Long-term Growth Rate Research Articles

Spatial consistency in drivers of population dynamics of a declining migratory bird.

Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets. We capitalized on a recent data harmonization initiative (SPI-Birds) and linked it to a generalized modelling framework to identify the demographic and environmental drivers of large-scale population decline in migratory pied flycatchers (Ficedula hypoleuca) breeding across Britain. We implemented a generalized integrated population model (IPM) to estimate age-specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long-term (34-64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structure to changes in short- and long-term population growth rate using transient life table response experiments (LTREs). Substantial covariation in population sizes across breeding locations suggested that change was the result of large-scale drivers. This was supported by LTRE analyses, which attributed past changes in short-term population growth rates and long-term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or nonbreeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period. We show that both short- and long-term population changes of British breeding pied flycatchers are likely linked to factors acting during migration and in nonbreeding areas, where future research should be prioritized. We illustrate the potential of multi-population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them.

Empirická analýza vybraných predikčních metod jako podkladu pro odhad dlouhodobého tempa růstu při výnosovém ocenění podniku

Empirická analýza vybraných predikčních metod jako podkladu pro odhad dlouhodobého tempa růstu při výnosovém ocenění podniku

Dynamics of neonatal morbidity in children with large body weight

Preservation of the health of each child is the basis of the activities of the service for protection of motherhood and childhood. The article presents the results of analysis of the structure of births by body weight. A retrospective analysis of the incidence of full-term children with large (4000 g or more) body weight at birth in Minsk for the period 2004–2019 was carried out according to state statistics. It was revealed that the average proportion value of large newborns was 10.1 ± 0.07 %. During the analyzed period, the incidence rate of newborns with a birth weight of 4000 g or more decreased (278.4 ‰ in 2004, 177.8 ‰ in 2019, the average long-term growth rate was ‒2.95 %). When analyzing the morbidity structure of newborns, the leading place was occupied by individual conditions that occur in the perinatal period, 87.2 ± 0.80 %. In the analyzed time interval of 2004–2019, diseases with the highest degree of association with biggest birth weight were other birth trauma (OR = 2.30 (2.19–2.43), p < 0.001), endocrine and metabolic disorders (OR = 2.19 (2.04–2.34), p < 0.001).

Effect of compositional fluctuation on the survival of bet-hedging species

Understanding the coexistence of diverse species in a changing environment is an important problem in community ecology. Bet-hedging is a strategy that helps species survive in such changing environments. However, studies of bet-hedging have often focused on the expected long-term growth rate of the species by itself, neglecting competition with other coexisting species. Here we study the extinction risk of a bet-hedging species in competition with others. We show that there are three contributions to the extinction risk. The first is the usual demographic fluctuation due to stochastic reproduction and selection processes in finite populations. The second, due to the fluctuation of population growth rate caused by environmental changes, may actually reduce the extinction risk for small populations. Besides those two, we reveal a third contribution, which is unique to bet-hedging species that diversify into multiple phenotypes: The phenotype composition of the population will fluctuate over time, resulting in increased extinction risk. We compare such compositional fluctuation to the demographic and environmental contributions, showing how they have different effects on the extinction risk depending on the population size, generation overlap, and environmental correlation.

Is Expected Inflation the Best Long-term Sustainable Growth Rate?

When using the income approach to value a business, selecting a sustainable long-term growth rate is a necessary input into the valuation model, one that can have a material effect on the value of the business. The business valuation literature has provided little guidance for estimating and understanding sustainable long-term growth rates. Apart from relying on macroeconomic indicators and historical industry averages, appraisers have few options for selecting sustainable long-term growth rates and are often relegated to making arbitrary assumptions. The objective of this article is to examine the accuracy of using historical industry average growth rates, historical average gross domestic product growth rates, and expected inflation as sustainable long-term growth rates. The accuracy of the forecasts was examined vis-à-vis actual growth rates for twenty-one selected industries from 1991 to 2021 for the purpose of selecting the most accurate forecasting method. The forecasts premised on expected inflation proved to be the most accurate. In light of the results, the notion that expected inflation may be the best estimate of sustainable long-term growth was explored.

From the Editor

Sustainable growth is one of the key inputs in the income approach. I have seen wide variation in practice over time with respect to selection of a sustainable growth rate ranging from long-term targets for inflation, expected industry growth rates, T-Bond yields and expected growth of the Gross Domestic Product. This list is clearly not exhaustive; I have seen many different variations with high growth companies. Shannon Pratt illustrated the significance of the long-term growth rate in the following passage from Valuing a Business:As the example illustrates, minor differences in sustainable growth rates can have very significant impacts on an opinion of value. This issue contains two papers that directly address the issue of sustainable growth. Dr. Gene Trevino analyzes the issue from the standpoint of the accuracy of using historical industry growth rates, historical gross domestic product growth rates and expected inflation rates as sustainable long-term growth rates, while Dr. Brad Cornell and Richard Gerger approach the topic by analyzing historic growth of public companies. Their findings are surprisingly similar.David Neuzil and Joe Thompson revisit the Value Driver Formula and illustrate short-comings of a traditional Gordon Growth Model in valuing a business that invest heavily in research and development.Finally, the issue has a Special Report from the International Valuation Standard Council (“IVSC”) on Environmental, Social and Governance (“ESG”) issues in valuation. The IVSC has been busy developing technical resources for valuation professional in the evolving area of ESG and its application in business valuation. The Special Report provides an overview of those resources and ongoing work in the area.To all our readers, enjoy the issue and let me know if you have any strong opinion or further thoughts on our articles – letters to the editor are welcome.

Long-term soil water limitation and previous tree vigor drive local variability of drought-induced crown dieback in Fagus sylvatica

Ongoing climate warming is increasing evapotranspiration, a process that reduces plant-available water and aggravates the impact of extreme droughts during the growing season. Such an exceptional hot drought occurred in Central Europe in 2018 and caused widespread defoliation in mid-summer in European beech (Fagus sylvatica L.) forests.Here, we recorded crown damage in 2021 in nine mature even-aged beech-dominated stands in northwestern Switzerland along a crown damage severity gradient (low, medium, high) and analyzed tree-ring widths of 21 mature trees per stand. We aimed at identifying predisposing factors responsible for differences in crown damage across and within stands such as tree growth characteristics (average growth rates and year-to-year variability) and site-level variables (mean canopy height, soil properties).We found that stand-level crown damage severity was strongly related to soil water availability, inferred from tree canopy height and plant available soil water storage capacity (AWC). Trees were shorter in drier stands, had higher year-to-year variability in radial growth, and showed higher growth sensitivity to moisture conditions of previous late summer than trees growing on soils with sufficient AWC, indicating that radial growth in these forests is principally limited by soil water availability. Within-stand variation of post-drought crown damage corresponded to growth rate and tree size (diameter at breast height, DBH), i.e., smaller and slower-growing trees that face more competition, were associated with increased crown damage after the 2018 drought. These findings point to tree vigor before the extreme 2018 drought (long-term relative growth rate) as an important driver of damage severity within and across stands. Our results suggest that European beech is less likely to be able to cope with future climate change-induced extreme droughts on shallow soils with limited water retention capacity.

Application of modern coexistence theory to rare plant restoration provides early indication of restoration trajectories.

Restoration ecology commonly seeks to re-establish species of interest in degraded habitats. Despite a rich understanding of how succession influences re-establishment, there are several outstanding questions that remain unaddressed: are short-term abundances sufficient to determine long-term re-establishment success, and what factors contribute to unpredictable restorations outcomes? In other words, when restoration fails, is it because the restored habitat is substandard, because of strong competition with invasive species, or alternatively due to changing environmental conditions that would equally impact established populations? Here, we re-purpose tools developed from modern coexistence theory to address these questions, and apply them to an effort to restore the endangered Contra Costa goldfields (Lasthenia conjugens) in constructed ("restored") California vernal pools. Using 16 years of data, we construct a population model of L. conjugens, a species of conservation concern due primarily to habitat loss and invasion of exotic grasses. We show that initial, short-term appearances of restoration success from population abundances is misleading, as year-to-year fluctuations cause long-term population growth rates to fall below zero. The failure of constructed pools is driven by lower maximum growth rates compared with reference ("natural") pools, coupled with a stronger negative sensitivity to annual fluctuations in abiotic conditions that yield decreased maximum growth rates. Nonetheless, our modeling shows that fluctuations in competition (mainly with exotic grasses) benefit L. conjugens through periods of competitive release, especially in constructed pools of intermediate pool depth. We therefore show how reductions in invasives and seed addition in pools of particular depths could change the outcome of restoration for L. conjugens. By applying a largely theoretical framework to the urgent goal of ecological restoration, our study provides a blueprint for predicting restoration success, and identifies future actions to reverse species loss.

Effects of habitat disturbance and rainfall on a dominant medicinal dry forest tree

The interactive effects of anthropogenic disturbance and climatic variables can shape the demography of plant populations, but they remain poorly understood especially for long-lived species like tropical trees. Understanding these interactions is critical for designing forest management strategies in the face of both growing anthropogenic pressures and climate change. We explored the effects of habitat disturbance and interannual variation in rainfall on the population dynamics of Amphipterygium adstringens (Anacardiaceae), an ecologically dominant tree species endemic to the tropical deciduous forests of Mexico, that is heavily harvested for its medicinal bark. Specifically, we compared A. adstringens vital rates and long-term population growth rates of unharvested populations in a disturbed versus a protected tropical deciduous forest site; and explored the effects of inter-annual variation in annual rainfall on A. adstringens by comparing vital rates and population growth rates across three years with differing levels of rainfall. We established four plots in each of the two sites and monitored survival, growth and reproduction of 251 individuals over three years. We found that anthropogenic disturbance and rainfall differentially affected the vital rates of A. adstringens. Survival did not differ across sites or years. Growth tended to be lower and fecundity higher, in the protected site, but these effects varied across years and as a function of plant size. No seedlings were found in the disturbed site over the three years study period. Integral projection models showed that projected population growth rates (λ values) in the protected site were higher and much less variable over time than those of the disturbed site. Lambda values in the disturbed site were <1, indicating long-term population decline. In both sites, the rainiest year showed the highest population growth rate but the increase in λ was much higher in the disturbed site than in the protected site. These findings suggest that the population dynamics of A. adstringens are heavily affected by habitat disturbance forest management regime and that the impacts of interannual variability in rainfall or other environmental conditions may be exacerbated in disturbed conditions. The persistence of A. adstringens populations over time will require the exclusion of livestock as well as the implementation of silvicultural practices that will lead to seedling establishment and survival. This study provides key data for the management and conservation of A. adstringens, a highly valued medicinal species.

Analyzing dynamic species abundance distributions using generalized linear mixed models.

Understanding the mechanisms of ecological community dynamics and how they could be affected by environmental changes is important. Population dynamic models have well known ecological parameters that describe key characteristics of species such as the effect of environmental noise and demographic variance on the dynamics, the long‐term growth rate, and strength of density regulation. These parameters are also central for detecting and understanding changes in communities of species; however, incorporating such vital parameters into models of community dynamics is challenging. In this paper, we demonstrate how generalized linear mixed models specified as intercept‐only models with different random effects can be used to fit dynamic species abundance distributions. Each random effect has an ecologically meaningful interpretation either describing general and species‐specific responses to environmental stochasticity in time or space, or variation in growth rate and carrying capacity among species. We use simulations to show that the accuracy of the estimation depends on the strength of density regulation in discrete population dynamics. The estimation of different covariance and population dynamic parameters, with corresponding statistical uncertainties, is demonstrated for case studies of fish and bat communities. We find that species heterogeneity is the main factor of spatial and temporal community similarity for both case studies.

REVIVING THE KLANG VALLEY ECONOMY DURING PANDEMIC THROUGH DIGITALISATION OF THE MARITIME LOGISTICS INDUSTRY

The maritime logistics industry is an international business ecosystem and backbone of Malaysia’s economic development. Due to the COVID-19 pandemic, we have witnessed a drastic decline of industries all over the world, which may take a very long time to recover. This paper discusses the digital transformation of the maritime logistics industry based in the Klang Valley of Peninsular Malaysia as a strategic plan to improve existing business processes and make it resilient in face of the challenges brought on by the pandemic. We evaluated the digitalisation practices of maritime logistics companies to identify enablers that can help restore the economy as the industry tries to move on under the shadow of COVID-19. The Fuzzy Delphi (FD) method is used to collect and analyse data based on the response of 18 experts with more than five years of industry experience. A total of 15 key enablers were determined and ranked in terms of priority, with the top three being changes in the long-term industry growth rate, marketing innovation and implementation of digital platforms. These key enablers may then be used to develop good strategies to enhance competitiveness and build the resilience of this sector against the disruptions brought on by the pandemic.

Temporal variation may have diverse impacts on range limits.

Environmental fluctuations are pervasive in nature, but the influence of non-directional temporal variation on range limits has received scant attention. We synthesize insights from the literature and use simple models to make conceptual points about the potentially wide range of ecological and evolutionary effects of temporal variation on range limits. Because organisms respond nonlinearly to environmental conditions, temporal variation can directionally alter long-term growth rates, either to shrink or to expand ranges. We illustrate this diversity of outcomes with a model of competition along a mortality gradient. Temporal variation can permit transitions between alternative states, potentially facilitating range expansion. We show this for variation in dispersal, using simple source–sink population models (with strong Allee effects, or with gene flow hampering local adaptation). Temporal variation enhances extinction risk owing to demographic stochasticity, rare events, and loss of genetic variation, all tending to shrink ranges. However, specific adaptations to exploit variation (including dispersal) may permit larger ranges than in similar but constant environments. Grappling with temporal variation is essential both to understand eco-evolutionary dynamics at range limits and to guide conservation and management strategies.This article is part of the theme issue ‘Species’ ranges in the face of changing environments (Part II)’.

The Disconnect Between Short- and Long-Term Population Projections for Plant Reintroductions

The reintroduction of rare species in natural preserves is a commonly used restoration strategy to prevent species extinction. An essential first step in planning successful reintroductions is identifying which life stages (e.g., seeds or large adults) should be used to establish these new populations. Following this initial establishment phase, it is necessary to determine the level of survival, growth, and recruitment needed to maintain population persistence over time and identify management actions that will achieve these goals. In this 5-year study, we projected the short- and long-term population growth rates of a critically endangered long-lived shrub, Delissea waianaeensis. Using this model system, we show that reintroductions established with mature individuals have the lowest probability of quasi-population extinction (10 individuals) and the highest increase in population abundance. However, our results also demonstrate that short-term increases in population abundances are overly optimistic of long-term outcomes. Using long-term stochastic model simulations, we identified the level of natural seedling regeneration needed to maintain a positive population growth rate over time. These findings are relevant for planning future reintroduction efforts for long-lived species and illustrate the need to forecast short- and long-term population responses when evaluating restoration success.

A Subset of Intracanalicular Vestibular Schwannomas Demonstrates Minimal Growth Over a 10-Year Period.

Vestibular schwannomas (VS) commonly undergo magnetic resonance imaging (MRI) surveillance, but long-term data to support the ideal frequency is limited. Herein, we aim to investigate intracanalicular VS growth predictors and long-term growth rates (GR). Retrospective chart review. Two tertiary care centers. Sporadic intracanalicular VS with initial conservative management and at least two sequential MRIs. Serial MRI. VS were categorized by baseline internal auditory canal tertile sublocalization (fundus, midpoint, porus) and size (≤100, 100-200, >200 mm3). Throughout follow-up, volumetric GR (mm3/yr) were determined (baseline-3 yrs, 3-5 yrs, 5-10 yrs) and treatment rates were assessed. Ninety-nine intracanalicular VS were identified (mean follow-up of 6.1 ± 4.5 yrs). Mean GR before 5-year follow-up were comparable for baseline tertile involvement and size. After 5-year follow-up, mean GR of VS involving the fundus at baseline were lower than those involving the midpoint and fundus (6.17 ± 21.16 and 119.74 ± 117.57 mm3/yr, respectively; p = 0.034). Mean GR of VS with less than or equal to 100 mm3 at baseline (-7.29 ± 25.44 mm3/yr) were lower than those with 100 to 200 mm3 (86.55 ± 103.99 mm3/yr; p = 0.011) and more than 200 mm3 (45.70 ± 35.71 mm3/yr; p = 0.031). Vestibular schwannomas involving the midpoint and fundus had greater treatment rates compared with VS involving only the fundus (p < 0.001). Baseline tertile involvement and size may predict long-term intracanalicular VS growth where fundal tumors or those less than or equal to 100 mm3 exhibit little long-term growth. Extending surveillance after 5-year follow-up may be reasonable for fundal VS.

Long-term Growth Rates in Discounted Cash Flow Models

Long-term Growth Rates in Discounted Cash Flow Models

Economic complexity and price competitiveness dependence: empirical evidence using panel models

PurposeAs economies with high economic complexity and productive capabilities may easily adapt their productive structure due to product differentiation and innovation, the central variable of competitiveness for these countries is the product quality, not price. On the other hand, the price can be an important determinant of less complex countries, and hence, real exchange rate (RER) misalignments may have long-term impacts. This paper aims to empirically assess variations in the magnitude of the impact in RER misalignments on output growth subject to countries’ economic complexity.Design/methodology/approachThe estimation technique used is the generalized method of moments-System estimator as this method is robust to reverse causality. Heterogeneous regressions using interaction models are undertaken to analyze to what extend promoting economic complexity can reduce price competitiveness dependence and allow countries to grow faster without relying on cost competitiveness.FindingsEstimates show that economic complexity (which measures technological and productive capabilities) determines cross-country differences regarding the effects of RER misalignments on countries’ long-term growth rates. The results suggest that exchange rate devaluations may not be effective for countries at the top end of the technological ladder while an overvalued RER may damage the long-term growth rate of countries with low levels of economic complexity.Originality/valueThis paper contributes to the literature by empirically investigating the impact of RER misalignments in countries with distinct technological and productive capabilities based on the recent developments of countries’ economic complexity analysis. It investigates whether more diversified and complex economies are less sensitive to RER misalignments as they can adapt their production, undertake other tasks, create new products and increase the quality of products they produce. Less complex economies, on the other hand, are less capable of innovating because it demands productive capabilities they do not have, and hence, they are more dependent on their current export basket.

Long-Term Gully Erosion and Its Response to Human Intervention in the Tableland Region of the Chinese Loess Plateau

The gully erosion process is influenced by both natural conditions and human activities on the tableland region, the Chinese Loess Plateau, which is a densely populated agricultural area with unique topography. For the purpose of assessing long-term gully growth rates, the influencing factors and potential of gully growth, KH-4B satellite images, Quickbird-2 images, and unmanned aerial vehicle (UAV) images were used to assess gully erosion from 1969 to 2019. The effects of runoff, topography and human activities were analyzed with information derived from historical and present images. Ninety-five investigated gullies were classified into four types: 45 growing, 25 stable, 21 infilled and four excavated gullies. The rates (RA) of 45 growing gullies ranged from 0.50 to 20.94 m2·yr−1, with an average of 5.66 m2·yr−1 from 1969 to 2010. The present drainage area, local slope, average drainage slope, annual runoff, and ratio of the terraced area were all significantly different between the stable and growing gullies. The long-term gully growth rate could be estimated using a nonlinear regression model with annual runoff (Qa) and the slope of the drainage area (Sd) as predictors (RA = 0.301Qa0.562Sd, R2 = 0.530). Based on the Sg-A and Sg-Qa relationship that was used to reveal the threshold conditions for gully growth, all growing gullies still have the potential to keep growing, but soil and water conservation measures, including terraces, could change the threshold condition by reducing the effective drainage area. The results of this study could be helpful for preventing further gully erosion by dealing with gullies far above the threshold line.

The Determinants and Effects of Competitiveness: The Role of Digitalization in the European Economies

Improving national competitiveness is fundamental to raising long-term economic growth rates and enhancing living standards. The determinants of competitiveness change along with macroeconomic factors, business environment and consumer demand. These changes are visible in the growing importance of digitalization of enterprises of all sectors that has become a critical factor for competitiveness in recent years and will likely become even more essential. The main determinants of competitiveness performance in the European Union (EU) were analyzed in the proposed research. The study included a holistic approach to competitiveness and economic growth and aimed to reveal the factors that determine and contribute to the growth of European economies, as well as to identify clusters of the EU countries. The criteria of competitiveness that are significant for estimation of competitiveness factors and their relationship with economic growth were revealed by using factor analysis. The results indicate that the most significant factors are F1 Macroeconomic Stability, F2 Research and Development (R&amp;D) and Digitalization, F3 Foreign Direct Investment and F4 Trade Openness. By applying cluster analysis, the EU countries were grouped into five clusters on the basis of the contribution of competitiveness factors to economic growth.

What Drives Growth: Analyzing Quantitative Factors and their Variation across Sectors

Value investing is often considered the antithesis of growth investing. However, core to any value investing strategy is an intrinsic valuation, typically calculated using a DCF analysis. One of the most sensitive DCF assumptions is the estimation of a company’s long-term cash flow growth rate. Thus, understanding a company’s growth potential is a vital component in any value thesis. This paper attempts to create a quantitative model to help predict a company’s long-term cash flow growth rate (using EBITDA growth as a proxy for cash flow growth) and to find the strongest indicators for a company’s growth potential by sector. To do so, this study analyzes variables pertaining to operating efficiency, risk metrics, market valuation, corporate investment levels, and the competitive landscape for S&amp;P 500 constituent companies. While all categories contributed at least one statistically significant variable, the market valuation and corporate investment level categories had the highest volume of significant variables. The results show that widely used quantitative metrics can help predict a meaningful portion of a company’s five-year EBITDA growth rate when analyzed on a sector-by-sector basis. Furthermore, both the types of variables and predictive strength of the model varies widely across sectors. In practice, analysts should prioritize different ratios, metrics, and quantitative variables based on the target company’s sector when estimating the trajectory of a company’s long-term growth rate.

The new post‐covid long term looks much like the old one

▪ We have become more optimistic that the long‐term damage to the world economy from the coronavirus crisis will be less than we originally anticipated, especially because of the rapid rebound of output and financial markets. Our baseline forecasts now estimate the level of world GDP being reduced by less than 1% over the long‐term – a considerable upgrade from a year ago. ▪ Key positives are the fast recovery in output, employment, and asset prices, which have rebounded from 2020's troughs far faster than after the global financial crisis. Early evidence also suggests much less financial ‘scarring’ than after the GFC – the trajectories of bad loans, firm failures, and bank credit standards are much more favourable. ▪ But the rate of long‐term world growth will be low as all the pre‐pandemic drags on growth resurface. After two very strong years in 2021 and 2022, we forecast that world growth will then be modest, averaging 2.7% per year to 2030 – below the long‐term average of the last forty years and lower than in 2011–2019. ▪ Key drivers of long‐term growth – demographic trends, capital stock growth, and total factor productivity growth, will all remain subdued. Growth faces headwinds from structural factors like high public and private debt, a loss of dynamism in the advanced economies, and slower growth in emerging markets. ▪ The pandemic also adds some new downside risks. Some financial scars from the pandemic may emerge later, sustained disruption to supply chains is possible, firms and households may be more cautious, and governments may react to high public debt with excessive austerity. Macroeconomic instability in emerging markets may also further weaken trend growth there.