More Like this

1. Geography of artiodactyl locomotor morphology as an environmental predictor

   https://doi.org/10.1111/ddi.13371  

   Short, Rachel A. ; Lawing, A. Michelle ; Thomassen, ed., Henri ( July 2021 , Diversity and Distributions)

   We investigate locomotor function in artiodactyls, represented by calcaneal gear ratio, as it relates to multiple environments. Using an ecometric approach, we develop a trait–environment model to investigate ecosystem‐level changes through time and to reconstruct past environments. We apply the trait–environment model to a case study of six sites in Kenya to evaluate changes over the past 100 years.

   Global.

   Locomotor morphology was represented by calcaneal gear ratios measured as the overall length of a calcaneum divided by length of its in‐lever, that is calcaneal tuber. We collected calcaneal gear ratio measurements from skeletal specimens of 157 artiodactyl species in museum collections and used species’ spatial distributions to determine the composition of 47,420 communities globally. For 21,827 communities with three or more species of artiodactyls, we used maximum likelihood to model ecometric relationships between community‐level locomotor morphology and five environmental variables, including mean annual temperature, annual precipitation, elevation, vegetation cover and ecoregion province.

   Community mean gear ratios range from 1.43 to 1.56 (µ = 1.50). Mean gear ratios are highest in the tropical regions and lowest in the mid‐latitudes. Variance in mean calcaneal gear ratio is related to ecoregion division (68.6%), vegetation cover (63.5%) and precipitation (60.7%). In a case study of Kenyan sites, we demonstrate habitat homogenization patterns that match mammal community turnover patterns.

   With this ecometric framework, fossils of artiodactyl post‐crania can be used to assist in interpreting past ecoregion, vegetation cover and precipitation for a more comprehensive understanding of palaeoenvironment. These relationships between functional traits and environment will enable better models of biotic responses for conservation of functional diversity under changing environments.

    

   more » « less
2. Examining variation in the leaf mass per area of dominant species across two contrasting tropical gradients in light of community assembly

   https://doi.org/10.1002/ece3.2281  

   Neyret, Margot ; Bentley, Lisa Patrick ; Oliveras, Imma ; Marimon, Beatriz S. ; Marimon‐Junior, Ben Hur ; Almeida de Oliveira, Edmar ; Barbosa Passos, Fábio ; Castro Ccoscco, Rosa ; dos Santos, Josias ; Matias Reis, Simone ; et al ( July 2016 , Ecology and Evolution)

   Understanding variation in key functional traits across gradients in high diversity systems and the ecology of community changes along gradients in these systems is crucial in light of conservation and climate change. We examined inter‐ and intraspecific variation in leaf mass per area (LMA) of sun and shade leaves along a 3330‐m elevation gradient in Peru, and in sun leaves across a forest–savanna vegetation gradient in Brazil. We also comparedLMAvariance ratios (T‐statistics metrics) to null models to explore internal (i.e., abiotic) and environmental filtering on community structure along the gradients. Community‐weightedLMAincreased with decreasing forest cover in Brazil, likely due to increased light availability and water stress, and increased with elevation in Peru, consistent with the leaf economic spectrum strategy expected in colder, less productive environments. A very high species turnover was observed along both environmental gradients, and consequently, the first source of variation inLMAwas species turnover. Variation inLMAat the genus or family levels was greater in Peru than in Brazil. Using dominant trees to examine possible filters on community assembly, we found that in Brazil, internal filtering was strongest in the forest, while environmental filtering was observed in the dry savanna. In Peru, internal filtering was observed along 80% of the gradient, perhaps due to variation in taxa or interspecific competition. Environmental filtering was observed at cloud zone edges and in lowlands, possibly due to water and nutrient availability, respectively. These results related to variation inLMAindicate that biodiversity in species rich tropical assemblages may be structured by differential niche‐based processes. In the future, specific mechanisms generating these patterns of variation in leaf functional traits across tropical environmental gradients should be explored.

    

   more » « less
3. Small Mammal Exclosure Study (SMES) Vegetation Data from the Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2009)

   https://doi.org/10.6073/pasta/84841a70dd8cc89b9a5716e3511cc3a4  

   Lightfoot, David ; Rudgers, Jennifer A ( January 2021 , Environmental Data Initiative)

   This is data for vegetation canopy cover measured from each of the SMES study plots. Vegetation canopy cover was measured from each of the 36 one-meter2 quadrats twice each year. Animal consumers have important roles in ecosystems, determining plant species composition and structure, regulating rates of plant production and nutrient, and altering soil structure and chemistry. The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. What role if any do indigenous small mammal consumers have in maintaining desertified landscapes in the Chihuahuan Desert? Additionally, how do the effects of small mammals interact with changing climate to affect vegetation patterns over time? This study will provide long-term experimental tests of the roles of consumers on ecosystem pattern and process across a latitudinal climate gradient. The following questions or hypotheses will be addressed. 1) Do small mammals influence patterns of plant species composition and diversity, vegetation structure, and spatial patterns of vegetation canopy cover and biomass in Chihuahuan Desert shrublands and grasslands? Are small mammals keystone species that determine plant species composition and physiognomy of Chihuahuan Desert communities? Do small mammals have a significant role in maintaining the existence of shrub islands and spatial heterogeneity of creosotebush shrub communities? 2) Do small mammals affect the taxonomic composition and spatial pattern of vegetation similarly or differently in grassland communities as compared to shrub communities? How do patterns compare between grassland and shrubland sites, and how do these relatively small scale patterns relate to overall landscape vegetation patterns? 3) Do small mammals interact with short-term (annual) and long-term (decades) climate change to affect temporal changes in vegetation spatial patterns and species composition? 4) Do small mammals interact with other herbivore and granivore consumers enough to affect the species composition and abundances of other consumers such as ants and grasshoppers? 

   more » « less
4. Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland

   Stephanie Pau ; Jesse B. Nippert ; Ryan Slapikas ; Daniel Griffith ; Seton Bachle ; Brent R. Helliker ; Rory C. O’Connor ; William J. Riley ; Christopher J. Still ; Marissa Zaricor ( January 2022 , Ecology)

   Elizabeth Borer (Ed.)

   Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Ecological Observatory Network’s (NEON’s) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high-resolution trait mapping. We tested the accuracy of readily available data products of NEON’s AOP, such as Leaf Area Index (LAI), Total Biomass, Ecosystem Structure (Canopy height model [CHM]), and Canopy Nitrogen, by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The strongest relationships were between AOP LAI and ground-measured LAI (r = 0.32) and AOP Total Biomass and ground-measured biomass (r = 0.23). We also examined how well the full reflectance spectra (380–2,500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression (PLSR) models. Among all the eight traits examined, only Nitrogen had a validation of more than 0.25. For all vegetation traits, validation ranged from 0.08 to 0.29 and the range of the root mean square error of prediction (RMSEP) was 14–64%. Our results suggest that currently available AOP-derived data products should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although careful consideration of field and AOP data mismatches in space and/or time, biases in field-based measurements or AOP algorithms, and model uncertainty are needed. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area, mixed functional types of plant communities, and heterogeneous mosaics of disturbance and resource availability. Remote sensing observations are one of the most promising approaches to understanding ecological patterns across space and time. But the opportunity to engage a diverse community of NEON data users will depend on establishing rigorous links with in-situ field measurements across a diversity of sites. 

   more » « less
5. Poor relationships between NEON Airborne Observation Platform data and field‐based vegetation traits at a mesic grassland

   https://doi.org/10.1002/ecy.3590  

   Pau, Stephanie ; Nippert, Jesse B. ; Slapikas, Ryan ; Griffith, Daniel ; Bachle, Seton ; Helliker, Brent R. ; O’Connor, Rory C. ; Riley, William J. ; Still, Christopher J. ; Zaricor, Marissa ( December 2021 , Ecology)

   Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Ecological Observatory Network’s (NEON’s) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high‐resolution trait mapping. We tested the accuracy of readily available data products of NEON’s AOP, such as Leaf Area Index (LAI), Total Biomass, Ecosystem Structure (Canopy height model [CHM]), and Canopy Nitrogen, by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The strongest relationships were between AOP LAI and ground‐measured LAI (r = 0.32) and AOP Total Biomass and ground‐measured biomass (r = 0.23). We also examined how well the full reflectance spectra (380–2,500 nm), as opposed to derived products, could predict vegetation traits using partial least‐squares regression (PLSR) models. Among all the eight traits examined, only Nitrogen had a validation of more than 0.25. For all vegetation traits, validation ranged from 0.08 to 0.29 and the range of the root mean square error of prediction (RMSEP) was 14–64%. Our results suggest that currently available AOP‐derived data products should not be used without extensive ground‐based validation. Relationships using the full reflectance spectra may be more promising, although careful consideration of field and AOP data mismatches in space and/or time, biases in field‐based measurements or AOP algorithms, and model uncertainty are needed. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area, mixed functional types of plant communities, and heterogeneous mosaics of disturbance and resource availability. Remote sensing observations are one of the most promising approaches to understanding ecological patterns across space and time. But the opportunity to engage a diverse community of NEON data users will depend on establishing rigorous links with in‐situ field measurements across a diversity of sites.

    

   more » « less