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1. Diversification Models Conflate Likelihood and Prior, and Cannot be Compared Using Conventional Model-Comparison Tools

   https://doi.org/10.1093/sysbio/syad010  

   May, Michael R. ; Rothfels, Carl J. ; Hoehna, ed., Sebastian ( March 2023 , Systematic Biology)

   Time-calibrated phylogenetic trees are a tremendously powerful tool for studying evolutionary, ecological, and epidemiological phenomena. Such trees are predominantly inferred in a Bayesian framework, with the phylogeny itself treated as a parameter with a prior distribution (a “tree prior”). However, we show that the tree “parameter” consists, in part, of data, in the form of taxon samples. Treating the tree as a parameter fails to account for these data and compromises our ability to compare among models using standard techniques (e.g., marginal likelihoods estimated using path-sampling and stepping-stone sampling algorithms). Since accuracy of the inferred phylogeny strongly depends on how well the tree prior approximates the true diversification process that gave rise to the tree, the inability to accurately compare competing tree priors has broad implications for applications based on time-calibrated trees. We outline potential remedies to this problem, and provide guidance for researchers interested in assessing the fit of tree models. [Bayes factors; Bayesian model comparison; birth-death models; divergence-time estimation; lineage diversification]

    

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2. Using unoccupied aerial vehicles to map and monitor changes in emergent kelp canopy after an ecological regime shift

   https://doi.org/10.1002/rse2.295  

   Saccomanno, Vienna R. ; Bell, Tom ; Pawlak, Camille ; Stanley, Charlotte K. ; Cavanaugh, Katherine C. ; Hohman, Rietta ; Klausmeyer, Kirk R. ; Cavanaugh, Kyle ; Nickels, Abby ; Hewerdine, Waz ; et al ( February 2023 , Remote Sensing in Ecology and Conservation)

   Kelp forests are complex underwater habitats that form the foundation of many nearshore marine environments and provide valuable services for coastal communities. Despite their ecological and economic importance, increasingly severe stressors have resulted in declines in kelp abundance in many regions over the past few decades, including the North Coast of California, USA. Given the significant and sustained loss of kelp in this region, management intervention is likely a necessary tool to reset the ecosystem and geospatial data on kelp dynamics are needed to strategically implement restoration projects. Because canopy‐forming kelp forests are distinguishable in aerial imagery, remote sensing is an important tool for documenting changes in canopy area and abundance to meet these data needs. We used small unoccupied aerial vehicles (UAVs) to survey emergent kelp canopy in priority sites along the North Coast in 2019 and 2020 to fill a key data gap for kelp restoration practitioners working at local scales. With over 4,300 hectares surveyed between 2019 and 2020, these surveys represent the two largest marine resource‐focused UAV surveys conducted in California to our knowledge. We present remote sensing methods using UAVs and a repeatable workflow for conducting consistent surveys, creating orthomosaics, georeferencing data, classifying emergent kelp and creating kelp canopy maps that can be used to assess trends in kelp canopy dynamics over space and time. We illustrate the impacts of spatial resolution on emergent kelp canopy classification between different sensors to help practitioners decide which data stream to select when asking restoration and management questions at varying spatial scales. Our results suggest that high spatial resolution data of emergent kelp canopy from UAVs have the potential to advance strategic kelp restoration and adaptive management.

    

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3. Leaf angle measurements for temperate tree species in northeastern USA

   https://doi.org/10.6073/pasta/faa03b13e5eab16a5e46a4ba0c2123e5  

   Hastings, Jack H ; Baillargeon, Kaitlyn ; Ouimette, Andrew P ; Ollinger, Scott V ( January 2023 , Environmental Data Initiative)

   Leaf angle distribution (LAD) measurements were made during the growing season in 2021 at the Harvard Forest in Petersham, MA, USA, and in 2022 at the Thompson Farm Earth Systems Observatory in Durham, NH, USA. At both sites, a level-calibrated digital angle tool was used to measure LAD in upper canopy foliage of common northeastern temperate tree species accessed using a mobile canopy lift. Additionally, at Thompson Farm, measurements were made at multiple heights to characterize differences of LAD in high, middle, and low canopy positions. Here, we have published those measurements, including a summary table of species average leaf angles and calculated parameters for fitted beta distributions. Processing scripts can be made available upon request to the authors. Additionally, leaf chemical, physical, structure, optical and physiological traits have been measured at these site as well as canopy scale measures of structure and UAV-based spectral, thermal, and lidar imagery. 

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4. Epiphytic fungal communities vary by substrate type and at submetre spatial scales

   https://doi.org/10.1111/mec.16358  

   Cook, Kel ; Sharma, Jyotsna ; Taylor, Andrew D. ; Herriott, Ian ; Taylor, D. Lee ( February 2022 , Molecular Ecology)

   Fungal species have numerous important environmental functions. Where these functions occur will depend on how fungi are spatially distributed, but the spatial structures of fungal communities are largely unknown, especially in understudied hyperdiverse tropical tree canopy systems. Here we explore fungal communities in a Costa Rican tropical rainforest canopy, with a focus on local‐scale spatial structure and substrate specificity of fungi. Samples of ~1 cm³were collected from 135 points along five adjacent tree branches, with intersample distances from 1 to 800 cm, and dissected into four substrates: outer host tree bark, inner bark, dead bryophytes and living bryophytes. We sequenced the ITS2 region to characterize total fungal communities. Fungal community composition and diversity varied among substrate types, even when multiple substrates were in direct contact. Fungi were most diverse in living bryophytes, with 39% of all operational taxonomic units (OTUs) found exclusively in this substrate, and the least diverse in inner bark. Fungal communities had significant positive spatial autocorrelation and distance decay of similarity only at distances less than 1 m. Similarity among samples declined by half in less than 10 cm, and even at these short distances, similarities were low with few OTUs shared among samples. These results indicate that community turnover is high and occurs at very small spatial scales, with any two locations sharing very few fungi in common. High heterogeneity of fungal communities in space and among substrates may have implications for the distributions, population dynamics and diversity of other tree canopy organisms, including epiphytic plants.

    

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5. Mapping Temperate Forest Phenology Using Tower, UAV, and Ground-Based Sensors

   https://doi.org/10.3390/drones4030056  

   Atkins, Jeff W. ; Stovall, Atticus E. ; Yang, Xi ( September 2020 , Drones)

   null (Ed.)

   Phenology is a distinct marker of the impacts of climate change on ecosystems. Accordingly, monitoring the spatiotemporal patterns of vegetation phenology is important to understand the changing Earth system. A wide range of sensors have been used to monitor vegetation phenology, including digital cameras with different viewing geometries mounted on various types of platforms. Sensor perspective, view-angle, and resolution can potentially impact estimates of phenology. We compared three different methods of remotely sensing vegetation phenology—an unoccupied aerial vehicle (UAV)-based, downward-facing RGB camera, a below-canopy, upward-facing hemispherical camera with blue (B), green (G), and near-infrared (NIR) bands, and a tower-based RGB PhenoCam, positioned at an oblique angle to the canopy—to estimate spring phenological transition towards canopy closure in a mixed-species temperate forest in central Virginia, USA. Our study had two objectives: (1) to compare the above- and below-canopy inference of canopy greenness (using green chromatic coordinate and normalized difference vegetation index) and canopy structural attributes (leaf area and gap fraction) by matching below-canopy hemispherical photos with high spatial resolution (0.03 m) UAV imagery, to find the appropriate spatial coverage and resolution for comparison; (2) to compare how UAV, ground-based, and tower-based imagery performed in estimating the timing of the spring phenological transition. We found that a spatial buffer of 20 m radius for UAV imagery is most closely comparable to below-canopy imagery in this system. Sensors and platforms agree within +/− 5 days of when canopy greenness stabilizes from the spring phenophase into the growing season. We show that pairing UAV imagery with tower-based observation platforms and plot-based observations for phenological studies (e.g., long-term monitoring, existing research networks, and permanent plots) has the potential to scale plot-based forest structural measures via UAV imagery, constrain uncertainty estimates around phenophases, and more robustly assess site heterogeneity. 

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