Evolutionary ecology of masting: mechanisms, models, and climate change.

Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question.

Research on Indoor Environment Prediction of Pig House Based on OTDBO-TCN-GRU Algorithm.

Temperature and humidity, along with concentrations of ammonia and hydrogen sulfide, are critical environmental factors that significantly influence the growth and health of pigs within porcine habitats. The ability to accurately predict these environmental variables in pig houses is pivotal, as it provides crucial decision-making support for the precise and targeted regulation of the internal environmental conditions. This approach ensures an optimal living environment, essential for the well-being and healthy development of the pigs. The existing methodologies for forecasting environmental factors in pig houses are currently hampered by issues of low predictive accuracy and significant fluctuations in environmental conditions. To address these challenges in this study, a hybrid model incorporating the improved dung beetle algorithm (DBO), temporal convolutional networks (TCNs), and gated recurrent units (GRUs) is proposed for the prediction and optimization of environmental factors in pig barns. The model enhances the global search capability of DBO by introducing the Osprey Eagle optimization algorithm (OOA). The hybrid model uses the optimization capability of DBO to initially fit the time-series data of environmental factors, and subsequently combines the long-term dependence capture capability of TCNs and the non-linear sequence processing capability of GRUs to accurately predict the residuals of the DBO fit. In the prediction of ammonia concentration, the OTDBO-TCN-GRU model shows excellent performance with mean absolute error (MAE), mean square error (MSE), and coefficient of determination (R2) of 0.0474, 0.0039, and 0.9871, respectively. Compared with the DBO-TCN-GRU model, OTDBO-TCN-GRU achieves significant reductions of 37.2% and 66.7% in MAE and MSE, respectively, while the R2 value is improved by 2.5%. Compared with the OOA model, the OTDBO-TCN-GRU achieved 48.7% and 74.2% reductions in the MAE and MSE metrics, respectively, while the R2 value improved by 3.6%. In addition, the improved OTDBO-TCN-GRU model has a prediction error of less than 0.3 mg/m3 for environmental gases compared with other algorithms, and has less influence on sudden environmental changes, which shows the robustness and adaptability of the model for environmental prediction. Therefore, the OTDBO-TCN-GRU model, as proposed in this study, optimizes the predictive performance of environmental factor time series and offers substantial decision support for environmental control in pig houses.

Masting, fire-stimulated flowering, and the evolutionary ecology of synchronized reproduction.

Synchronized episodic reproduction among long-lived plants shapes ecological interactions, ecosystem dynamics, and evolutionary processes worldwide. Two active scientific fields investigate the causes and consequences of such synchronized reproduction: the fields of masting and fire-stimulated flowering. While parallels between masting and fire-stimulated flowering have been previously noted, there has been little dialogue between these historically independent fields. We predict that the synthesis of these fields will facilitate new insight into the causes and consequences of synchronized reproduction. Here we briefly review parallels between masting and fire-stimulated flowering, using two case studies and a database of 1870 plant species to facilitate methodological, conceptual, geographical, taxonomic, and phylogenetic comparisons. We identify avenues for future research and describe three key opportunities associated with synthesis. First, the taxonomic and geographic complementarity of empirical studies from these historically independent fields highlights the potential to derive more general inferences about global patterns and consequences of synchronized reproduction in perennial plants. Second, masting's well developed conceptual framework for evaluating adaptive hypotheses can help guide empirical studies of fire-stimulated species and enable stronger inferences about the evolutionary ecology of fire-stimulated flowering. Third, experimental manipulation of reproductive variation in fire-stimulated species presents unique opportunities to empirically investigate foundational questions about ecological and evolutionary processes underlying synchronized reproduction. Synthesis of these fields and their complementary insights offers a unique opportunity to advance our understanding of the evolutionary ecology of synchronized reproduction in perennial plants.

Modes of climate variability bridge proximate and evolutionary mechanisms of masting.

There is evidence that variable and synchronous reproduction in seed plants (masting) correlates to modes of climate variability, e.g. El Niño Southern Oscillation and North Atlantic Oscillation. In this perspective, we explore the breadth of knowledge on how climate modes control reproduction in major masting species throughout Earth's biomes. We posit that intrinsic properties of climate modes (periodicity, persistence and trends) drive interannual and decadal variability of plant reproduction, as well as the spatial extent of its synchrony, aligning multiple proximate causes of masting through space and time. Moreover, climate modes force lagged but in-phase ecological processes that interact synergistically with multiple stages of plant reproductive cycles. This sets up adaptive benefits by increasing offspring fitness through either economies of scale or environmental prediction. Community-wide links between climate modes and masting across plant taxa suggest an evolutionary role of climate variability. We argue that climate modes may 'bridge' proximate and ultimate causes of masting selecting for variable and synchronous reproduction. The future of such interaction is uncertain: processes that improve reproductive fitness may remain coupled with climate modes even under changing climates, but chances are that abrupt global warming will affect Earth's climate modes so rapidly as to alter ecological and evolutionary links. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'.

Natural disturbances and masting: from mechanisms to fitness consequences.

The timing of seed production and release is highly relevant for successful plant reproduction. Ecological disturbances, if synchronized with reproductive effort, can increase the chances of seeds and seedlings to germinate and establish. This can be especially true under variable and synchronous seed production (masting). Several observational studies have reported worldwide evidence for co-occurrence of disturbances and seed bumper crops in forests. Here, we review the evidence for interaction between disturbances and masting in global plant communities; we highlight feedbacks between these two ecological processes and posit an evolutionary pathway leading to the selection of traits that allow trees to synchronize seed crops with disturbances. Finally, we highlight relevant questions to be tested on the functional and evolutionary relationship between disturbances and masting. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'.

Genetically Informed Regression Analysis: Application to Aggression Prediction by Inattention and Hyperactivity in Children and Adults.

We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7%, with 22.6% due to the genetic component of HA. In adults, about 21% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2%), with 8.6% due to the genetic component of InA.

Impacts of potential evapotranspiration on drought phenomena in different regions and climate zones.

The present study is aimed at examining whether potential evapotranspiration (PET), which is important for drought assessment, influences a drought index (standardized precipitation evapotranspiration index; SPEI) for different regions and climate zones. The study regions were East Asia, Europe, the United States (US), and West Africa, and the climate zones considered were the arid, semiarid, subhumid, and humid zones. We examined the pattern of water deficits, spatial trend of the SPEI, area ratio of spatial extent, and temporal trend to provide an understanding of drought characteristics. Two datasets, Climate Research Unit (CRU) and National Centers for Environmental Prediction (NCEP), were used for assessing the drought phenomena. Two types of evapotranspiration obtained using Thornthwaite and Penman-Monteith equations were used to estimate the PET. Negative water deficit values were clearly observed in the arid and semiarid zones of the majority of regions, whereas positive water deficit values were observed in the subhumid and humid zones of the regions. The SPEI spatial trend largely presented a decreasing trend in East Asia and West Africa, a neutral or decreasing trend in Europe, and a neutral or increasing trend in the US. The area ratio of the spatial extent showed large values of a neutral or decreasing trend in East Asia and Europe, a neutral or increasing trend in the US, and a decreasing trend in West Africa. The temporal trend of the spatial extent primarily exhibited no trend or an increasing trend in the aforementioned regions, except in the case of the majority of West Africa. Although the results obtained from the two datasets appear to be slightly different, they show that the PET is predominant in regions, especially in the US. The PET trends are identified through comparisons and used to understand the drought phenomena while considering various geographic regions and climatic zones.