No abstract

No abstract

Summary1. Priority question exercises are becoming an increasingly common tool to frame future agendas in conservation and ecological science. They are an effective way to identify research foci that advance the field and that also have high policy and conservation relevance. 2. To date, there has been no coherent synthesis of key questions and priority research areas for palaeoecology, which combines biological, geochemical and molecular techniques in order to reconstruct past ecological and environmental systems on time-scales from decades to millions of years. 3. We adapted a well-established methodology to identify 50 priority research questions in palaeoecology. Using a set of criteria designed to identify realistic and achievable research goals, we selected questions from a pool submitted by the international palaeoecology research community and relevant policy practitioners. 4. The integration of online participation, both before and during the workshop, increased international engagement in question selection. 5. The questions selected are structured around six themes: human-environment interactions in the Anthropocene; biodiversity, conservation and novel ecosystems; biodiversity over long time-scales; ecosystem processes and biogeochemical cycling; comparing, combining and synthesizing information from multiple records; and new developments in palaeoecology. 6. Future opportunities in palaeoecology are related to improved incorporation of uncertainty into reconstructions, an enhanced understanding of ecological and evolutionary dynamics and processes and the continued application of long-term data for better-informed landscape management. 256-26750 priority research questions in palaeoecology 257 7. Synthesis. Palaeoecology is a vibrant and thriving discipline, and these 50 priority questions highlight its potential for addressing both pure (e.g. ecological and evolutionary, methodological) and applied (e.g. environmental and conservation) issues related to ecological science and global change.

Taxonomic identification of pollen and spores uses inherently qualitative descriptions of morphology. Consequently, identifications are restricted to categories that can be reliably classified by multiple analysts, resulting in the coarse taxonomic resolution of the pollen and spore record. Grass pollen represents an archetypal example; it is not routinely identified below family level. To address this issue, we developed quantitative morphometric methods to characterize surface ornamentation and classify grass pollen grains. This produces a means of quantifying morphological features that are traditionally described qualitatively. We used scanning electron microscopy to image 240 specimens of pollen from 12 species within the grass family (Poaceae). We classified these species by developing algorithmic features that quantify the size and density of sculptural elements on the pollen surface, and measure the complexity of the ornamentation they form. These features yielded a classification accuracy of 77.5%. In comparison, a texture descriptor based on modelling the statistical distribution of brightness values in image patches yielded a classification accuracy of 85.8%, and seven human subjects achieved accuracies between 68.33 and 81.67%. The algorithmic features we developed directly relate to biologically meaningful features of grass pollen morphology, and could facilitate direct interpretation of unsupervised classification results from fossil material.

Aim Climate is recognized for the significant role it plays in the global distribution of plant species diversity. We test the extent to which two aspects of climate, namely temperature and precipitation, explain the spatial distribution of high taxonomic groupings (plant families) at a regional spatial resolution (the Neotropics). Our goal is to provide a quantitative and comparative framework for identifying the local effects of climate on the familial composition of tropical forests by identifying the influence of climate on the number of individuals and the number of species within a given family.Location One hundred and forty-four 0.1-ha forest transect sites from the Neotropics (19.8°N-27.0°S and 40.1°W-105.1°W). Data were originally collected by A.H. Gentry.Methods Spatial variability in the abundance (density) and species richness of 159 tropical plant families across a range of predominately lowland Neotropical landscapes were attributed to eight temperature and precipitation measures using the eigen analysis method of two-field joint single-value decomposition.Results Climate significantly affects the within-clade diversity of several ecologically important Neotropical plant families. Intrafamily abundance and richness covary with temperature in some families (e.g. Fabaceae) and with precipitation in others (e.g. Bignoniaceae, Arecaceae), with differing climatic preferences observed even among co-occurring families. In addition, the familylevel composition of Neotropical forests, in both abundance and richness, appears to be influenced more by temperature than by precipitation. Among lowland families, only Asteraceae increased in species richness with decreasing temperature, although several families, including Melastomataceae and Rubiaceae, are more abundant at lower temperatures.Main conclusions Although plant diversity is known to vary as a function of climate at the species level, we document clear climatic preferences even at the rank of family. Temperature plays a stronger role in governing the familial composition of tropical forests, particularly in the richness of families, than might be expected given its narrow annual and diurnal range in the tropics. Although other environmental or geographic variables that covary with temperature may be more causally linked to diversity differences than temperature itself, the results nonetheless identify the taxonomic components of tropical forest composition that may be most affected by future climatic changes.

SummaryPollen is among the most ubiquitous of terrestrial fossils, preserving an extended record of vegetation change. However, this temporal continuity comes with a taxonomic tradeoff. Analytical methods that improve the taxonomic precision of pollen identifications would expand the research questions that could be addressed by pollen, in fields such as paleoecology, paleoclimatology, biostratigraphy, melissopalynology, and forensics.We developed a supervised, layered, instance-based machine-learning classification system that uses leave-one-out bias optimization and discriminates among small variations in pollen shape, size, and texture. We tested our system on black and white spruce, two paleoclimatically significant taxa in the North American Quaternary.We achieved > 93% grain-to-grain classification accuracies in a series of experiments with both fossil and reference material. More significantly, when applied to Quaternary samples, the learning system was able to replicate the count proportions of a human expert (R 2 = 0.78, P = 0.007), with one key difference -the machine achieved these ratios by including larger numbers of grains with low-confidence identifications.Our results demonstrate the capability of machine-learning systems to solve the most challenging palynological classification problem, the discrimination of congeneric species, extending the capabilities of the pollen analyst and improving the taxonomic resolution of the palynological record.

The emergence of macrosystems ecology (MSE), which focuses on regional‐ to continental‐scale ecological patterns and processes, builds upon a history of long‐term and broad‐scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi‐thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross‐scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them.

Research on the comparative morphology of pollen grains depends crucially on the application of appropriate microscopy techniques. Information on the performance of microscopy techniques can be used to inform that choice. We compared the ability of several microscopy techniques to provide information on the shape and surface texture of three pollen types with differing morphologies. These techniques are: widefield, apotome, confocal and two-photon microscopy (reflected light techniques), and brightfield and differential interference contrast microscopy (DIC) (transmitted light techniques). We also provide a first view of pollen using super-resolution microscopy. The three pollen types used to contrast the performance of each technique are: Croton hirtus (Euphorbiaceae), Mabea occidentalis (Euphorbiaceae) and Agropyron repens (Poaceae). No single microscopy technique provided an adequate picture of both the shape and surface texture of any of the three pollen types investigated here. The wavelength of incident light, photon-collection ability of the optical technique, signal-to-noise ratio, and the thickness and light absorption characteristics of the exine profoundly affect the recovery of morphological information by a given optical microscopy technique. Reflected light techniques, particularly confocal and two-photon microscopy, best capture pollen shape but provide limited information on very fine surface texture. In contrast, transmitted light techniques, particularly differential interference contrast microscopy, can resolve very fine surface texture but provide limited information on shape. Texture comprising sculptural elements that are spaced near the diffraction limit of light (∼250 nm; NDL) presents an acute challenge to optical microscopy. Super-resolution structured illumination microscopy provides data on the NDL texture of A. repens that is more comparable to textural data from scanning electron microscopy than any other optical microscopy technique investigated here. Maximizing the recovery of morphological information from pollen grains should lead to more robust classifications, and an increase in the taxonomic precision with which ancient vegetation can be reconstructed.