An in situ approach to detect tree root ecology: linking ground‐penetrating radar imaging to isotope‐derived water acquisition zones

Tree root distribution and activity are determinants of belowground competition. However, studying root response to environmental and management conditions remains logistically challenging. Methodologically, nondestructive in situ tree root ecology analysis has lagged. In this study, we tested a nondestructive approach to determine tree coarse root architecture and function of a perennial tree crop, Theobroma cacao L., at two edaphically contrasting sites (sandstone and phyllite–granite derived soils) in Ghana, West Africa. We detected coarse root vertical distribution using ground‐penetrating radar and root activity via soil water acquisition using isotopic matching of δ¹⁸O plant and soil signatures. Coarse roots were detected to a depth of 50 cm, however, intraspecifc coarse root vertical distribution was modified by edaphic conditions. Soil δ¹⁸O isotopic signature declined with depth, providing conditions for plant–soil δ¹⁸O isotopic matching. This pattern held only under sandstone conditions where water acquisition zones were identifiably narrow in the 10–20 cm depth but broader under phyllite–granite conditions, presumably due to resource patchiness. Detected coarse root count by depth and measured fine root density were strongly correlated as were detected coarse root count and identified water acquisition zones, thus validating root detection capability of ground‐penetrating radar, but exclusively on sandstone soils. This approach was able to characterize trends between intraspecific root architecture and edaphic‐dependent resource availability, however, limited by site conditions. This study successfully demonstrates a new approach for in situ root studies that moves beyond invasive point sampling to nondestructive detection of root architecture and function. We discuss the transfer of such an approach to answer root ecology questions in various tree‐based landscapes.     

MODISTools – downloading and processing MODIS remotely sensed data in R

Remotely sensed data – available at medium to high resolution across global spatial and temporal scales – are a valuable resource for ecologists. In particular, products from NASA's MODerate‐resolution Imaging Spectroradiometer (MODIS), providing twice‐daily global coverage, have been widely used for ecological applications. We present MODISTools, an R package designed to improve the accessing, downloading, and processing of remotely sensed MODIS data. MODISTools automates the process of data downloading and processing from any number of locations, time periods, and MODIS products. This automation reduces the risk of human error, and the researcher effort required compared to manual per‐location downloads. The package will be particularly useful for ecological studies that include multiple sites, such as meta‐analyses, observation networks, and globally distributed experiments. We give examples of the simple, reproducible workflow that MODISTools provides and of the checks that are carried out in the process. The end product is in a format that is amenable to statistical modeling. We analyzed the relationship between species richness across multiple higher taxa observed at 526 sites in temperate forests and vegetation indices, measures of aboveground net primary productivity. We downloaded MODIS derived vegetation index time series for each location where the species richness had been sampled, and summarized the data into three measures: maximum time‐series value, temporal mean, and temporal variability. On average, species richness covaried positively with our vegetation index measures. Different higher taxa show different positive relationships with vegetation indices. Models had high R² values, suggesting higher taxon identity and a gradient of vegetation index together explain most of the variation in species richness in our data. MODISTools can be used on Windows, Mac, and Linux platforms, and is available from CRAN and GitHub ( https://github.com/seantuck12/MODISTools ).     

Chloroplast DNA diversity associated with protected slopes and valleys for hybridizing Eucalyptus species on isolated ranges in south‐eastern Australia

Aim To relate genetic diversity to topographic features and to investigate genetic interactions between Eucalyptus species in a local centre of endemism and diversity in south‐eastern Australia. Location Grampian Ranges, Victoria, Australia. Methods We documented chloroplast DNA (cpDNA) variation for a group of endemic Eucalyptus species (E. serraensis, E. verrucata and E. victoriana) that dominate rocky, high‐elevation ridgelines of the Grampian Ranges and for one closely‐related, widespread species (E. baxteri) occupying flanking slopes and valleys. We documented genetic patterns across the landscape using cpDNA microsatellites, and related them to topographic features (exposed west‐facing versus protected east‐facing slopes and valleys). We also determined the extent of local haplotype sharing between populations of endemic species and neighbouring E. baxteri downslope with cpDNA microsatellites, and haplotype sharing between the endemic group and more distantly related species (E. obliqua, E. pauciflora and E. willisii) with sequences of the J_LA+ chloroplast region. Results We detected 26 cpDNA microsatellite haplotypes in a relatively small area of c. 20 km × 50 km. Populations of E. baxteri on east‐facing slopes and valleys had greater cpDNA microsatellite diversity than E. baxteri and endemic species on exposed west‐facing slopes. Endemic species frequently shared chloroplast haplotypes with E. baxteri downslope. Sharing of J_LA+ haplotypes with species outside the endemic group was mostly restricted to E. victoriana, which had cpDNA more similar to the species from other sections of Eucalyptus (E. obliqua, E. willisii and E. pauciflora). Main conclusions Intensive sampling of related species on small isolated mountain ranges allowed us to relate genetic diversity to fine‐scale habitats and to document extensive local haplotype sharing between species. This study contributes to a general understanding of the environmental conditions that enable plant population persistence by linking concentrations of genetic diversity to particular habitats.