The carbon balance of plants: economics, optimization, and trait spectra in a historical perspective

Over fifty years have passed since the publication of Harold Mooney's formative paper, "The Carbon Balance of Plants" on pages 315-346 of Volume 3 (1972) of Annual Review of Ecology and Systematics. Arguably, the conceptual framework presented in that paper, and the work by Mooney and his students leading up to the paper, provided the foundational principles from which core disciplines emerged in plant economic theory, functional trait theory and, more generally, plant physiological ecology. Here, we revisit the primary impacts of those early discoveries to understand how researchers constructed major concepts in our understanding of plant adaptations, and where those concepts are likely to take us in the near future. The discipline of functional trait ecology, which is rooted in the principles of evolutionary and economic optimization, has captured the imagination of the plant physiological ecology research community, though its emphasis has shifted toward predicting species distributions and ecological roles across resource gradients. In the face of 'big-data' research pursuits that are revealing trait expression patterns at the cellular level and mass and energy exchange patterns at the planetary scale, an opportunity exists to reconnect the principles of plant carbon balance and evolutionary optimization with trait origins at the genetic and cellular scales and trait impacts at the global scale.

Assessment of Individual Tree Detection and Canopy Cover Estimation using Unmanned Aerial Vehicle based Light Detection and Ranging (UAV-LiDAR) Data in Planted Forests

Canopy cover is a key forest structural parameter that is commonly used in forest inventory, sustainable forest management and maintaining ecosystem services. Recently, much attention has been paid to the use of unmanned aerial vehicle (UAV)-based light detection and ranging (LiDAR) due to the flexibility, convenience, and high point density advantages of this method. In this study, we used UAV-based LiDAR data with individual tree segmentation-based method (ITSM), canopy height model-based method (CHMM), and a statistical model method (SMM) with LiDAR metrics to estimate the canopy cover of a pure ginkgo (Ginkgo biloba L.) planted forest in China. First, each individual tree within the plot was segmented using watershed, polynomial fitting, individual tree crown segmentation (ITCS) and point cloud segmentation (PCS) algorithms, and the canopy cover was calculated using the segmented individual tree crown (ITSM). Second, the CHM-based method, which was based on the CHM height threshold, was used to estimate the canopy cover in each plot. Third, the canopy cover was estimated using the multiple linear regression (MLR) model and assessed by leave-one-out cross validation. Finally, the performance of three canopy cover estimation methods was evaluated and compared by the canopy cover from the field data. The results demonstrated that, the PCS algorithm had the highest accuracy (F = 0.83), followed by the ITCS (F = 0.82) and watershed (F = 0.79) algorithms; the polynomial fitting algorithm had the lowest accuracy (F = 0.77). In the sensitivity analysis, the three CHM-based algorithms (i.e., watershed, polynomial fitting and ITCS) had the highest accuracy when the CHM resolution was 0.5 m, and the PCS algorithm had the highest accuracy when the distance threshold was 2 m. In addition, the ITSM had the highest accuracy in estimation of canopy cover (R2 = 0.92, rRMSE = 3.5%), followed by the CHMM (R2 = 0.94, rRMSE = 5.4%), and the SMM had a relative low accuracy (R2 = 0.80, rRMSE = 5.9%).The UAV-based LiDAR data can be effectively used in individual tree crown segmentation and canopy cover estimation at plot-level, and CC estimation methods can provide references for forest inventory, sustainable management and ecosystem assessment.

Reduced resistance to sediment-trapping turfs with decline of native kelp and establishment of an exotic kelp

Understanding the strength and type of interactions among species is vital to anticipate how ecosystems will respond to ongoing anthropogenic stressors. Here, we examine the ecological function of native (Ecklonia radiata) and invasive (Undaria pinnatifida) kelps in resisting shifts to sediment-trapping turf on reefs within the highly urbanized temperate Port Phillip Bay (PPB), Australia. Short-term (30 days) and long-term (232 days) manipulations demonstrated that kelp laminae can clear and maintain the substratum free of turfs, while conversely, removal of kelp leads to a proliferation of turfs. Analyses looking at the relationship between total length of E. radiata and U. pinnatifida and the area cleared of turf algae showed that the clearing effect of E. radiata over a year was greater than that of U. pinnatifida due to the annual die-back of the invasive. A natural experiment (608 days) identified that ongoing sea urchin (Heliocidaris erythrogramma) grazing led to native kelp bed decline, facilitating turf dominance. Even though U. pinnatifida establishes once native beds are disturbed, its ecological function in clearing turf is weaker than E. radiata, given its annual habit. In PPB, turfs represent the more persistent and problematic algal group and are likely changing the structure, function, and energy flows of shallow temperate reefs in this urbanised embayment.

Actuarial senescence in a long-lived orchid challenges our current understanding of ageing

The dominant evolutionary theory of actuarial senescence-an increase in death rate with advancing age-is based on the concept of a germ cell line that is separated from the somatic cells early in life. However, such a separation is not clear in all organisms. This has been suggested to explain the paucity of evidence for actuarial senescence in plants. We used a 32 year study of Dactylorhiza lapponica that replaces its organs each growing season, to test whether individuals of this tuberous orchid senesce. We performed a Bayesian survival trajectory analysis accounting for reproductive investment, for individuals under two types of land use, in two climatic regions. The mortality trajectory was best approximated by a Weibull model, showing clear actuarial senescence. Rates of senescence in this model declined with advancing age, but were slightly higher in mown plots and in the more benign climatic region. At older ages, senescence was evident only when accounting for a positive effect of reproductive investment on mortality. Our results demonstrate actuarial senescence as well as a survival-reproduction trade-off in plants, and indicate that environmental context may influence senescence rates. This knowledge is crucial for understanding the evolution of demographic senescence and for models of plant population dynamics.

The evolution of phenotypic plasticity: genealogy of a debate in genetics

The paper describes the context and the origin of a particular debate that concerns the evolution of phenotypic plasticity. In 1965, British biologist A. D. Bradshaw proposed a widely cited model intended to explain the evolution of norms of reaction, based on his studies of plant populations. Bradshaw's model went beyond the notion of the "adaptive norm of reaction" discussed before him by Dobzhansky and Schmalhausen by suggesting that "plasticity"--the ability of a phenotype to be modified by the environment--should be genetically determined. To prove Bradshaw's hypothesis, it became necessary for some authors to identify the pressures exerted by natural selection on phenotypic plasticity in particular traits, and thus to model its evolution. In this paper, I contrast two different views, based on quantitative genetic models, proposed in the mid-1980s: Russell Lande and Sara Via's conception of phenotypic plasticity, which assumes that the evolution of plasticity is linked to the evolution of the plastic trait itself, and Samuel Scheiner and Richard Lyman's view, which assumes that the evolution of plasticity is independent from the evolution of the trait. I show how the origin of this specific debate, and different assumptions about the evolution of phenotypic plasticity, depended on Bradshaw's definition of plasticity and the context of quantitative genetics.

The extent and genetic basis of phenotypic divergence in life history traits in Mimulus guttatus

Differential natural selection acting on populations in contrasting environments often results in adaptive divergence in multivariate phenotypes. Multivariate trait divergence across populations could be caused by selection on pleiotropic alleles or through many independent loci with trait-specific effects. Here, we assess patterns of association between a suite of traits contributing to life history divergence in the common monkey flower, Mimulus guttatus, and examine the genetic architecture underlying these correlations. A common garden survey of 74 populations representing annual and perennial strategies from across the native range revealed strong correlations between vegetative and reproductive traits. To determine whether these multitrait patterns arise from pleiotropic or independent loci, we mapped QTLs using an approach combining high-throughput sequencing with bulk segregant analysis on a cross between populations with divergent life histories. We find extensive pleiotropy for QTLs related to flowering time and stolon production, a key feature of the perennial strategy. Candidate genes related to axillary meristem development colocalize with the QTLs in a manner consistent with either pleiotropic or independent QTL effects. Further, these results are analogous to previous work showing pleiotropy-mediated genetic correlations within a single population of M. guttatus experiencing heterogeneous selection. Our findings of strong multivariate trait associations and pleiotropic QTLs suggest that patterns of genetic variation may determine the trajectory of adaptive divergence.