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  1. null (Ed.)
  2. Abstract

    Native biodiversity decline and non-native species spread are major features of the Anthropocene. Both processes can drive biotic homogenization by reducing trait and phylogenetic differences in species assemblages between regions, thus diminishing the regional distinctiveness of biotas and likely have negative impacts on key ecosystem functions. However, a global assessment of this phenomenon is lacking. Here, using a dataset of >200,000 plant species, we demonstrate widespread and temporal decreases in species and phylogenetic turnover across grain sizes and spatial extents. The extent of homogenization within major biomes is pronounced and is overwhelmingly explained by non-native species naturalizations. Asia and North America are major sources of non-native species; however, the species they export tend to be phylogenetically close to recipient floras. Australia, the Pacific and Europe, in contrast, contribute fewer species to the global pool of non-natives, but represent a disproportionate amount of phylogenetic diversity. The timeline of most naturalisations coincides with widespread human migration within the last ~500 years, and demonstrates the profound influence humans exert on regional biotas beyond changes in species richness.

     
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  3. null (Ed.)
  4. Abstract

    Species interactions drive ecosystem processes and are a major focus of global change research. Among the most consequential interactions expected to shift with climate change are those between insect herbivores and plants, both of which are highly sensitive to temperature. Insect herbivores and their host plants display varying levels of synchrony that could be disrupted or enhanced by climate change, yet empirical data on changes in synchrony are lacking. Using evidence of herbivory on herbarium specimens collected from the northeastern United States and France from 1900 to 2015, we provide evidence that plant species with temperature‐sensitive phenologies experience higher levels of insect damage in warmer years, while less temperature‐sensitive, co‐occurring species do not. While herbivory might be mediated by interactions between warming and phenology through multiple pathways, we suggest that warming might lengthen growing seasons for phenologically sensitive plant species, exposing their leaves to herbivores for longer periods of time in warm years. We propose that elevated herbivory in warm years may represent a previously underappreciated cost to phenological tracking of climate change over longer timescales.

     
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  5. Abstract Natural history collections (NHCs) are the foundation of historical baselines for assessing anthropogenic impacts on biodiversity. Along these lines, the online mobilization of specimens via digitization—the conversion of specimen data into accessible digital content—has greatly expanded the use of NHC collections across a diversity of disciplines. We broaden the current vision of digitization (Digitization 1.0)—whereby specimens are digitized within NHCs—to include new approaches that rely on digitized products rather than the physical specimen (Digitization 2.0). Digitization 2.0 builds on the data, workflows, and infrastructure produced by Digitization 1.0 to create digital-only workflows that facilitate digitization, curation, and data links, thus returning value to physical specimens by creating new layers of annotation, empowering a global community, and developing automated approaches to advance biodiversity discovery and conservation. These efforts will transform large-scale biodiversity assessments to address fundamental questions including those pertaining to critical issues of global change. 
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  6. 1. Predicting how ecological interactions will respond to global change is a major challenge. Plants and their associated insect herbivores compose much of macroscopic diversity, yet how their interactions have been altered by recent environmental change remains underexplored. 2. To address this gap, we quantified herbivory on herbarium specimens of four plant species with records extending back 112 years. Our study focused on the northeastern US, where temperatures have increased rapidly over the last few decades. This region also represents a range of urban development, a form of global change that has shown variable effects on herbivores in the past studies. 3. Herbarium specimens collected in the early 2000s were 23% more likely to be damaged by herbivores than those collected in the early 1900s. Herbivory was greater following warmer winters and at low latitudes, suggesting that climate warming may drive increasing insect damage over time. In contrast, human population densities were negatively associated with herbivore damage. 4. To explore whether changes in insect occurrence or abundance might explain shifts in herbivory, we used insect observational records to build climate occupancy models for lepidopteran herbivores (butterflies and moths) of our focal plant species. 5. These models show that higher winter temperatures were associated with higher probability of insect herbivore presence, while urbanization was associated with reduced probability of herbivore presence, supporting a link between insect herbivore occurrence and herbivory mediated through environment. 6. Synthesis. Using a temporal record of plant herbivory that spans over a century, we show that both temperature and urbanization influence insect damage to plants, but in very different ways. Our results indicate that damage to plants by insect herbivores will likely continue to increase through time in the northeastern US as global temperatures rise, but that urbanization may disrupt local effects of winter warming on herbivory by excluding certain herbivores. These changes may scale to shape ecosystem processes that are driven by herbivory, including plant productivity. 
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  7. Abstract Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth. 
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