Ecologists have worked to ascribe function to the variation found in plant populations, communities and ecosystems across environments for at least the past century. The vast body of research in functional ecology has drastically improved understanding of how individuals respond to their environment, communities are assembled and ecosystems function. However, with limited exceptions, few studies have quantified differences in plant function during the Drawing from the literature and our collective experience, we describe the current state of knowledge in seedling functional ecology and provide examples of how this subdiscipline can enrich our fundamental understanding of plant function across levels of organisation. To inspire progressive work in this area, we also outline key considerations involved in seedling functional research (who, what, when, where and how to measure seedling traits) and identify remaining challenges and gaps in understanding around methodological approaches. Within this conceptual synthesis, we highlight three critical areas in seedling ecology for future research to target. First, given wide variation in the definition of a ‘seedling’, we provide a standard definition based on seed reserve dependence while emphasising the need to measure ontogenetic variation more clearly both within and following the seedling stage. Second, studies demonstrate that seedlings can be studied in multiple media (e.g. soil, agar, filter paper) and conditions (e.g. field, greenhouse, laboratory). We recommend that researchers select methods based on explicit goals, yet follow standard guidelines to reduce methodological noise across studies. Third, research is critically needed to assess the implications of different methodologies on trait measurement and compatibility across studies. By highlighting the importance of seedling functional ecology and suggesting pathways to address key challenges, we aim to inspire future research that generates useful and comparable data on seedling functional ecology. This work is critical to explain variation within and among populations, communities and ecosystems and integrate this most vulnerable stage of plant life into ecological frameworks.
A long‐standing question in biology is how organisms change through time and space in response to their environment. This knowledge is of particular relevance to predicting how organisms might respond to future environmental changes caused by human‐induced global change. Usually researchers make inferences about past events based on an understanding of current static genetic patterns, but these are limited in their capacity to inform on underlying past processes. Natural history collections (NHCs) represent a unique and critical source of information to provide temporally deep and spatially broad time‐series of samples. By using NHC samples, researchers can directly observe genetic changes over time and space and link those changes with specific ecological/evolutionary events. Until recently, such genetic studies were hindered by the intrinsic challenges of NHC samples (i.e. low yield of highly fragmented DNA). However, recent methodological and technological developments have revolutionized the possibilities in the novel field of NHC genomics. In this Special Feature, we compile a range of studies spanning from methodological aspects to particular case studies which demonstrate the enormous potential of NHC samples for accessing large genomic data sets from the past to advance our knowledge on how populations and species respond to global change at multiple spatial–temporal scales. We also highlight possible limitations, recommendations and a few opportunities for future researchers aiming to study NHC genomics.
more » « less- NSF-PAR ID:
- 10454570
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- Volume:
- 20
- Issue:
- 5
- ISSN:
- 1755-098X
- Page Range / eLocation ID:
- p. 1153-1160
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract earliest stages of the plant life cycle, and fewer have tested how this early variability shapes populations, communities and ecosystems. -
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Abstract Historical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed to enable robust inferences. Occupancy–detection models, a relatively new and powerful suite of statistical methods, are a potentially promising avenue because they can account for changes in collection effort through space and time.
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Abstract Aim Climate and disturbance alter forest dynamics, from individual trees to biomes and from years to millennia, leaving legacies that vary with local, meso‐ and macroscales. Motivated by recent insights in temperate forests, we argue that temporal and spatial extents equivalent to that of the underlying drivers are necessary to characterize forest dynamics across scales. We focus specifically on characterizing mesoscale forest dynamics because they bridge fine‐scale (local) processes and the continental scale (macrosystems) in ways that are highly relevant for climate change science and ecosystem management. We revisit ecological concepts related to spatial and temporal scales and discuss approaches to gain a better understanding of climate–forest dynamics across scales.
Location Eastern USA.
Time period Last century to present.
Major taxa studied Temperate broadleaf forests.
Methods We review regional literature of past tree mortality studies associated with climate to identify mesoscale climate‐driven disturbance events. Using a dynamic vegetation model, we then simulate how these forests respond to a typical climate‐driven disturbance.
Results By identifying compound disturbance events from both a literature review and simulation modelling, we find that synchronous patterns of drought‐driven mortality at mesoscales have been overlooked within these forests.
Main conclusions As ecologists, land managers and policy‐makers consider the intertwined drivers of climate and disturbance, a focus on spatio‐temporal scales equivalent to those of the drivers will provide insight into long‐term forest change, such as drought impacts. Spatially extensive studies should also have a long temporal scale to provide insight into pathways for forest change, evaluate predictions from dynamic forest models and inform development of global vegetation models. We recommend integrating data collected from spatially well‐replicated networks (e.g., archaeological, historical or palaeoecological data), consisting of centuries‐long, high‐resolution records, with models to characterize better the mesoscale response of forests to climate change in the past and in the future.
