Plant Strategies Research Articles

Modeling the Potential Habitat Gained by Planting Sagebrush in Burned Landscapes

Many revegetation projects are intended to benefit wildlife species. Yet, there are few a priori evaluations that assess the potential efficiency of restoration actions in recovering wildlife habitats. We developed a spatial vegetation–habitat recovery model to gauge the degree to which field planting strategies could be expected to recover multi-factor habitat conditions for wildlife following wildfires. We simulated a wildfire footprint, multiple sagebrush (Artemisia spp.) planting scenarios, and tracked projected vegetation growth for 15 years post-fire. We used a vegetation transition framework to track and estimate the degree to which revegetation could accelerate habitat restoration for a Greater sage-grouse (Centrocercus) population within the Great Basin, western United States. We assessed the amount of habitat 15 years post-fire to estimate the degree to which revegetation could be expected to accelerate habitat restoration. Our results highlight a potential disconnect between the expansive areas required by wide-ranging wildlife such as sage-grouse and the relatively small areas that planting treatments have created. Habitat restorations and planting strategies that are intended to benefit sage-grouse may only speed up localized habitat restoration. This study provides an example of how linked revegetation–habitat modeling approaches can scope the expected return on restoration investment for habitat improvements and support the strategic use of limited restoration resources.

Response of Tomato Plants, Ailsa Craig and Carotenoid Mutant tangerine, to Simultaneous Treatment by Low Light and Low Temperature.

Tomato (Solanum lycopersicum L.) plants, wild type Ailsa Craig, and carotenoid mutant tangerine that accumulates prolycopene instead of all-trans-lycopene were exposed to a combined treatment by low light and low temperature for 5 days. The ability of plants to recover from the stress after development for 3 days at control conditions was followed as well. The suffered oxidative stress was evaluated by the extent of pigment content, lipid peroxidation, membrane stability, and H2O2 generation. The level of MDA content under combined treatment in tangerine implies that the mutant demonstrates lower sensitivity to stress in comparison with Ailsa Craig. The oxidative protective strategy of plants was estimated by following the antioxidant and antiradical activity of phenolic metabolites, including anthocyanins, as well as the activities of antioxidant enzymes superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT). Presented results revealed that the oxidative stress was much stronger expressed after exposure of both types of plants to low light combined with low temperature compared to that after treatment with only low light. The most significant antioxidant protection was provided by phenolic substances, including anthocyanins. The lower sensitivity of tangerine plants to low light can be attributed to the higher activity of the antioxidant enzyme CAT.

Optimal bidding strategy for the price-maker virtual power plant in the day-ahead market based on multi-agent twin delayed deep deterministic policy gradient algorithm

In recent years, distributed energy resources (DERs) have developed greatly, and the total capacity of resources aggregated by virtual power plants (VPPs) has increased. The role VPP plays in the market is changing. It is necessary to explore VPP's bidding strategy in the electricity market based on the impact of VPP on the clearing price. At the same time, the strategy game of different market players will also impact VPP's strategy. The multi-agent twin delayed deep deterministic policy gradient (MATD3) algorithm is used to solve the problem of price-maker VPP participation in the day-ahead (DA) market. VPP is required to submit the power and prices of electricity in multi-segments at different times. In the market bidding process, the main market participants are considered as agents. Iterative refinement of each player's strategy is achieved through multi-agent reinforcement learning, with the primary aim of maximizing revenue. For the VPP, the MATD3 algorithm improved the reward by approximately 65 % and increased the convergence speed by 17 % compared to the multi-agent deep deterministic policy gradient and multi-agent proximal policy optimization algorithms. The effects of different influences on VPP's bidding strategy are analyzed, which can provide a decision-making reference for market participants.

Optimizing the In Vitro Propagation of Tea Plants: A Comparative Analysis of Machine Learning Models

In this study, we refine in vitro propagation techniques for Camellia sinensis using a machine learning approach to ascertain the influence of different shooting and rooting conditions on key growth metrics. This was achieved by applying random forest (RF), XGBoost, and multilayer perceptron (MLP) models to dissect the complexities of micropropagation and rooting processes. The research unveiled significant disparities in growth metrics under varying media conditions, underscoring the profound impact of media composition on plant development. The meticulous statistical analysis, employing ANOVA, highlighted statistically significant differences in growth metrics, indicating the critical role of media composition in optimizing growth conditions. Methodologically, the study utilized explants from 2–3-year-old tea plants, which underwent sterilization before being introduced to two distinct culture media for their micropropagation and rooting phases. Statistical analyses were conducted to evaluate the differences in growth outcomes between media, while machine learning models were employed to predict the efficacy of micropropagation and rooting based on various growth regulators. This approach allowed for a comprehensive evaluation of the model’s performance in simulating plant growth under different conditions, leveraging metrics like R2, RMSE, and MAE. The findings from this study significantly advance the understanding of tea plant micropropagation, highlighting the utility of machine learning models in agricultural optimization. This research contributes to enhancing micropropagation strategies for the tea plant and exemplifies the transformative potential of integrating machine learning into plant science, paving the way for improved agricultural and horticultural practices. This interdisciplinary approach offers a novel perspective on optimizing in vitro propagation processes, contributing substantially to plant tissue culture and biotechnology.

Evaluating sustainability power plant efficiency: Unveiling the impact of power plant load ratio on holding steam ejector performance

Understanding the role of holding ejectors is essential in the broader context of environmental and sustainability research. Through rigorous analysis, optimization of ejector usage is applied to minimize resource consumption and promote cleaner, more sustainable production methods. However, the design and control strategies of the power plant, including the setpoints and tolerances of various components, can also contribute to the power plant load ratio (PPLR). This study explores the impact of PPLR in the power plant cycle on the holding ejectors performance under various condenser temperatures. For comprehensive analysis, the study employs a comprehensive framework encompassing various indicators such as condensing fluid behavior, energy consumption, exergy destruction, air suction in the condenser, and entrainment ratio. The research unveils key findings, including a notable increase in oblique shocks with rising PPLR and a quantifiable rise in the maximum liquid mass fraction in the condensed regime. Additionally, the analysis reveals numerical relationships, such as a 5 % increase in mass flow rate and a 4.9 % rise in energy consumption with a PPLR increase from 0 to +5 %. Negative impacts on performance, such as a 4.6 % reduction in air extraction flow rate from the condenser, are observed with PPLR changes from 0 to −5%.

Seed dormancy types and germination response of 15 plant species in temperate montane peatlands.

Despite their crucial role in determining the fate of seeds, the type and breaking mode of seed dormancy in peatland plants in temperate Asia with a continental monsoon climate are rarely known. Fifteen common peatland plant species were used to test their seed germination response to various dormancy-breaking treatments, including dry storage (D), gibberellin acid soaking (GA), cold stratification (CS), warm followed cold stratification (WCS), GA soaking + cold stratification (GA + CS) and GA soaking + warm followed cold stratification (GA + WCS). Germination experiment, viability and imbibition test, and morphological observation of embryos were conducted. Of the 15 species, nine showed physiological dormancy (PD), with non-deep PD being the dominant type. Four species, Angelica pubescens, Cicuta virosa, Iris laevigata, and Iris setosa exhibited morphophysiological dormancy. Two species, Lycopus uniflorus and Spiraea salicifolia, demonstrated nondormancy. Overall, the effect hierarchy of dormancy-breaking is: CS > GA > WCS > GA + CS > D > GA + WCS. Principal component analysis demonstrated that seed traits, including embryo length: seed length ratio, seed size, and monocot/eudicot divergence, are more likely to influence seed dormancy than environmental factors. Our study suggests that nearly 90% of the tested peatland plant species in the Changbai Mountains demonstrated seed dormancy, and seed traits (e.g. embryo-to-seed ratio and seed size) and abiotic environmental factors (e.g. pH and temperature seasonality) are related to germination behavior, suggesting seed dormancy being a common adaptation strategy for the peatland plants in the temperate montane environment.

Optimal Design of I-PD and PI-D Industrial Controllers Based on Artificial Intelligence Algorithm

This research aims to apply Artificial Intelligence (AI) methods, specifically Artificial Immune Systems (AIS), to design an optimal control strategy for a multivariable control plant. Two specific industrial control approaches are investigated: I-PD (Integral-Proportional Derivative) and PI-D (Proportional-Integral Derivative) control. The motivation for using these variations of PID controllers is that they are functionally implemented in modern industrial controllers, where they provide precise process control. The research results in a novel solution to the control synthesis problem for the industrial system. In particular, the research deals with the synthesis of I-P control for a two-loop system in the technological process of a distillation column. This synthesis is carried out using the AIS algorithm, which is the first application of this technique in this specific context. Methodological approaches are proposed to improve the performance of industrial multivariable control systems by effectively using optimization algorithms and establishing modified quality criteria. The numerical performance index ISE justifies the effectiveness of the AIS-based controllers in comparison with conventional PID controllers (ISE1 = 1.865, ISE2 = 1.56). The problem of synthesis of the multi-input multi-output (MIMO) control system is solved, considering the interconnections due to the decoupling procedure.

Root pH variation of herbaceous plants among plant functional groups in response to climate and soil gradients on the Tibetan alpine grasslands.

Plant pH is an emerging functional trait that plays important roles in physiological processes and nutrient cycling. However, how root pH varies among plant functional groups (PFGs) and the regulatory factors on a large scale remain unclear. Therefore, we quantified root pH variation of herbaceous plants in four PFGs from 20 sites on the Tibetan Plateau along a 1600 km transect and explored the correlations between root pH and different PFGs, climate and soil conditions. The results showed that the root pH of herbaceous plants was slightly acidic (6.46 ± 0.05). Grasses had the highest root pH (6.91 ± 0.10) across all functional groups (p < .05), whereas legumes had the lowest (5.90 ± 0.08; p < .05). The root pH decreased with mean annual precipitation, aridity index, soil water content and soil stress coefficient, whereas the significant positive correlation with soil pH. PFGs, climate and soil explained 5.39, 11.15 and 24.94% of the root pH variance, respectively. This study provided a comprehensive analysis of root pH patterns in herbaceous plants over a large spatial scale. Root pH was controlled by the combined influence of PFGs, climate and soil properties, with moisture status being the main influential factor. In contrast to the leaf pH, the root pH of herbaceous plants is strongly affected by the soil pH along environmental gradients. Our findings provide new insights into root functional traits and survival strategies of herbaceous plants in alpine ecosystems.

Exploring the coordinated hydraulic plasticity across organs in soybean plants exposed to drought cycles

The coordination of hydraulic function among different organs and their plasticity under stressful conditions are crucial for understanding drought tolerance in crops but remains poorly understood. Here, we evaluate the hydraulic plasticity in soybean organs exposed to one or two droughts and correlated this plasticity with recovery after rewatering. Repeated drought events resulted in different levels of dehydration in soybean leaves since plants exposed to two droughts (D2 plants) maintained higher water potential than plants exposed to a single drought (D1 plants). The difference in leaf water potential reflected the different drought acclimation strategies in D1 and D2 plants. D1 plants increased root hydraulic conductance, a change that can occur rapidly due to molecular modifications. The first drought also acted as an environmental cue, triggering changes that continued to develop over time (anatomical changes) and which increased water transport in the stem of D2 plants, reducing the drought impact in these organs and maintaining the water transport to the leaves. Leaves of D1 and D2 plants, in turn, reduced vulnerability to embolism, avoiding losses in rehydration capacity and helping to maintain the hydraulic functions essential for the rapid recovery of photosynthesis after rewatering.

Soil salinity regulates spatial-temporal heterogeneity of seed germination and seedbank persistence of an annual diaspore-trimorphic halophyte in northern China

Background and aimsSeed heteromorphism is a plant strategy that an individual plant produces two or more distinct types of diaspores, which have diverse morphology, dispersal ability, ecological functions and different effects on plant life history traits. The aim of this study was to test the effects of seasonal soil salinity and burial depth on the dynamics of dormancy/germination and persistence/depletion of buried trimorphic diaspores of a desert annual halophyte Atriplex centralasiatica.MethodsWe investigated the effects of salinity and seasonal fluctuations of temperature on germination, recovery of germination and mortality of types A, B, C diaspores of A. centralasiatica in the laboratory and buried diaspores in situ at four soil salinities and three depths. Diaspores were collected monthly from the seedbank from December 2016 to November 2018, and the number of viable diaspores remaining (not depleted) and their germinability were determined.ResultsNon-dormant type A diaspores were depleted in the low salinity “window” in the first year. Dormant diaspore types B and C germinated to high percentages at 0.3 and 0.1 mol L-1 soil salinity, respectively. High salinity and shallow burial delayed depletion of diaspore types B and C. High salinity delayed depletion time of the three diaspore types and delayed dormancy release of types B and C diaspores from autumn to spring. Soil salinity modified the response of diaspores in the seedbank by delaying seed dormancy release in autum and winter and by providing a low-salt concentration window for germination of non-dormant diaspores in spring and early summer.ConclusionsBuried trimorphic diaspores of annual desert halophyte A. centralasiatica exhibited diverse dormancy/germination behavior in respond to seasonal soil salinity fluctuation. Prolonging persistence of the seedbank and delaying depletion of diaspores under salt stress in situ primarily is due to inhibition of dormancy-break. The differences in dormancy/germination and seed persistence in the soil seedbank may be a bet-hadging strategy adapted to stressful temporal and spatial heterogeneity, and allows A. centralasiatica to persist in the unpredictable cold desert enevironment.

Hyperspectral signals in the soil: Plant-soil hydraulic connection and disequilibrium as mechanisms of drought tolerance and rapid recovery.

Predicting soil water status remotely is appealing due to its low cost and large-scale application. During drought, plants can disconnect from the soil, causing disequilibrium between soil and plant water potentials at pre-dawn. The impact of this disequilibrium on plant drought response and recovery is not well understood, potentially complicating soil water status predictions from plant spectral reflectance. This study aimed to quantify drought-induced disequilibrium, evaluate plant responses and recovery, and determine the potential for predicting soil water status from plant spectral reflectance. Two species were tested: sweet corn (Zea mays), which disconnected from the soil during intense drought, and peanut (Arachis hypogaea), which did not. Sweet corn's hydraulic disconnection led to an extended 'hydrated' phase, but its recovery was slower than peanut's, which remained connected to the soil even at lower water potentials (-5 MPa). Leaf hyperspectral reflectance successfully predicted the soil water status of peanut consistently, but only until disequilibrium occurred in sweet corn. Our results reveal different hydraulic strategies for plants coping with extreme drought and provide the first example of using spectral reflectance to quantify rhizosphere water status, emphasizing the need for species-specific considerations in soil water status predictions from canopy reflectance.

Climate interacts with the trait structure of tree communities to influence forest productivity

Abstract Tree functional diversity can increase forest productivity by enhancing species interactions and providing greater growth stability. However, very few studies have examined the influence of tree community trait structure on survivor growth, recruitment and mortality simultaneously, which are the main drivers of forest population dynamics. Here, we explore the interactions among functional diversity, productivity and climate to investigate the role of the trait structure of communities on forest productivity and to determine under what circumstances functional diversity should be promoted to ensure forest adaptive capacity under future climate. Using random‐forest modelling and a network of permanent sample plots covering a broad gradient of climatic conditions, we isolated the effects of functional diversity—described as the distribution of trait values in a community—and climate variables on net forest productivity (NFP), survivor growth, recruitment and mortality. Based on our findings, community‐level trait structure affects forest productivity in different ways. NFP was influenced by three traits from three different plant strategy dimensions, whereas survivor growth and recruitment were strongly correlated with leaf and resource acquisition traits, and tree mortality with a mix of traits reflecting various plant strategies. We also observed climate interactions with the functional trait structure of tree communities. For instance, we observed an interaction between drought tolerance and mean annual temperature: At low temperatures, NFP biomass accumulation increased with the value of the drought tolerance trait; however, at higher temperatures, the opposite pattern was observed. However, we found contrasting patterns of population response to climate variability, depending on their functional diversity. Greater functional diversity does not necessarily increase biomass accumulation under different climatic conditions. Synthesis. As all components of forest productivity contribute to NFP, studies on forest productivity should consider not only survivor growth but also recruitment and mortality. Each component responds differently in terms of biomass changes in climatic variation, according to the trait structure of tree communities. This study provides a framework to identify the trait structure that should be targeted under different climate scenarios to anticipate change and help strengthen forest response capacity to climate change.

Identifying factors related to delayed neck metastasis after surgical treatment in patients with oral squamous cell carcinoma

BackgroundGeneral treatment of oral squamous cell carcinoma (OSCC) is surgical treatment with or without neck dissection. Although the incidence of delayed neck metastasis is rare, it may occur after the surgery and is known to be the most important factor in the prognosis. The purpose of is study is to evaluate the clinical and histopathological factors associated with delayed neck metastasis case among patients.MethodsA total of 195 patients who underwent surgical treatment for OSCC from 2016 to 2022 were investigated. Among them, delayed neck metastasis (DNM) was analyzed. The criterion for delayed neck metastasis was a newly developed neck lesion after the primary operation without neck dissection in cN0 necks. To identify the correlation between prognostic factors and the incidence of delayed neck metastasis, χ2 analysis with phi correlation and Cramer’s V test was performed. Cumulative survival rates (CRS) were compared between the groups with the incidence of DNM and without DNM. Also, the log rank test for CSR and Cox proportional hazard model was analyzed to estimate the significance of the CSR and confirm the correlations between prognostic factors and DNM.ResultAmong 195 patients, 14 were discovered to have DNM. The primary tumor locations were the tongue (n = 5), floor of the mouth (n = 2), mandibular gingiva (n = 1), maxillary gingiva (n = 4), retromolartrigone (n = 1), and buccal mucosa (n = 2) each. The cases consisted of TNM stage I (n = 1), stage II (n = 3), stage III (n = 3), and stage IV (n = 8), respectively. The result of the χ2 analysis identified a correlation between positive neck (p = 0.01), depth of invasion (p = 0.09), radiation therapy (p = 0.003), and DNM. Groups without DNM showed better prognosis compared to groups with DNM. Regarding positive neck, depth of invasion, and radiation therapy, only depth of invasion showed significance in CSR analysis.ConclusionDNM after surgical treatment of OSCC is a rare event, and few were found in a review of the literature. Also, many prognostic factors have been suggested but controversial. However, in our study, some prognostic factors have been identified to have a significant correlation with the incidence of DNM, and analysis of such factors provides important information predicting neck metastasis and the prognosis.

Salicylic Acid Is Involved in the Growth Inhibition Caused by Excessive Ammonium in Oilseed Rape (Brassica napus L.).

Rapeseed (Brassica napus L.) is extremely sensitive to excessive NH4+ toxicity. There remains incomplete knowledge of the causal factors behind the growth suppression in NH4+-nourished plants, with limited studies conducted specifically on field crop plants. In this study, we found that NH4+ toxicity significantly increased salicylic acid (SA) accumulation by accelerating the conversion of SA precursors. Moreover, exogenous SA application significantly aggravated NH4+ toxicity symptoms in the rapeseed shoots. Genome-wide differential transcriptomic analysis showed that NH4+ toxicity increased the expression of genes involved in the biosynthesis, transport, signaling transduction, and conversion of SA. SA treatment significantly increased shoot NH4+ concentrations by reducing the activities of glutamine synthase and glutamate synthase in NH4+-treated rapeseed plants. The application of an SA biosynthesis inhibitor, ABT, alleviated NH4+ toxicity symptoms. Furthermore, SA induced putrescine (Put) accumulation, resulting in an elevated ratio of Put to [spermidine (Spd) + spermine (Spm)] in the NH4+-treated plants, while the opposite was true for ABT. The application of exogenous Put and its biosynthesis inhibitor DFMA induced opposite effects on NH4+ toxicity in rapeseed shoots. These results indicated that the increased endogenous SA contributed noticeably to the toxicity caused by the sole NH4+-N supply in rapeseed shoots. This study provided fresh perspectives on the mechanism underlying excessive NH4+-induced toxicity and the corresponding alleviating strategies in plants.

Hybrid Advanced Control Strategy for Post-Combustion Carbon Capture Plant by Integrating PI and Model-Based Approaches

Even though the energy penalties and solvent regeneration costs associated with amine-based absorption/stripping systems are important challenges, this technology remains highly recommended for post-combustion decarbonization systems given its proven capture efficacy and technical maturity. This study introduces a novel centralized and decentralized hybrid control strategy for the post-combustion carbon capture plant, aimed at mitigating main disturbances and sustaining high system performance. The strategy is rooted in a comprehensive mathematical model encompassing absorption and desorption columns, heat exchangers and a buffer tank, ensuring smooth operation and energy efficiency. The buffer tank is equipped with three control loops to finely regulate absorber inlet solvent solution parameters, preventing disturbance recirculation from the desorber. Additionally, a model-based controller, utilizing the model predictive control (MPC) algorithm, maintains a carbon capture yield of 90% and stabilizes the reboiler liquid temperature at 394.5 K by manipulating the influent flue gas to the lean solvent flowrates ratio and the heat duty of the reboiler. The hybrid MPC approach reveals efficiency in simultaneously managing targeted variables and handling complex input–output interactions. It consistently maintains the controlled variables at desired setpoints despite CO2 flue gas flow disturbances, achieving reduced settling time and low overshoot results. The hybrid control strategy, benefitting from the constraint handling ability of MPC, succeeds in keeping the carbon capture yield above the preset minimum value of 86% at all times, while the energy performance index remains below the favorable value of 3.1 MJ/kgCO2.

Safety Management and Accident-Control Strategy for a Commercial-Scale Plant for Supercritical Water Oxidation of Sludge

Supercritical water oxidation is a promising technology for decomposition of industrial wastewater and sludge. However, the system is operated under high temperature and pressure (usually higher than 500 °C and 25 MPa). Corrosion of component materials and salt deposition may lead to leakage or even the burst of the pressure vessel in the SCWO system, resulting in a high level of worry about the safe operation of the system. In this paper, the safety management and accident- control strategies are introduced according to a commercial-scale SCWO plant in China. The safety management strategy refers to the special design and operation strategies of some facilities. Different types of potential accidents are analyzed and the coping strategies for accidents of different levels of severity are described in detail. The strategies are valuable for the safe operation of commercial SCWO plants and other plants operated in high temperature and high pressure.

Tree species mixing effects on the radial growth of Pinus massoniana and Castanopsis hystrix: A comparison between even-aged and uneven-aged stands

The establishment of mixed-species forests with complex structures and high biodiversity has emerged as a key approach for enhancing productivity and maintaining the stability of plantation forests. However, how the mixing effect changes with stand development and climate variation is still unclear. Additionally, little is known about how the mixing effects vary between even- and uneven-aged mixed planting strategies based on the same species combinations and site conditions. In this study, we used dendrochronological methods to reconstruct 37 years of annual growth series for even-aged mixed plantations (EMs) and uneven-aged mixed plantations (UEMs) of Pinus massoniana and Castanopsis hystrix, as well as their respective monocultures at the individual tree (286 trees in total) level. We found that in EMs, the growth of P. massoniana and C. hystrix was 20.8 % lower and 26.2 % higher than those of their monocultures, respectively. However, the growth of P. massoniana remained unchanged during the first 17 years of mixing, after which it was significantly suppressed by C. hystrix. The growth of P. massoniana and C. hystrix in the UEMs was 20.8 % and 26.2 % lower than that in their monocultures, respectively. Remarkably, the mixing effect on the growth of P. massoniana shifted from suppression to promotion after 30 years of mixing. Furthermore, the relative growth of P. massoniana in the UEMs increased with dry season precipitation. These results indicate that transforming pure plantations into uneven-aged mixed plantations may be a crucial forest management strategy for enhancing tree growth and to improving adaptation to future precipitation pattern changes. However, in EMs, thinning should be conducted before fast-growing, shade-intolerant species experience intense light competition.

Understanding Stress Corrosion Cracking (SCC), Affecting Variables and Prevention Strategies in Nuclear Power Plants—A Review

Understanding Stress Corrosion Cracking (SCC), Affecting Variables and Prevention Strategies in Nuclear Power Plants—A Review

Unifying functional and population ecology to test the adaptive value of traits.

Plant strategies are phenotypes shaped by natural selection that enable populations to persist in a given environment. Plant strategy theory is essential for understanding the assembly of plant communities, predicting plant responses to climate change, and enhancing the restoration of our degrading biosphere. However, models of plant strategies vary widely and have tended to emphasize either functional traits or life-history traits at the expense of integrating both into a general framework to improve our ecological and evolutionary understanding of plant form and function. Advancing our understanding of plant strategies will require investment in two complementary research agendas that together will unify functional ecology and population ecology. First, we must determine what is phenotypically possible by quantifying the dimensionality of plant traits. This step requires dense taxonomic sampling of traits on species representing the broad diversity of phylogenetic clades, environmental gradients, and geographical regions found across Earth. It is important that we continue to sample traits locally and share data globally to fill biased gaps in trait databases. Second, we must test the power of traits for explaining species distributions, demographic rates, and population growth rates across gradients of resource limitation, disturbance regimes, temperature, vegetation density, and frequencies of other strategies. This step requires thoughtful, theory-driven empiricism. Reciprocal transplant experiments beyond the native range and synthetic demographic modelling are the most powerful methods to determine how trait-by-environment interactions influence fitness. Moving beyond easy-to-measure traits and evaluating the traits that are under the strongest ecological selection within different environmental contexts will improve our understanding of plant adaptations. Plant strategy theory is poised to (i) unpack the multiple dimensions of productivity and disturbance gradients and differentiate adaptations to climate and resource limitation from adaptations to disturbance, (ii) distinguish between the fundamental and realized niches of phenotypes, and (iii) articulate the distinctions and relationships between functional traits and life-history traits.

Investigation of Marketing Strategies of Ornamental Plants in Konya Province

The aim of this study is to examine the marketing strategies of ornamental plants in Konya province, to determine the target markets that the sector can best serve, and to evaluate all the components that can contribute to the development of the sector on a provincial basis. In this context, the sales and marketing strategies of the companies producing and selling in Konya province were identified, suggestions for improvement were presented and the potential of ornamental plants in the region was determined. It is believed that the study will make an important contribution to the literature in this area. The main body of the research consists of ornamental plant companies selling in Konya province. In order to answer the questions of the study, a face-to-face survey was conducted with 32 operators representing the main mass. Porter’s Diamond model was used to evaluate the competitiveness. As a result of the analysis of the data, it was observed that the competitiveness of the companies is low and they are not looking for alternative markets. The lack of legislation defining the sector, the problem of organisation, the fact that they consider their income to be sufficient and the lack of information at the point of sale are the main obstacles to competitiveness. In fact, the main priority for a company is to gain a competitive position in order to increase profit margins. For this reason, companies need to evaluate the opportunities that may present themselves, develop strategies to add value to customers in the long term, and determine strategies to be close to the market in order to create new markets.