactions and the plant traits that influence the detection of their interactions.

Biodiversity is important for many ecosystem processes. Global declines in pollinator diversity and abundance have been recognized, raising concerns about a pollination crisis of crops and wild plants. However, experimental evidence for effects of pollinator species diversity on plant reproduction is extremely scarce. We established communities with 1-5 bee species to test how seed production of a plant community is determined by bee diversity. Higher bee diversity resulted in higher seed production, but the strongest difference was observed for one compared to more than one bee species. Functional complementarity among bee species had a far higher explanatory power than bee diversity, suggesting that additional bee species only benefit pollination when they increase coverage of functional niches. In our experiment, complementarity was driven by differences in flower and temperature preferences. Interspecific interactions among bee species contributed to realized functional complementarity, as bees reduced interspecific overlap by shifting to alternative flowers in the presence of other species. This increased the number of plant species visited by a bee community and demonstrates a new mechanism for a biodiversity-function relationship (\"interactive complementarity\"). In conclusion, our results highlight both the importance of bee functional diversity for the reproduction of plant communities and the need to identify complementarity traits for accurately predicting pollination services by different bee communities.

Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

ANOSIM, PERMANOVA, and the Mantel test are all resemblance-based permutation methods widely used in ecology. Here, we report the results of the first simulation study, to our knowledge, specifically designed to examine the effects of heterogeneity of multivariate dispersions on the rejection rates of these tests and on a classical MANOVA test (Pillai's trace). Increasing differences in dispersion among groups were simulated under scenarios of changing sample sizes, correlation structures, error distributions, numbers of variables, and numbers of groups for balanced and unbalanced one-way designs. The power of these tests to detect environmental impacts or natural large-scale biogeographic gradients was also compared empirically under simulations based on parameters derived from real ecological data sets. Overall, ANOSIM and the Mantel test were very sensitive to heterogeneity in dispersions, with ANOSIM generally being more sensitive than the Mantel test. In contrast, PERMANOVA and Pillai's trace were largely unaffected by heterogeneity for balanced designs. PERMANOVA was also unaffected by differences in correlation structure, unlike Pillai's trace. For unbalanced designs, however, all of the tests were (1) too liberal when the smaller group had greater dispersion and (2) overly conservative when the larger group had greater dispersion, especially ANOSIM and the Mantel test. For simulations based on real ecological data sets, PERMANOVA was generally, but not always, more powerful than the others to detect changes in community structure, and the Mantel test was usually more powerful than ANOSIM. Both the error distributions and the resemblance measure affected results concerning power. Differences in the underlying construction of these test statistics result in important differences in the nature of the null hypothesis they are testing, their sensitivity to heterogeneity, and their power to detect important changes in ecological communities. For balanced designs, PERMANOVA and PERMDISP can be used to rigorously identify location vs. dispersion effects, respectively, in the space of the chosen resemblance measure. ANOSIM and the Mantel test can be used as more \"omnibus\" tests, being sensitive to differences in location, dispersion or correlation structure among groups. Unfortunately, none of the tests (PERMANOVA, Mantel, or ANOSIM) behaved reliably for unbalanced designs in the face of heterogeneity.