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   Berg, Emily; Fuller, Wayne A. (September 2018, Canadian Journal of Statistics)
2. Twin Cities Metro Area Road Surface Area, 2022

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   Marek-Spartz, Mary (January 2023, Data Repository for the University of Minnesota (DRUM))
3. Scaling relationships between lake surface area and catchment area

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4. Species-area and network-area relationships in host–helminth interactions

   https://doi.org/10.1098/rspb.2020.3143  

   Dallas, Tad A.; Jordano, Pedro (March 2021, Proceedings of the Royal Society B: Biological Sciences)

   The scaling relationship observed between species richness and the geographical area sampled (i.e. the species-area relationship (SAR)) is a widely recognized macroecological relationship. Recently, this theory has been extended to trophic interactions, suggesting that geographical area may influence the structure of species interaction networks (i.e. network-area relationships (NARs)). Here, we use a global dataset of host–helminth parasite interactions to test existing predictions from macroecological theory. Scaling between single locations to the global host–helminth network by sequentially adding networks together, we find support that geographical area influences species richness and the number of species interactions in host–helminth networks. However, species-area slopes were larger for host species relative to their helminth parasites, counter to theoretical predictions. Lastly, host–helminth network modularity—capturing the tendency of the network to form into separate subcommunities—decreased with increasing area, also counter to theoretical predictions. Reconciling this disconnect between existing theory and observed SAR and NAR will provide insight into the spatial structuring of ecological networks, and help to refine theory to highlight the effects of network type, species distributional overlap, and the specificity of trophic interactions on NARs. 

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5. Between-area communication through the lens of within-area neuronal dynamics

   https://doi.org/10.1126/sciadv.adl6120  

   Gozel, Olivia; Doiron, Brent (October 2024, Science Advances)

   A core problem in systems and circuits neuroscience is deciphering the origin of shared dynamics in neuronal activity: Do they emerge through local network interactions, or are they inherited from external sources? We explore this question with large-scale networks of spatially ordered spiking neuron models where a downstream network receives input from an upstream sender network. We show that linear measures of the communication between the sender and receiver networks can discriminate between emergent or inherited population dynamics. A match in the dimensionality of the sender and receiver population activities promotes faithful communication. In contrast, a nonlinear mapping between the sender to receiver activity, for example, through downstream emergent population-wide fluctuations, can impair linear communication. Our work exposes the benefits and limitations of linear measures when analyzing between-area communication in circuits with rich population-wide neuronal dynamics. 

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