The Impact of Fine-Scale Disturbances on the Predictability of Vegetation Dynamics and Carbon Flux

Predictions from forest ecosystem models are limited in part by large uncertainties in the current state of the land surface, as previous disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect. Likewise, future disturbances also present a challenge to prediction as their dynamics are episodic and complex and occur across a range of spatial and temporal scales. While large extreme events such as tropical cyclones, fires, or pest outbreaks can produce dramatic consequences, small fine-scale disturbance events are typically much more common and may be as or even more important. This study focuses on the impacts of these smaller disturbance events on the predictability of vegetation dynamics and carbon flux. Using data on vegetation structure collected for the same domain at two different times, i.e. “repeat lidar data”, we test high-resolution model predictions of vegetation dynamics and carbon flux across a range of spatial scales at an important tropical forest site at La Selva Biological Station, Costa Rica. We found that predicted height change from a height-structured ecosystem model compared well to lidar measured height change at the domain scale (~150 ha), but that the model-data mismatch increased exponentially as the spatial scale of evaluation decreased below 20 ha. We demonstrate that such scale-dependent errors can be attributed to errors predicting the pattern of fine-scale forest disturbances. The results of this study illustrate the strong impact fine-scale forest disturbances have on forest dynamics, ultimately limiting the spatial resolution of accurate model predictions.     

Changes in biodiversity and ecosystem function during the restoration of a tropical forest in south China

Tropical forests continue to vanish rapidly,but few long-term studies have ever examined if and how the lost forests can be restored.Based on a 45-year restoration study in south China,we found that a tropical rain forest,once completely destroyed,could not recover naturally without deliberate restoration efforts.We identified two kinds of thresholds that must be overcome with human ameliorative measures before the ecosystem was able to recover.The first threshold was imposed primarily by extreme physical conditions such as exceedingly high surface temperature and impoverished soil,while the second was characterized by a critical level of biodiversity and a landscape context that accommodates dispersal and colonization processes.Our three treatment catchments(un-restored barren land,single-species plantation,and mixed-forest stand)exhibited dramatically different changes in biodiversity and ecosystem functioning over 4 decades.The mixed forest,having the highest level of biodiversity and ecosystem functioning,possesses several major properties of tropical rain forest.These findings may have important implications for the restoration of many severely degraded or lost tropical forest ecosystems.     

Changes in biodiversity and ecosystem function during the restoration of a tropical forest in south China

Tropical forests continue to vanish rapidly, but few long-term studies have ever examined if and how the lost forests can be restored. Based on a 45-year restoration study in south China, we found that a tropical rain forest, once completely destroyed, could not recover naturally without deliberate restoration efforts. We identified two kinds of thresholds that must be overcome with human ameliorative measures before the ecosystem was able to recover. The first threshold was imposed primarily by extreme physical conditions such as exceedingly high surface temperature and impoverished soil, while the second was characterized by a critical level of biodiversity and a landscape context that accommodates dispersal and colonization processes. Our three treatment catchments (un-restored barren land, single-species plantation, and mixed-forest stand) exhibited dramatically different changes in biodiversity and ecosystem functioning over 4 decades. The mixed forest, having the highest level of biodiversity and ecosystem functioning, possesses several major properties of tropical rain forest.These findings may have important implications for the restoration of many severely degraded or lost tropical forest ecosystems.     

退化森林生态系统评价指标体系研究进展

森林是陆地生态系统的主要组成部分,而森林退化是全球面临的主要环境问题之一,准确评价退化森林生态系统是进行森林生态系统恢复与重建的重要前提,建立合理的评价指标体系目前已成为生态学研究的热点问题。在研究国内外提出的关于退化森林生态系统评价理论的基础上,综述了森林退化的定义、特征和一般过程,梳理了退化森林生态系统评价指标筛选的一般原则和指标体系构建的主要方法,分析比较了不同学者所提出的主要评价指标。并在此基础上,重新筛选、构建了一套退化森林生态系统评价指标体系,即从生态系统的组成结构、功能和生境这3个方面选取了32个能够较全面反映退化生态系统主要特征的评价指标,以期为构建我国区域尺度上的退化森林生态系统评价指标体系提供参考,为退化森林生态系统的恢复和重建提供科学依据。总结分析了退化森林生态系统评价指标体系在构建过程中产生的一些问题和不足,提出了今后开展研究和探索应该深入的方向,以提高评价指标体系的科学性、准确性和合理性。     

Global vegetation models: incorporating transient changes to structure and composition

Abstract. We describe an approach for developing a Dynamic Global Vegetation Model (DGVM) that accounts for transient changes in vegetation distribution over a decadal time scale. The DGVM structure is based on a linkage between an equilibrium global vegetation model and smaller scale ecosystem dynamics modules that simulate the rate of vegetation change. Vegetation change is classified into four basic types, based largely on the projected change in above-ground biomass of the vegetation. These four types of change are: (1) dieback of forest, shrubland or grassland; (2) successional replacement within forest, shrubland or grassland; (3) invasion of forest, shrubland or grassland; (4) change in tree/grass ratio. We then propose an approach in which the appropriate ecosystem dynamics module for each type of change is applied and the grid cells of the global model updated accordingly. An approach for accounting for fire, as an example of a disturbance which may strongly influence the rate and spatial pattern of forest dieback, is incorporated. We also discuss data needs for the development, calibration and validation of the model.     

Lodgepole pine forest age class dynamics and susceptibility to mountain pine beetle attack

Because mountain pine beetle attack mature pine stands, an understanding of forest age class dynamics is important to managing forests within the distribution of the beetle. The assumed theoretical negative exponential forest age distribution provides an estimate when ecosystem dynamics are in equilibrium. This study investigates the dynamics of forest age distribution for non-equilibrium ecosystem dynamics, which result primarily from large and irregular stand-replacement fire disturbances that alter the forest age distribution. A model experiment using the SEM-LAND model on a 1 million ha lodgepole pine forest landscape was conducted to estimate how the proportion of susceptible area could be influenced by different fire regimes. The results of the simulation suggest that the temporal dynamics of the area susceptible to mountain pine beetle attack are complex and depend on the fire history of the study area, if the area is experiencing large and irregular stand-replacement fires. The age range of the lodgepole pine forest stands susceptible to mountain pine beetle attack might significantly affect the estimate of the area susceptible to attack.     

Spatiotemporal behavior of a prey–predator system with a group defense for prey

Group defense is a strategy widely employed by various species. We consider the effect of grouping on population persistence when animals join together in herds in order to provide a self-defense from predators. In literature, group defense is usually addressed in terms of individual behavioral responses. In this paper, we consider an alternative ‘mean-field’ approach which uses prey and predator densities as the dynamical variables. The model is essentially a predator–prey system but with an unconventional parametrization for the predation term. We discuss the outcomes of the ecosystem dynamics in terms of persistence and prey survival. In the spatially distributed model some specific spatio-temporal features are discovered.     

Persistence of pyrophilous insects in fire-driven boreal forests: population dynamics in burned and unburned habitats

Several boreal insect species respond to smoke and heat generated by forest fires and use recent burns to reproduce in high numbers. Some of these species are rare or uncommon in undisturbed forests, and the contribution of recently burned habitats to their population dynamics has been deemed crucial by some to their long-term persistence. Consequently, the severe decline seen in some species in Fennoscandia has been frequently linked with fire suppression. In this paper, we explore some aspects of the spatial dynamics of pyrophilous insect populations in relation to the expected relative contribution of burned and unburned habitats to their global population dynamics. Forest fires are, throughout the boreal forest biome, generally highly aggregated in some years while rare in most other years. The low connectivity between fire events and the typical life cycle seen in these species make it improbable that recent burns act as significant population sources. This leads us to suggest that populations of pyrophilous species may be more limited by the adequacy of the unburned matrix than by the occurrence of fire events. Moreover, by combining an age-class distribution model and a dead wood availability model, we show that the quality of the unburned matrix increases in landscapes with longer fire cycles, in which pyrophilous insects should persist at higher population levels. We conclude that the degradation of the unburned habitat better explains the decline of pyrophilous insects than fire suppression alone.     

Diverse water quality responses to extreme climate events: an introduction

We synthesize and summarize main findings from a special issue examining the origins, evolution, and resilience of diverse water quality responses to extreme climate events resulting from a Chapman Conference of the American Geophysical Union (AGU). Origins refer to sequences of interactive disturbances and antecedent conditions that influence diversification of water quality responses to extreme events. Evolution refers to the amplification, intensification, and persistence of water quality signals across space and time in watersheds. Resilience refers to strategies for managing and minimizing extreme water quality impacts and ecosystem recovery. The contributions of this special issue, taken together, highlight the following: (1) there is diversification in the origins of water quality responses to extreme climate events based on the intensity, duration, and magnitude of the event mediated by previous historical conditions; (2) interactions between climate variability and watershed disturbances (e.g., channelization of river networks, land use change, and deforestation) amplify water quality ‘pulses,’ which can manifest as large changes in chemical concentrations and fluxes over relatively short time periods. In the context of the evolution of water quality responses, results highlight: (3) there are high intensity and long-term climate events, which can generate unique sequences in water quality, which have differential impacts on persistence of water quality problems and ecosystem recovery rates; and (4) ‘chemical cocktails’ or novel mixtures of elements and compounds are transported and transformed during extreme climate events. The main findings regarding resilience to extreme climate events are that: (5) river restoration strategies for reducing pollution from extreme events can be improved by preserving and restoring floodplains, wetlands, and oxbow ponds, which enhance hydrologic and biogeochemical retention, and lengthen the distribution of hydrologic residence times; and (6) the biogeochemical capacity for stream and river ecosystems to retain and transform pollution from landscapes can become “saturated” during floods unless watershed pollution sources are reduced. Finally, the unpredictable occurrence of extreme climate events argues for wider deployment of high-frequency, in situ sensors for monitoring, managing, and modeling diverse water quality responses. These sensors can be used to develop robust proxies for chemical cocktails, detect water quality violations following extreme climate events, and effectively trace the trajectory of water quality recovery in response to managing ecosystem resilience.     

Climate-Based Models for Pulsed Resources Improve Predictability of Consumer Population Dynamics: Outbreaks of House Mice in Forest Ecosystems

Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer–resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year’s advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer–resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.     

Long-term changes in forest response to extreme atmospheric dryness

Atmospheric dryness, as indicated by vapor pressure deficit (VPD), has a strong influence on forest greenhouse gas exchange with the atmosphere. In this study, we used long-term (10–30 years) net ecosystem productivity (NEP) measurements from 60 forest sites across the world (1003 site-years) to quantify long-term changes in forest NEP resistance and NEP recovery in response to extreme atmospheric dryness. We tested two hypotheses: first, across sites differences in NEP resistance and NEP recovery of forests will depend on both the biophysical characteristics (i.e., leaf area index [LAI] and forest type) of the forest as well as on the local meteorological conditions of the site (i.e., mean VPD of the site), and second, forests experiencing an increasing trend in frequency and intensity of extreme dryness will show an increasing trend in NEP resistance and NEP recovery over time due to emergence of long-term ecological stress memory. We used a data-driven statistical learning approach to quantify NEP resistance and NEP recovery over multiple years. Our results showed that forest types, LAI, and median local VPD conditions explained over 50% of variance in both NEP resistance and NEP recovery, with drier sites showing higher NEP resistance and NEP recovery compared to sites with less atmospheric dryness. The impact of extreme atmospheric dryness events on NEP lasted for up to 3 days following most severe extreme events in most forests, indicated by an NEP recovery of less than 100%. We rejected our second hypothesis as we found no consistent relationship between trends of extreme VPD with trends in NEP resistance and NEP recovery across different forest sites, thus an increase in atmospheric dryness as it is predicted might not increase the resistance or recovery of forests in terms of NEP.     

Intermediate Coupling between Aboveground and Belowground Biomass Maximises the Persistence of Grasslands

Aboveground and belowground biomass compartments of vegetation fulfil different functions and they are coupled by complex interactions. These compartments exchange water, carbon and nutrients and the belowground biomass compartment has the capacity to buffer vegetation dynamics when aboveground biomass is removed by disturbances such as herbivory or fire. However, despite their importance, root-shoot interactions are often ignored in more heuristic vegetation models. Here, we present a simple two-compartment grassland model that couples aboveground and belowground biomass. In this model, the growth of belowground biomass is influenced by aboveground biomass and the growth of aboveground biomass is influenced by belowground biomass. We used the model to explore how the dynamics of a grassland ecosystem are influenced by fire and grazing. We show that the grassland system is most persistent at intermediate levels of aboveground-belowground coupling. In this situation, the system can sustain more extreme fire or grazing regimes than in the case of strong coupling. In contrast, the productivity of the system is maximised at high levels of coupling. Our analysis suggests that the yield of a grassland ecosystem is maximised when coupling is strong, however, the intensity of disturbance that can be sustained increases dramatically when coupling is intermediate. Hence, the model predicts that intermediate coupling should be selected for as it maximises the chances of persistence in disturbance driven ecosystems.     

Carrot or Stick? Modelling How Landowner Behavioural Responses Can Cause Incentive-Based Forest Governance to Backfire

Mitigating the negative impacts of declining worldwide forest cover remains a significant socio-ecological challenge, due to the dominant role of human decision-making. Here we use a Markov chain model of land-use dynamics to examine the impact of governance on forest cover in a region. Each land parcel can be either forested or barren (deforested), and landowners decide whether to deforest their parcel according to perceived value (utility). We focus on three governance strategies: yearly incentive for conservation, one-time penalty for deforestation and one-time incentive for reforestation. The incentive and penalty are incorporated into the expected utility of forested land, which decreases the net gain of deforestation. By analyzing the equilibrium and stability of the landscape dynamics, we observe four possible outcomes: a stationary-forested landscape, a stationary-deforested landscape, an unstable landscape fluctuating near the equilibrium, and a cyclic-forested landscape induced by synchronized deforestation. We find that the two incentive-based strategies often result in highly fluctuating forest cover over decadal time scales or longer, and in a few cases, reforestation incentives actually decrease the average forest cover. In contrast, a penalty for deforestation results in the stable persistence of forest cover (generally >30%). The idea that larger conservation incentives will always yield higher and more stable forest cover is not supported in our findings. The decision to deforest is influenced by more than a simple, “rational” cost-benefit analysis: social learning and myopic, stochastic decision-making also have important effects. We conclude that design of incentive programs may need to account for potential counter-productive long-term effects due to behavioural feedbacks.     

Hybrid stochastic and deterministic simulations of calcium blips

Intracellular calcium release is a prime example for the role of stochastic effects in cellular systems. Recent models consist of deterministic reaction-diffusion equations coupled to stochastic transitions of calcium channels. The resulting dynamics is of multiple time and spatial scales, which complicates far-reaching computer simulations. In this article, we introduce a novel hybrid scheme that is especially tailored to accurately trace events with essential stochastic variations, while deterministic concentration variables are efficiently and accurately traced at the same time. We use finite elements to efficiently resolve the extreme spatial gradients of concentration variables close to a channel. We describe the algorithmic approach and we demonstrate its efficiency compared to conventional methods. Our single-channel model matches experimental data and results in intriguing dynamics if calcium is used as charge carrier. Random openings of the channel accumulate in bursts of calcium blips that may be central for the understanding of cellular calcium dynamics.     

基于VAR模型的森林植被碳储量影响因素分析——以陕西省为例

森林作为陆地生态系统最大的碳库,对现在及未来的气候变化、碳平衡都具有重要影响。而对影响森林植被碳库的自然和非自然因素进行研究更是对增强森林的碳汇作用,继而改善生态环境状况意义重大。现有的森林动态模型虽然可以很好的模拟碳储量各影响因子之间的联系,但研究往往集中于小尺度从单一影响因素着手,且由于确定模型输入变量和参数的复杂性,使得这些模型在区域甚至更大尺度上的应用存在着一些困难。因此,运用VAR模型,以陕西省为例,构建森林植被碳储量与病虫害发生面积、木材产量、森林火灾面积、森林抚育面积、人工更新造林面积、降水和温度之间的动态关系,来验证该模型在省级尺度条件下的区域森林植被碳储量影响因素分析中的可行性。结果表明:各变量在5%的显著性水平下呈一阶单整序列并具有长期稳定的均衡关系,VAR模型也通过了平稳性检验满足运行的前提条件。通过脉冲响应和方差分解分析可知,森林病虫害、木材产量对陕西省森林植被碳储量呈现出很明显的负作用,并且贡献度很高,分别为5.61%和4.52%;森林抚育、人工更新造林对碳储量的影响存在一定的滞后期;火灾、温度和降水的冲击给碳储量带来的影响均不明显。模型较好的模拟了各影响因素对陕西省碳储量的影响,且具有一定的现实意义,因此,该模型可应用于省级尺度条件下的区域森林植被碳储量影响因素分析。     

Lowland tapirs facilitate seed dispersal in degraded Amazonian forests

The forests of southeastern Amazonia are highly threatened by disturbances such as fragmentation, understory fires, and extreme climatic events. Large‐bodied frugivores such as the lowland tapir (Tapirus terrestris) have the potential to offset this process, supporting natural forest regeneration by dispersing a variety of seeds over long distances to disturbed forests. However, we know little about their effectiveness as seed dispersers in degraded forest landscapes. Here, we investigate the seed dispersal function of lowland tapirs in Amazonian forests subject to a range of human (fire and fragmentation) and natural (extreme droughts and windstorms) disturbances, using a combination of field observations, camera traps, and light detection and ranging (LiDAR) data. Tapirs travel and defecate more often in degraded forests, dispersing much more seeds in these areas [9,822 seeds per ha/year (CI_95% = 9,106; 11,838)] than in undisturbed forests [2,950 seeds per ha/year (CI_95% = 2,961; 3,771)]. By effectively dispersing seeds across disturbed forests, tapirs may contribute to natural forest regeneration—the cheapest and usually the most feasible way to achieve large‐scale restoration of tropical forests. Through the dispersal of large‐seeded species that eventually become large trees, such frugivores also contribute indirectly to maintaining forest carbon stocks. These functions may be critical in helping tropical countries to achieve their goals to maintain and restore biodiversity and its ecosystem services. Ultimately, preserving these animals along with their habitats may help in the process of natural recovery of degraded forests throughout the tropics. Abstract in Portuguese is available with online material.     

A spatially structured metapopulation model with patch dynamics

Metapopulation models that incorporate both spatial and temporal structure are studied in this paper. The existence and stability of equilibria are provided, and an extinction threshold condition is derived which depends on patch dynamics (patch destruction and creation) and metapopulation dynamics (patch colonization and extinction). These results refine threshold conditions given by previous metapopulation models. By comparing landscapes with different spatial heterogeneities with respect to weighted long-term patch occupancies, we conclude that the pattern of a landscape is of overwhelming importance in determining metapopulation persistence and patch occupancy. We show that the same conclusion holds when a rescue effect is considered. We also derive a stochastic differential equations (SDE) model of the It? type based on our deterministic model. Our simulations reveal good agreement between the deterministic model and the SDE model.     

Transmission Dynamics of an SIS Model with Age Structure on Heterogeneous Networks

Infection age is often an important factor in epidemic dynamics. In order to realistically analyze the spreading mechanism and dynamical behavior of epidemic diseases, in this paper, a generalized disease transmission model of SIS type with age-dependent infection and birth and death on a heterogeneous network is discussed. The model allows the infection and recovery rates to vary and depend on the age of infection, the time since an individual becomes infected. We address uniform persistence and find that the model has the sharp threshold property, that is, for the basic reproduction number less than one, the disease-free equilibrium is globally asymptotically stable, while for the basic reproduction number is above one, a Lyapunov functional is used to show that the endemic equilibrium is globally stable. Finally, some numerical simulations are carried out to illustrate and complement the main results. The disease dynamics rely not only on the network structure, but also on an age-dependent factor (for some key functions concerned in the model).     

Flow regime alteration effects on the organic C dynamics in semiarid stream ecosystems

There is evidence of an ongoing alteration of the flow regime owing to climate change forcing, which has resulted in substantial increases in the frequency and magnitude of extreme events such as floods and droughts. Such changes in the flow regime may have major implications in freshwater ecosystems and, in particular, in the organic carbon dynamics in semiarid stream ecosystems. Much is known about the role of extreme flow events on structuring stream ecosystems, but few studies explored the effects of extreme flow events magnitude, timing, and sequence on stream ecosystems. To assess the effect of extreme events on stream organic C dynamics, a simple and flexible modeling approach was applied to simulate the organic carbon dynamics in a simplified river reach. The river reach model was initially calibrated and tested using long-term data for stream water velocity and amount of organic carbon in sediment. After that, multiple scenarios differing in the extreme flow events (floods and droughts) sequence and magnitude were used to simulate the effects of possible flow regime changes on the stream organic carbon dynamics. Initial expectations were that: (i) an increase in the magnitude or frequency of extreme flow events would reduce the amount of organic carbon respired within the simulated river reach, and (ii) relationship between the timings of the extreme flow events and of the litterfall input would influence considerably the effects of the extreme flow events. Results pointed out that: (i) the amount of processed carbon respect the amount entering the ecosystem was affected by extreme events such floods and droughts, but the relevance of those events differed along the year, with a maximal effect during the litterfall period; (ii) extreme event timing rather than the magnitude was more relevant to the stream organic carbon dynamics; and (iii) the amount of respired carbon in the ecosystem could be amplified or reduced depending on event sequence. Increasing awareness of the role of inland waters in the global carbon cycle and the shaping role of hydrology on the stream organic carbon dynamics stress the need to better quantify carbon fluxes and the hydrological controls on these fluxes.     

森林生态系统碳水关系及其影响因子研究进展

森林生态系统的碳水关系是陆地生态系统碳循环和水循环相互耦合的作用过程,对研究森林碳汇、森林生态水文过程和全球变化响应有重要意义.在全球变化背景下,森林生态系统碳水关系已成为生态水文学领域中的一个热点科学问题.本文在总结国际上森林碳汇研究的基础上,概述了森林碳水关系的过程机制,包括森林水分利用效率、不同尺度上的碳水关系、尺度推绎和碳水关系的模拟研究方面的进展;总结了影响森林碳水关系的因子和研究进展,包括水分条件、CO₂浓度升高、增温、氮沉降、臭氧浓度变化、辐射因子和海拔梯度因子对森林碳水关系的影响;最后对已有研究存在的问题进行了初步分析,并对未来研究内容和方向进行了展望.