Exploring differences in spatial patterns and temporal trends of phenological models at continental scale using gridded temperature time-series

Mehdipoor, Hamed; Zurita-Milla, R.; Augustijn, Ellen-Wien; Izquierdo‐Verdiguier, Emma

doi:10.1007/s00484-019-01826-7

Cited by 5 publications

(1 citation statement)

References 62 publications

(86 reference statements)

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“…have colocated equipment at hundreds of sites globally. This has led to numerous studies comparing the vegetative phenology, satellite remote sensing metrics, and carbon uptake dynamics of terrestrial ecosystems, ultimately making all these measurements more interoperable (Brown et al, 2016; Hufkens et al, 2018; Jeong & Medvigy, 2014; Mehdipoor et al, 2020; Peng et al, 2017; Rosemartin et al, 2018).…”

Section: Linking Networkmentioning

confidence: 99%

People, infrastructure, and data: A pathway to an inclusive and diverse ecological network of networks

et al. 2022

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Macrosystem‐scale research is supported by many ecological networks of people, infrastructure, and data. However, no network is sufficient to address all macrosystems ecology research questions, and there is much to be gained by conducting research and sharing resources across multiple networks. Unfortunately, conducting macrosystem research across networks is challenging due to the diversity of expertise and skills required, as well as issues related to data discoverability, veracity, and interoperability. The ecological and environmental science community could substantially benefit from networking existing networks to leverage past research investments and spur new collaborations. Here, we describe the need for a “network of networks” (NoN) approach to macrosystems ecological research and articulate both the challenges and potential benefits associated with such an effort. We describe the challenges brought by rapid increases in the volume, velocity, and variety of “big data” ecology and highlight how a NoN could build on the successes and creativity within component networks, while also recognizing and improving upon past failures. We argue that a NoN approach requires careful planning to ensure that it is accessible and inclusive, incorporates multimodal communications and ways to interact, supports the creation, testing, and promulgation of community standards, and ensures individuals and groups receive appropriate credit for their contributions. Additionally, a NoN must recognize important trade‐offs in network architecture, including how the degree of centralization of people, infrastructure, and data influence network scalability and creativity. If implemented carefully and thoughtfully, a NoN has the potential to substantially advance our understanding of ecological processes, characteristics, and trajectories across broad spatial and temporal scales in an efficient, inclusive, and equitable manner.

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