Height-diameter allometry for tropical forest in northern Amazonia

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapá State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.

Height-diameter allometry for tropical forest in northern Amazonia

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapá State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.

GeneRax: A Tool for Species-Tree-Aware Maximum Likelihood-Based Gene Family Tree Inference under Gene Duplication, Transfer, and Loss

Inferring phylogenetic trees for individual homologous gene families is difficult because alignments are often too short, and thus contain insufficient signal, while substitution models inevitably fail to capture the complexity of the evolutionary processes. To overcome these challenges, species-tree-aware methods also leverage information from a putative species tree. However, only few methods are available that implement a full likelihood framework or account for horizontal gene transfers. Furthermore, these methods often require expensive data preprocessing (e.g., computing bootstrap trees) and rely on approximations and heuristics that limit the degree of tree space exploration. Here, we present GeneRax, the first maximum likelihood species-tree-aware phylogenetic inference software. It simultaneously accounts for substitutions at the sequence level as well as gene level events, such as duplication, transfer, and loss relying on established maximum likelihood optimization algorithms. GeneRax can infer rooted phylogenetic trees for multiple gene families, directly from the per-gene sequence alignments and a rooted, yet undated, species tree. We show that compared with competing tools, on simulated data GeneRax infers trees that are the closest to the true tree in 90% of the simulations in terms of relative Robinson–Foulds distance. On empirical data sets, GeneRax is the fastest among all tested methods when starting from aligned sequences, and it infers trees with the highest likelihood score, based on our model. GeneRax completed tree inferences and reconciliations for 1,099 Cyanobacteria families in 8 min on 512 CPU cores. Thus, its parallelization scheme enables large-scale analyses. GeneRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax (last accessed June 17, 2020).

Consistency of SVDQuartets and Maximum Likelihood for Coalescent-Based Species Tree Estimation

Numerous methods for inferring species-level phylogenies under the coalescent model have been proposed within the last 20 years, and debates continue about the relative strengths and weaknesses of these methods. One desirable property of a phylogenetic estimator is that of statistical consistency, which means intuitively that as more data are collected, the probability that the estimated tree has the same topology as the true tree goes to 1. To date, consistency results for species tree inference under the multispecies coalescent (MSC) have been derived only for summary statistics methods, such as ASTRAL and MP-EST. These methods have been found to be consistent given true gene trees but may be inconsistent when gene trees are estimated from data for loci of finite length. Here, we consider the question of statistical consistency for four taxa for SVDQuartets for general data types, as well as for the maximum likelihood (ML) method in the case in which the data are a collection of sites generated under the MSC model such that the sites are conditionally independent given the species tree (we call these data coalescent independent sites [CIS] data). We show that SVDQuartets is statistically consistent for all data types (i.e., for both CIS data and for multilocus data), and we derive its rate of convergence. We additionally show that ML is consistent for CIS data under the JC69 model and discuss why a proof for the more general multilocus case is difficult. Finally, we compare the performance of ML and SDVQuartets using simulation for both data types. [Consistency; gene tree; maximum likelihood; multilocus data; hylogenetic inference; species tree; SVDQuartets.]

When species trees disagree: an approach consistent with the coalescent that quantifies phylogenomic support for contentious relationships

Phylogenies inferred using both concatenation- and coalescent-based analyses typically render highly congruent trees. However, when they disagree, they often differ with respect to historically contentious and evolutionarily important relationships. These relationships may also involve etiolated lineages where increased sampling is not possible. Recently, methods aimed at interrogating single relationships or trees have emerged as promising investigative tools to examine these cases. Although recent methods such as “Edge-based Phylogenomic Support analYsis” (EPSY) led to insights into both systematic error and real biological signal, whether they are consistent with the coalescent in cases with high Incomplete Lineage Sorting (ILS) has yet to be characterized. Here, we use simulations and an empirical dataset to test the performance of EPSY, concatenation, and coalescent-based summary analyses under high levels of ILS. We focused on high-ILS scenarios because these represent the typical difficult cases that researchers often face due to the prevalence of ILS in phylogenomic datasets. ILS is known to be a major cause of phylogenomic conflict, which confounds many biological conclusions that depend on a resolved phylogeny, such as inferring ancestral character states, biogeographic reconstructions, and domestication histories. Our study found that EPSY was consistent with the coalescent in a high-ILS empirical dataset. In high-ILS simulations EPSY infers the correct edge more than half the time, whereas coalescent based methods and concatenation methods inferred the actual tree 37.8% and 25% of the time, respectively. All methods have conditions under which they generate the most accurate inferences. Given the levels of ILS in simulations, 26.2% of the time no method recovered the true tree. This zone where no current method can infer the true topology is likely due to properties of the species tree, such as the length of internal edges adjacent to a conflict and/or the length of the shortest branch. Nevertheless, the EPSY approach proves to be a valuable complement to phylogenomic analyses for interrogating regions of the tree with conflicting hypotheses generated from past studies or alternative inference methods. Our analyses highlight that robust phylogenetic trees may not be possible under some scenarios regardless of method and data source.

Identifying Vegetation in Arid Regions Using Object-Based Image Analysis with RGB-Only Aerial Imagery

Vegetation state is usually assessed by calculating vegetation indices (VIs) derived from remote sensing systems where the near infrared (NIR) band is used to enhance the vegetation signal. However VIs are pixel-based and require both visible and NIR bands. Yet, most archived photographs were obtained with cameras that record only the three visible bands. Attempts to construct VIs with the visible bands alone have shown only limited success, especially in drylands. The current study identifies vegetation patches in the hyperarid Israeli desert using only the visible bands from aerial photographs by adapting an alternative geospatial object-based image analysis (GEOBIA) routine, together with recent improvements in preprocessing. The preprocessing step selects a balanced threshold value for image segmentation using unsupervised parameter optimization. Then the images undergo two processes: segmentation and classification. After tallying modeled vegetation patches that overlap true tree locations, both true positive and false positive rates are obtained from the classification and receiver operating characteristic (ROC) curves are plotted. The results show successful identification of vegetation patches in multiple zones from each study area, with area under the ROC curve values between 0.72 and 0.83.

GeneRax: A tool for species tree-aware maximum likelihood based gene family tree inference under gene duplication, transfer, and loss

Inferring phylogenetic trees for individual homologous gene families is difficult because alignments are often too short, and thus contain insufficient signal, while substitution models inevitably fail to capture the complexity of the evolutionary processes. To overcome these challenges species tree-aware methods also leverage information from a putative species tree. However, only few methods are available that implement a full likelihood framework or account for horizontal gene transfers. Furthermore, these methods often require expensive data pre-processing (e.g., computing bootstrap trees), and rely on approximations and heuristics that limit the degree of tree space exploration. Here we present GeneRax, the first maximum likelihood species tree-aware phylogenetic inference software. It simultaneously accounts for substitutions at the sequence level as well as gene level events, such as duplication, transfer, and loss relying on established maximum likelihood optimization algorithms. GeneRax can infer rooted phylogenetic trees for multiple gene families, directly from the per-gene sequence alignments and a rooted, yet undated, species tree. We show that compared to competing tools, on simulated data GeneRax infers trees that are the closest to the true tree in 90% of the simulations in terms of relative Robinson-Foulds distance. On empirical datasets, GeneRax is the fastest among all tested methods when starting from aligned sequences, and it infers trees with the highest likelihood score, based on our model. GeneRax completed tree inferences and reconciliations for 1099 Cyanobacteria families in eight minutes on 512 CPU cores. Thus, its parallelization scheme enables large-scale analyses. GeneRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax.

Stick supply to nests by cliff-nesting raptors as an evolutionary load of past tree-nesting

The supply of sticks to cliff nests by many European raptors has been explained only as a functional means of decreasing ectoparasite loads in nests and for signalling nest occupancy. We provide here a historical explanation of this behaviour as we consider it represents an evolutionary load of formerly tree-nesting species. Basically, from this perspective, facultative tree/cliff-nesting species reproduce the nests they used to build originally on top of trees, but on cliffs. Facultative species (likely evolved in forested areas) that supply their cliff nests with sticks include Pandion haliaetus, Haliaetus albicilla, Milvus migrans, Circaetus gallicus, Buteo buteo, Aquila fasciata, A. pennata, A. chrysaetos, A. heliaca, Gypaetus barbatus Gyps fulvus and Neophron percnopterus. On the contrary, the only Falco species that solely nests in cliffs (F. eleonorae)) and does not supply its nests with sticks and should be considered a true cliff-nester, likely evolved in non-forested areas. All other Falco species that do not supply their cliff nests with sticks but can make use of tree nests made by other non-raptorial species, should also be considered as true cliff-nesters, likely evolved in more forested areas or times. Milvus milvus, Elanus caeruleus, Accipiter nisus, A. gentilis, Pernis apivorus, Aquila adalberti, A. clanga, A. pomarina and Aegypius monachus are true tree nesters, likely evolved in forested areas, which did not evolve the plasticity to nest directly on cliffs.

The ‘Holy Grail’ in Phylogenetic Reconstruction: Seeing the Forest for the Trees?

Systematic/macroevolutionary biology has dedicated much of the past 50 years of its energy and resources in an effort to resolve definitively the one true ‘tree of life’ and to explain materially its cause. But, no matter the quantity/quality of data, experimentation, and analysis, the effort is hampered by persistent and ever-accumulating contradictory observations. This may be an indication that the source of the problem lies in the observer rather than the observed. Observations do not conflict with themselves; they conflict with theoretical expectations. Thus, systematic and evolutionary biology requires epistemological overhaul. Rather than continued misaligning of evidence with theory, theory must be realigned with the evidence. Evidence suggests that the Darwinian reductionist perspective is the epistemological driver of considerable conflict/contradiction in systematic/evolutionary research, and that robust non-Darwinian theories not only better reconcile observations, but also provide a superior investigative perspective.

Consistency of SVDQuartets and Maximum Likelihood for Coalescent-based Species Tree Estimation

AbtractNumerous methods for inferring species-level phylogenies under the coalescent model have been proposed within the last 20 years, and debates continue about the relative strengths and weaknesses of these methods. One desirable property of a phylogenetic estimator is that of statistical consistency, which means intuitively that as more data are collected, the probability that the estimated tree has the same topology as the true tree goes to 1. To date, consistency results for species tree inference under the multispecies coalescent have been derived only for summary statistics methods, such as ASTRAL and MP-EST. These methods have been found to be consistent given true gene trees, but may be inconsistent when gene trees are estimated from data for loci of finite length (Roch et al., 2019). Here we consider the question of statistical consistency for four taxa for SVDQuartets for general data types, as well as for the maximum likelihood (ML) method in the case in which the data are a collection of sites generated under the multispecies coalescent model such that the sites are conditionally independent given the species tree (we call these data Coalescent Independent Sites (CIS) data). We show that SVDQuartets is statistically consistent for all data types (i.e., for both CIS data and for multilocus data), and we derive its rate of convergence. We additionally show that ML is consistent for CIS data under the JC69 model, and discuss why a proof for the more general multilocus case is difficult. Finally, we compare the performance of maximum likelihood and SDVQuartets using simulation for both data types.