Limits to reproduction and seed size-number trade-offs that shape forest dominance and future recovery

Remotely sensed crown nutrient concentrations modulate forest reproduction across the contiguous United States

Global forests are increasingly lost to climate change, disturbance, and human management. Evaluating forests' capacities to regenerate and colonize new habitats has to start with the seed production of individual trees and how it depends on nutrient access. Studies on the linkage between reproduction and foliar nutrients are limited to a few locations and few species, due to the large investment needed for field measurements on both variables. We synthesized tree fecundity estimates from the Masting Inference and Forecasting (MASTIF) network with foliar nutrient concentrations from hyperspectral remote sensing at the National Ecological Observatory Network (NEON) across the contiguous United States. We evaluated the relationships between seed production and foliar nutrients for 56,544 tree-years from 26 species at individual and community scales. We found a prevalent association between high foliar phosphorous (P) concentration and low individual seed production (ISP) across the continent. Within-species coefficients to nitrogen (N), potassium (K), calcium (Ca), and magnesium (Mg) are related to species differences in nutrient demand, with distinct biogeographic patterns. Community seed production (CSP) decreased four orders of magnitude from the lowest to the highest foliar P. This first continental-scale study sheds light on the relationship between seed production and foliar nutrients, highlighting the potential of using combined Light Detection And Ranging (LiDAR) and hyperspectral remote sensing to evaluate forest regeneration. The fact that both ISP and CSP decline in the presence of high foliar P levels has immediate application in improving forest demographic and regeneration models by providing more realistic nutrient effects at multiple scales.

Seed classification with random forest models

Premise

To improve forest conservation monitoring, we developed a protocol to automatically count and identify the seeds of plant species with minimal resource requirements, making the process more efficient and less dependent on human operators.

Methods and Results

Seeds from six North American conifer tree species were separated from leaf litter and imaged on a flatbed scanner. In the most successful species-classification approach, an ImageJ macro automatically extracted measurements for random forest classification in the software R. The method allows for good classification accuracy, and the same process can be used to train the model on other species.

Conclusions

This protocol is an adaptable tool for efficient and consistent identification of seed species or potentially other objects. Automated seed classification is efficient and inexpensive, making it a practical solution that enhances the feasibility of large-scale monitoring projects in conservation biology.

Relatives reproduce in synchrony: kinship and individual condition shape intraspecific variation in masting phenotype

Masting (synchronous and interannually variable seed production) is frequently called a reproductive strategy; yet it is unclear whether the reproductive behaviour of individuals has a heritable component. To address this, we used 22 years of annual fruit production data from 110 Sorbus aucuparia L. trees to examine the contributions of genetic factors to the reproductive phenotype of individuals, while controlling for environmental variation. Trees sharing close genetic relationships and experiencing similar habitat conditions exhibited similar levels of reproductive synchrony. Trees of comparable sizes displayed similar levels of year-to-year variation in fruiting, with relatedness contributing to this variation. External factors, such as shading, influenced the time intervals between years with abundant fruit production. The effects of genetic relatedness on the synchrony of reproduction among trees and on interannual variation provide long-awaited evidence that the masting phenotype is heritable, and can respond to natural selection.

Evolution of masting in plants is linked to investment in low tissue mortality

Masting, a variable and synchronized variation in reproductive effort is a prevalent strategy among perennial plants, but the factors leading to interspecific differences in masting remain unclear. Here, we investigate interannual patterns of reproductive investment in 517 species of terrestrial perennial plants, including herbs, graminoids, shrubs, and trees. We place these patterns in the context of the plants' phylogeny, habitat, form and function. Our findings reveal that masting is widespread across the plant phylogeny. Nonetheless, reversion from masting to regular seed production is also common. While interannual variation in seed production is highest in temperate and boreal zones, our analysis controlling for environment and phylogeny indicates that masting is more frequent in species that invest in tissue longevity. Our modeling exposes masting-trait relationships that would otherwise remain hidden and provides large-scale evidence that the costs of delayed reproduction play a significant role in the evolution of variable reproduction in plants.

Environmental hormesis in living systems: The role of hormetic trade-offs

Hormesis (low-dose stimulation and high-dose inhibition) can be accompanied by hormetic trade-offs, that is, stimulation of some traits and inhibition (trade-off 1) or invariability (trade-off 2) of others. Currently, trade-off options and their biological significance are insufficiently studied. Therefore, the review analyses trade-off types, their relationship with asynchronous stress responses of indicators, the importance of trade-offs for preconditioning, hormesis transgenerational effects, fitness, and evolution. The analysis has shown that hormetic trade-offs 1 and 2 can be observed in evolutionarily distant groups of organisms and at different biological levels (cells, individuals, populations, and communities) with abiotic and biotic stressors, as well as various pollutants. Trade-offs 1 and 2 are found both between different functional traits (e.g., self-maintenance and reproduction in animals, growth and defense in plants), and between the endpoints of the same functional trait (e.g., seed weight and seed number in plants). Asynchronous responses of indicators to a low-dose stressor can lead to hormetic trade-offs in two cases: 1) these indicators have different responses (hormesis, inhibition or zero reaction) in the same dose range; 2) these indicators have hormetic responses with different hormetic zones. Trade-offs can have a positive, negative or zero effect on preconditioning, offspring, and fitness of the population. Trade-offs can potentially affect evolution in two ways: 1) the creation of trends in genotype selection; 2) participation in the assimilation of phenotypic adaptations in the genotype through the Baldwin effect (selection of mutations copying adaptive phenotypes).

Proline concentrations in seedlings of woody plants change with drought stress duration and are mediated by seed characteristics: a meta-analysis

Proline accumulation represents one of mechanisms used by plants to prevent the adverse consequences of water stress. The effects of increased proline levels in response to drought differ among species. Trees are exposed to the long-term effects of climate change. The reproductive success of species in a specific environment depends on the functional trait of tree seeds. We conducted a meta-analysis to evaluate the effects of drought stress on the proline concentrations in seedling leaf tissues of woody plant species and their relationships to drought duration, seed mass, seed category and coniferous/deciduous classification. Drought duration exhibited a nonlinear effect on proline accumulations. The drought effect on proline accumulations is greater for deciduous than for coniferous species and is higher for orthodox seed species than for recalcitrant. The seedlings of large-seeded species showed greater effect sizes than those of small-seeded species. Our results suggest that there is an optimum level at which proline accumulations under the influence of drought are the highest. A link between seed functional traits, as well as the coniferous/deciduous classification, and proline concentrations in tree seedlings during water stress were determined for the first time. Proline may help to identify high-quality seeds of trees used for reforestation.

Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradients

The benefits of masting (volatile, quasi-synchronous seed production at lagged intervals) include satiation of seed predators, but these benefits come with a cost to mutualist pollen and seed dispersers. If the evolution of masting represents a balance between these benefits and costs, we expect mast avoidance in species that are heavily reliant on mutualist dispersers. These effects play out in the context of variable climate and site fertility among species that vary widely in nutrient demand. Meta-analyses of published data have focused on variation at the population scale, thus omitting periodicity within trees and synchronicity between trees. From raw data on 12 million tree-years worldwide, we quantified three components of masting that have not previously been analysed together: (i) volatility, defined as the frequency-weighted year-to-year variation; (ii) periodicity, representing the lag between high-seed years; and (iii) synchronicity, indicating the tree-to-tree correlation. Results show that mast avoidance (low volatility and low synchronicity) by species dependent on mutualist dispersers explains more variation than any other effect. Nutrient-demanding species have low volatility, and species that are most common on nutrient-rich and warm/wet sites exhibit short periods. The prevalence of masting in cold/dry sites coincides with climatic conditions where dependence on vertebrate dispersers is less common than in the wet tropics. Mutualist dispersers neutralize the benefits of masting for predator satiation, further balancing the effects of climate, site fertility and nutrient demands.

Mapping Soil Organic Carbon in Low-Relief Farmlands Based on Stratified Heterogeneous Relationship

Accurate mapping of farmland soil organic carbon (SOC) provides valuable information for evaluating soil quality and guiding agricultural management. The integration of natural factors, agricultural activities, and landscape patterns may well fit the high spatial variation of SOC in low-relief farmlands. However, commonly used prediction methods are global models, ignoring the stratified heterogeneous relationship between SOC and environmental variables and failing to reveal the determinants of SOC in different subregions. Using 242 topsoil samples collected from Jianghan Plain, China, this study explored the stratified heterogeneous relationship between SOC and natural factors, agricultural activities, and landscape metrics, determined the dominant factors of SOC in each stratum, and predicted the spatial distribution of SOC using the Cubist model. Ordinary kriging, stepwise linear regression (SLR), and random forest (RF) were used as references. SLR and RF results showed that land use types, multiple cropping index, straw return, and percentage of water bodies are global dominant factors of SOC. Cubist results exhibited that the dominant factors of SOC vary in different cropping systems. Compared with the SOC of paddy fields, the SOC of irrigated land was more affected by irrigation-related factors. The effect of straw return on SOC was diverse under different cropping intensities. The Cubist model outperformed the other models in explaining SOC variation and SOC mapping (fitting R2 = 0.370 and predicted R2 = 0.474). These results highlight the importance of exploring the stratified heterogeneous relationship between SOC and covariates, and this knowledge provides a scientific basis for farmland zoning management. The Cubist model, integrating natural factors, agricultural activities, and landscape metrics, is effective in explaining SOC variation and mapping SOC in low-relief farmlands.