Spatial and temporal models in plant ecology: logic and causality

In the paper, I argue that in order to make credible ecological predictions for terrestrial ecosystems in a changing environment, we need empirical plant ecological models that are fitted to spatial and temporal ecological data. Here, it is advocated to use structural equation models in a hierarchical framework with latent variables. Furthermore, it is an advantage that the proposed hierarchical models are analogous to well-known theoretical epistemological models of how knowledge is obtained.

Plant ecological genomics at the limits of life in the Atacama Desert

The Atacama Desert in Chile—hyperarid and with high–ultraviolet irradiance levels—is one of the harshest environments on Earth. Yet, dozens of species grow there, including Atacama-endemic plants. Herein, we establish the Talabre–Lejía transect (TLT) in the Atacama as an unparalleled natural laboratory to study plant adaptation to extreme environmental conditions. We characterized climate, soil, plant, and soil–microbe diversity at 22 sites (every 100 m of altitude) along the TLT over a 10-y period. We quantified drought, nutrient deficiencies, large diurnal temperature oscillations, and pH gradients that define three distinct vegetational belts along the altitudinal cline. We deep-sequenced transcriptomes of 32 dominant plant species spanning the major plant clades, and assessed soil microbes by metabarcoding sequencing. The top-expressed genes in the 32 Atacama species are enriched in stress responses, metabolism, and energy production. Moreover, their root-associated soils are enriched in growth-promoting bacteria, including nitrogen fixers. To identify genes associated with plant adaptation to harsh environments, we compared 32 Atacama species with the 32 closest sequenced species, comprising 70 taxa and 1,686,950 proteins. To perform phylogenomic reconstruction, we concatenated 15,972 ortholog groups into a supermatrix of 8,599,764 amino acids. Using two codon-based methods, we identified 265 candidate positively selected genes (PSGs) in the Atacama plants, 64% of which are located in Pfam domains, supporting their functional relevance. For 59/184 PSGs with an Arabidopsis ortholog, we uncovered functional evidence linking them to plant resilience. As some Atacama plants are closely related to staple crops, these candidate PSGs are a “genetic goldmine” to engineer crop resilience to face climate change.

Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms

Plant Ecological Unit’s (PEUs) are the abstraction of vegetation communities that occur on a site which similarly respond to management actions and natural disturbances. Identification and monitoring of PEUs in a heterogeneous landscape is the most difficult task in medium resolution satellite images datasets. The main objective of this study is to compare pixel-based classification versus object-based classification for accurately classifying PEUs with four selected different algorithms across heterogeneous rangelands in Central Zagros, Iran. We used images of Landsat-8 OLI that were pan-sharpened to 15 m to classify four PEU classes based on a random dataset collected in the field (40%). In the first stage, we applied the following classification algorithms to distinguish PEUs: Minimum Distance (MD), Maximum Likelihood Classification (MLC), Neural Network-Multi Layer Perceptron (NN-MLP) and Classification Tree Analysis (CTA) for pixel based method and object based method. Then, by using the most accurate classification approach, in the second stage auxiliary data (Principal Component Analysis (PCA)) was incorporated to improve the accuracy of the PEUs classification process. At the end, test data (60%) were used for accuracy assessment of the resulting maps. Object-based maps clearly outperformed pixel-based maps, especially with CTA, NN-MLP and MD algorithms with overall accuracies of 86%, 72% and 59%, respectively. The MLC algorithm did not reveal any significant difference between the object-based and pixel-based analyses. Finally, complementing PCA auxiliary bands to the CTA algorithms offered the most successful PEUs classification strategy, with the highest overall accuracy (89%). The results clearly underpin the importance of object-based classification with the CTA classifier together with PCA auxiliary data to optimize identification of PEU classes.

Variations in Leaf Traits Modulate Plant Vegetative and Reproductive Phenological Sequencing Across Arid Mediterranean Shrublands

Structural and nutrient traits of a leaf are important for understanding plant ecological strategies (e.g., drought avoidance). We studied the specific leaf area (SLA), leaf carbon content (LCC), leaf nitrogen content (LNC), leaf phosphorous content (LPC), and the phenophase sequence index (PSI) in 126 Mediterranean perennial species from predesert (SMS) and semiarid (SaMS) to subalpine (SAS), alpine cushion (AcS), and oro-Mediterranean (AjS) shrublands, which represent eight functional groups (evergreen and deciduous trees, evergreen large and half shrubs, deciduous large and half shrubs, succulents and perennial herbs). We analyzed the variation and relationships between leaf traits and PSI among shrublands, functional groups, and within species with drought-avoidance mechanisms. SLA variation of 20–60% could be ascribed to differences between functional groups and only 38–48% to different shrublands increasing from the predesert to the alpine. Alpine species display low PSI and N:P and high SLA, LNC, LPC, LCC, and C:N. On the contrary, predesert and semiarid showed high PSI and low SLA. SLA mediates the vegetative and reproductive phenological plant sequencing, high SLA is often associated with the overlapping in growth and reproductive phenophases with a seasonal reduction of vegetative growth, whereas low SLA is associated with vegetative and reproductive sequencing and a seasonal extension of vegetative growth. Species with drought-avoidance mechanisms (e.g., semideciduous species) contribute to an increase in the mean values of the SLA and LNC because these species show similar leaf and phenological patterns as the deciduous (high SLA and LNC and low PSI). The N:P indicates that only the alpine shrublands could present P limitations. The positive correlations between SLA and LPC and LNC and LPC (leaf economic spectrum) and the negative correlation between SLA and C:N were consistently maintained in the studied arid Mediterranean shrublands.

Evidence for magnesium–phosphorus synergism and co-limitation of grain yield in wheat agriculture

Modern crop production is characterized by high nitrogen (N) application rates, which can influence the co-limitation of harvested yield by other nutrients. Using a multidimensional niche volume concept and scaling exponents frequently applied in plant ecological research, we report that increased N and phosphorus (P) uptake in a growing wheat crop along with enhanced grain biomass is associated with more than proportional increase of other nutrients. Furthermore, N conversion efficiency and grain yield are strongly affected by the magnesium (Mg) to P ratio in the growing crop. We analyzed a field trial in Central Sweden including nine wheat varieties grown during two years with contrasting weather, and found evidence for Mg co-limitation at lower grain yields and P co-limitation at higher yields. We argue that critical concentrations of single nutrients, which are often applied in agronomy, should be replaced by nutrient ratios. In addition, links between plant P and Mg contents and root traits were found; high root number enhanced the P:N ratio, whilst steep root angle, indicating deep roots, increased the Mg:N ratio. The results have significant implications on the management and breeding targets of agriculturally grown wheat, which is one of the most important food crops worldwide.

How FAIR are plant sciences in the twenty-first century? The pressing need for reproducibility in plant ecology and evolution

The need for open, reproducible science is of growing concern in the twenty-first century, with multiple initiatives like the widely supported FAIR principles advocating for data to be Findable, Accessible, Interoperable and Reusable. Plant ecological and evolutionary studies are not exempt from the need to ensure that the data upon which their findings are based are accessible and allow for replication in accordance with the FAIR principles. However, it is common that the collection and curation of herbarium specimens, a foundational aspect of studies involving plants, is neglected by authors. Without publicly available specimens, huge numbers of studies that rely on the field identification of plants are fundamentally not reproducible. We argue that the collection and public availability of herbarium specimens is not only good botanical practice but is also fundamental in ensuring that plant ecological and evolutionary studies are replicable, and thus scientifically sound. Data repositories that adhere to the FAIR principles must make sure that the original data are traceable to and re-examinable at their empirical source. In order to secure replicability, and adherence to the FAIR principles, substantial changes need to be brought about to restore the practice of collecting and curating specimens, to educate students of their importance, and to properly fund the herbaria which house them.