Understory vegetation plays a crucial role in carbon and nutrient cycling in forest ecosystems; however, it is not clear how understory species affect tree litter decomposition and nutrient dynamics. In this study, we examined the impacts of understory litter on the decomposition and nutrient release of tree litter both in a pine (Pinus sylvestris var. mongolica) and a poplar (Populus × xiaozhuanica) plantation in Northeast China. Leaf litter of tree species, and senesced aboveground materials from two dominant understory species, Artemisia scoparia and Setaria viridis in the pine stand and Elymus villifer and A. sieversiana in the poplar stand, were collected. Mass loss and N and P fluxes of single-species litter and three-species mixtures in each of the two forests were quantified. Data from single-species litterbags were used to generate predicted mass loss and N and P fluxes for the mixed-species litterbags. In the mixture from the pine stand, the observed mass loss and N release did not differ from the predicted value, whereas the observed P release was greater than the predicted value. However, the presence of understory litter decelerated the mass loss and did not affect N and P releases from the pine litter. In the poplar stand, litter mixture presented a positive non-additive effect on litter mass loss and P release, but an addition effect on N release. The presence of understory species accelerated only N release of poplar litter. Moreover, the responses of mass loss and N and P releases of understory litter in the mixtures varied with species in both pine and poplar plantations. Our results suggest that the effects of understory species on tree litter decomposition vary with tree species, and also highlight the importance of understory species in litter decomposition and nutrient cycles in forest ecosystems.
Orchard understory represents an important component of the orchards, performing numerous functions related to soil quality, water relations and microclimate, but little attention has been paid on its effect on soil C sequestration. In the face of global climate change, fruit producers also require techniques that increase carbon (C) sequestration in a cost-effective manner. Here we present a case study to compare the effects of understory management (sod culture vs. clean tillage) on soil C sequestration in four subtropical orchards. The results of a 10-year study indicated that the maintenance of sod significantly enhanced the soil C stock in the top 1 m of orchard soils. Relative to clean tillage, sod culture increased annual soil C sequestration by 2.85 t C ha-1, suggesting that understory management based on sod culture offers promising potential for soil carbon sequestration. Considering that China has the largest area of orchards in the world and that few of these orchards currently have sod understories, the establishment and maintenance of sod in orchards can help China increase C sequestration and greatly contribute to achieving CO2 reduction targets at a regional scale and potentially at a national scale.
Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.
Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (σo) properties of PALSAR data. The relationship between the PALSAR σo HV and HH/HV with field measured biomass was strong with R2 = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R2 = 0.61 with RMSE = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level.
A two year (2010–2012) study was conducted to assess the effects of different agronomic management practices on the emissions of CO2 from a field of non-irrigated wheat planted on China's Loess Plateau. Management practices included four tillage methods i.e. T1: (chisel plow tillage), T2: (zero-tillage), T3: (rotary tillage) and T4: (mold board plow tillage), 2 mulch levels i.e., M0 (no corn residue mulch) and M1 (application of corn residue mulch) and 5 levels of N fertilizer (0, 80, 160, 240, 320 kg N/ha). A factorial experiment having a strip split-split arrangement, with tillage methods in the main plots, mulch levels in the sub plots and N-fertilizer levels in the sub-sub plots with three replicates, was used for this study. The CO2 data were recorded three times per week using a portable GXH-3010E1 gas analyzer. The highest CO2 emissions were recorded following rotary tillage, compared to the lowest emissions from the zero tillage planting method. The lowest emissions were recorded at the 160 kg N/ha, fertilizer level. Higher CO2 emissions were recorded during the cropping year 2010–11 relative to the year 2011–12. During cropping year 2010–11, applications of corn residue mulch significantly increased CO2 emissions in comparison to the non-mulched treatments, and during the year 2011–12, equal emissions were recorded for both types of mulch treatments. Higher CO2 emissions were recorded immediately after the tillage operations. Different environmental factors, i.e., rain, air temperatures, soil temperatures and soil moistures, had significant effects on the CO2 emissions. We conclude that conservation tillage practices, i.e., zero tillage, the use of corn residue mulch and optimum N fertilizer use, can reduce CO2 emissions, give better yields and provide environmentally friendly options.
Seasonality drives ecological processes through networks of forcings, and the resultant complexity requires creative approaches for modeling to be successful. Recently ecologists and climatologists have developed sophisticated methods for fully describing seasons. However, to date the relationships among the variables produced by these methods have not been analyzed as networks, but rather with simple univariate statistics. In this manuscript we used structural equation modeling (SEM) to analyze a proposed causal network describing seasonality of rainfall for a site in south-central Florida. We also described how this network was influenced by the El Niño-Southern Oscillation (ENSO), and how the network in turn affected the site’s wildfire regime. Our models indicated that wet and dry seasons starting later in the year (or ending earlier) were shorter and had less rainfall. El Niño conditions increased dry season rainfall, and via this effect decreased the consistency of that season’s drying trend. El Niño conditions also negatively influenced how consistent the moistening trend was during the wet season, but in this case the effect was direct and did not route through rainfall. In modeling wildfires, our models showed that area burned was indirectly influenced by ENSO via its effect on dry season rainfall. Area burned was also indirectly reduced when the wet season had consistent rainfall, as such wet seasons allowed fewer wildfires in subsequent fire seasons. Overall area burned at the study site was estimated with high accuracy (R2 score = 0.63). In summary, we found that by using SEMs, we were able to clearly describe causal patterns involving seasonal climate, ENSO and wildfire. We propose that similar approaches could be effectively applied to other sites where seasonality exerts strong and complex forcings on ecological processes.
Carbon emissions resulting from deforestation and forest degradation are poorly known at local, national and global scales. In part, this lack of knowledge results from uncertain above-ground biomass estimates. It is generally assumed that using more sophisticated methods of estimating above-ground biomass, which make use of remote sensing, will improve accuracy. We examine this assumption by calculating, and then comparing, above-ground biomass area density (AGBD) estimates from studies with differing levels of methodological sophistication. We consider estimates based on information from nine different studies at the scale of Africa, Mozambique and a 1160 km2 study area within Mozambique. The true AGBD is not known for these scales and so accuracy cannot be determined. Instead we consider the overall precision of estimates by grouping different studies. Since an the accuracy of an estimate cannot exceed its precision, this approach provides an upper limit on the overall accuracy of the group. This reveals poor precision at all scales, even between studies that are based on conceptually similar approaches. Mean AGBD estimates for Africa vary from 19.9 to 44.3 Mg ha−1, for Mozambique from 12.7 to 68.3 Mg ha−1, and for the 1160 km2 study area estimates range from 35.6 to 102.4 Mg ha−1. The original uncertainty estimates for each study, when available, are generally small in comparison with the differences between mean biomass estimates of different studies. We find that increasing methodological sophistication does not appear to result in improved precision of AGBD estimates, and moreover, inadequate estimates of uncertainty obscure any improvements in accuracy. Therefore, despite the clear advantages of remote sensing, there is a need to improve remotely sensed AGBD estimates if they are to provide accurate information on above-ground biomass. In particular, more robust and comprehensive uncertainty estimates are needed.
Among terrestrial environments, forests are not only the largest long-term sink of atmospheric carbon (C), but are also susceptible to global change themselves, with potential consequences including alterations of C cycles and potential C emission. To inform global change risk assessment of forest C across large spatial/temporal scales, this study constructed and evaluated a basic risk framework which combined the magnitude of C stocks and their associated probability of stock change in the context of global change across the US. For the purposes of this analysis, forest C was divided into five pools, two live (aboveground and belowground biomass) and three dead (dead wood, soil organic matter, and forest floor) with a risk framework parameterized using the US's national greenhouse gas inventory and associated forest inventory data across current and projected future Köppen-Geiger climate zones (A1F1 scenario). Results suggest that an initial forest C risk matrix may be constructed to focus attention on short- and long-term risks to forest C stocks (as opposed to implementation in decision making) using inventory-based estimates of total stocks and associated estimates of variability (i.e., coefficient of variation) among climate zones. The empirical parameterization of such a risk matrix highlighted numerous knowledge gaps: 1) robust measures of the likelihood of forest C stock change under climate change scenarios, 2) projections of forest C stocks given unforeseen socioeconomic conditions (i.e., land-use change), and 3) appropriate social responses to global change events for which there is no contemporary climate/disturbance analog (e.g., severe droughts in the Lake States). Coupling these current technical/social limits of developing a risk matrix to the biological processes of forest ecosystems (i.e., disturbance events and interaction among diverse forest C pools, potential positive feedbacks, and forest resiliency/recovery) suggests an operational forest C risk matrix remains elusive.
Sub-surface irrigation (SUI) is a new water-saving irrigation technology. To explore the influence of SUI on soil conditions in a cherry orchard and its water-saving efficiency, experiments were conducted from 2009 to 2010 using both SUI and flood irrigation (FLI) and different SUI quotas in hilly semi-arid area of northern China. The results demonstrated the following: 1) The bulk density of the soil under SUI was 6.8% lower than that of soil under FLI (P<0.01). The total soil porosity, capillary porosity and non-capillary porosity of soils using SUI were 11.7% (P<0.01), 8.7% (P<0.01) and 43.8% (P<0.01) higher than for soils using FLI. 2) The average soil temperatures at 0, 5, 10, 15 and 20 cm of soil depth using SUI were 1.7, 1.1, 0.7, 0.4 and 0.3°C higher than those for FLI, specifically, the differences between the surface soil layers were more significant. 3) Compared with FLI, the average water-saving efficiency of SUI was 55.6%, and SUI increased the irrigation productivity by 7.9-12.3 kg m-3 ha-1. 4) The soil moisture of different soil layers using SUI increased with increases in the irrigation quotas, and the soil moisture contents under SUI were significantly higher in the 0-20 cm layer and in the 21-50 cm layer than those under FLI (P<0.01). 5) The average yields of cherries under SUI with irrigation quotas of 80-320 m3 ha-1 were 8.7%-34.9% higher than those in soil with no irrigation (CK2). The average yields of cherries from soils using SUI were 4.5%-12.2% higher than using FLI. It is appropriate to irrigate 2-3 times with 230 m3 ha-1 per application using SUI in a year with normal rainfall. Our findings indicated that SUI could maintain the physical properties, greatly improve irrigation water use efficiency, and significantly increase fruit yields in hilly semi-arid areas of northern China.
The northeastern United States is a predominately-forested region that, like most of the eastern U.S., has undergone a 400-year history of intense logging, land clearance for agriculture, and natural reforestation. This setting affords the opportunity to address a major ecological question: How similar are today's forests to those existing prior to European colonization? Working throughout a nine-state region spanning Maine to Pennsylvania, we assembled a comprehensive database of archival land-survey records describing the forests at the time of European colonization. We compared these records to modern forest inventory data and described: (1) the magnitude and attributes of forest compositional change, (2) the geography of change, and (3) the relationships between change and environmental factors and historical land use. We found that with few exceptions, notably the American chestnut, the same taxa that made up the pre-colonial forest still comprise the forest today, despite ample opportunities for species invasion and loss. Nonetheless, there have been dramatic shifts in the relative abundance of forest taxa. The magnitude of change is spatially clustered at local scales (<125 km) but exhibits little evidence of regional-scale gradients. Compositional change is most strongly associated with the historical extent of agricultural clearing. Throughout the region, there has been a broad ecological shift away from late successional taxa, such as beech and hemlock, in favor of early- and mid-successional taxa, such as red maple and poplar. Additionally, the modern forest composition is more homogeneous and less coupled to local climatic controls.
Rainfall events can be characterized as “pulses”, which are discrete and variable episodes that can significantly influence the structure and function of desert ecosystems, including shifts in aboveground net primary productivity (ANPP). To determine the threshold and hierarchical response of rainfall event size on the Normalized Difference Vegetation Index (NDVI, a proxy for ANPP) and the difference across a desert area in northwestern China with two habitats – dune and desert – we selected 17 independent summer rainfall events from 2005 to 2012, and obtained a corresponding NDVI dataset extracted from MODIS images. Based on the threshold-delay model and statistical analysis, the results showed that the response of NDVI to rainfall pulses began at about a 5 mm event size. Furthermore, when the rainfall event size was more than 30 mm, NDVI rapidly increased 3- to 6-fold compared with the response to events of less than 30 mm, suggesting that 30 mm was the threshold for a large NDVI response. These results revealed the importance of the 5 mm and 30 mm rainfall events for plant survival and growth in desert regions. There was an 8- to 16-day lag time between the rainfall event and the NDVI response, and the response duration varied with rainfall event size, reaching a maximum of 32 days. Due to differences in soil physical and mineralogical properties, and to biodiversity structure and the root systems' abilities to exploit moisture, dune and desert areas differed in precipitation responses: dune habitats were characterized by a single, late summer productivity peak; in contrast, deserts showed a multi-peak pattern throughout the growing season.
China has been experiencing rapid urbanization in parallel with its economic boom over the past three decades. To date, the organic carbon storage in China's urban areas has not been quantified. Here, using data compiled from literature review and statistical yearbooks, we estimated that total carbon storage in China's urban areas was 577±60 Tg C (1 Tg = 1012 g) in 2006. Soil was the largest contributor to total carbon storage (56%), followed by buildings (36%), and vegetation (7%), while carbon storage in humans was relatively small (1%). The carbon density in China's urban areas was 17.1±1.8 kg C m−2, about two times the national average of all lands. The most sensitive variable in estimating urban carbon storage was urban area. Examining urban carbon storages over a wide range of spatial extents in China and in the United States, we found a strong linear relationship between total urban carbon storage and total urban area, with a specific urban carbon storage of 16 Tg C for every 1,000 km2 urban area. This value might be useful for estimating urban carbon storage at regional to global scales. Our results also showed that the fraction of carbon storage in urban green spaces was still much lower in China relative to western countries, suggesting a great potential to mitigate climate change through urban greening and green spaces management in China.
The northeastern forest region of China is an important component of total temperate and boreal forests in the northern hemisphere. But how carbon (C) pool size and distribution varies among tree, understory, forest floor and soil components, and across stand ages remains unclear. To address this knowledge gap, we selected three major temperate and two major boreal forest types in northeastern (NE) China. Within both forest zones, we focused on four stand age classes (young, mid-aged, mature and over-mature). Results showed that total C storage was greater in temperate than in boreal forests, and greater in older than in younger stands. Tree biomass C was the main C component, and its contribution to the total forest C storage increased with increasing stand age. It ranged from 27.7% in young to 62.8% in over-mature stands in boreal forests and from 26.5% in young to 72.8% in over-mature stands in temperate forests. Results from both forest zones thus confirm the large biomass C storage capacity of old-growth forests. Tree biomass C was influenced by forest zone, stand age, and forest type. Soil C contribution to total forest C storage ranged from 62.5% in young to 30.1% in over-mature stands in boreal and from 70.1% in young to 26.0% in over-mature in temperate forests. Thus soil C storage is a major C pool in forests of NE China. On the other hand, understory and forest floor C jointly contained less than 13% and <5%, in boreal and temperate forests respectively, and thus play a minor role in total forest C storage in NE China.
Plant biomass allocation between below- and above-ground parts can actively adapt to the ambient growth conditions and is a key parameter for estimating terrestrial ecosystem carbon (C) stocks. To investigate how climatic variations affect patterns of plant biomass allocation, we sampled 548 plants belonging to four dominant genera (Stipa spp., Cleistogenes spp., Agropyron spp., and Leymus spp.) along a large-scale (2500 km) climatic gradient across the temperate grasslands from west to east in northern China. Our results showed that Leymus spp. had the lowest root/shoot ratios among the each genus. Root/shoot ratios of each genera were positively correlated with mean annual temperature (MAT), and negatively correlated with mean annual precipitation (MAP) across the transect. Temperature contributed more to the variation of root/shoot ratios than precipitation for Cleistogenes spp. (C4 plants), whereas precipitation exerted a stronger influence than temperature on their variations for the other three genera (C3 plants). From east to west, investment of C into the belowground parts increased as precipitation decreased while temperature increased. Such changes in biomass allocation patterns in response to climatic factors may alter the competition regimes among co-existing plants, resulting in changes in community composition, structure and ecosystem functions. Our results suggested that future climate change would have great impact on C allocation and storage, as well as C turnover in the grassland ecosystems in northern China.
Through a modeling approach, we investigated weather factors that affect the summer incidence of Tomato spotted wilt virus (TSWV), a virus vectored exclusively by thrips, in cultivated tobacco. Aspects of thrips and plant biology that affect disease spread were treated as functions of weather, leading to a model of disease incidence informed by thrips and plant biology, and dependent on weather input variables. We found that disease incidence during the summer was influenced by weather affecting thrips activity during the preceding year, especially during a time when thrips transmit TSWV to and from the plant hosts that constitute the virus’ natural reservoir. We identified an interaction between spring precipitation and earlier weather affecting thrips, relating this to virus abundance and transmission intensity as interacting factors affecting disease incidence. Throughout, weather is the basic driver of epidemiology in the system, and our findings allowed us to detect associations between atypically high- or low-incidence years and the local climatic deviations from normal weather patterns, brought about by El Niño Southern Oscillation transitions.
Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.
Montane forests of western China provide an opportunity to establish baseline studies for climate change. The region is being impacted by climate change, air pollution, and significant human impacts from tourism. We analyzed forest stand structure and climate-growth relationships from Jiuzhaigou National Nature Reserve in northwestern Sichuan province, along the eastern edge of the Tibetan plateau. We conducted a survey to characterize forest stand diversity and structure in plots occurring between 2050 and 3350 m in elevation. We also evaluated seedling and sapling recruitment and tree-ring data from four conifer species to assess: 1) whether the forest appears in transition toward increased hardwood composition; 2) if conifers appear stressed by recent climate change relative to hardwoods; and 3) how growth of four dominant species responds to recent climate. Our study is complicated by clear evidence of 20th century timber extraction. Focusing on regions lacking evidence of logging, we found a diverse suite of conifers (Pinus, Abies, Juniperus, Picea, and Larix) strongly dominate the forest overstory. We found population size structures for most conifer tree species to be consistent with self-replacement and not providing evidence of shifting composition toward hardwoods. Climate-growth analyses indicate increased growth with cool temperatures in summer and fall. Warmer temperatures during the growing season could negatively impact conifer growth, indicating possible seasonal climate water deficit as a constraint on growth. In contrast, however, we found little relationship to seasonal precipitation. Projected warming does not yet have a discernible signal on trends in tree growth rates, but slower growth with warmer growing season climates suggests reduced potential future forest growth.
The revegetation of abandoned farmland significantly influences soil organic C (SOC) and total N (TN). However, the dynamics of both soil OC and N storage following the abandonment of farmland are not well understood. To learn more about soil C and N storages dynamics 30 years after the conversion of farmland to grassland, we measured SOC and TN content in paired grassland and farmland sites in the Zhifanggou watershed on the Loess Plateau, China. The grassland sites were established on farmland abandoned for 1, 7, 13, 20, and 30 years. Top soil OC and TN were higher in older grassland, especially in the 0–5 cm soil depths; deeper soil OC and TN was lower in younger grasslands (<20 yr), and higher in older grasslands (30 yr). Soil OC and N storage (0–100 cm) was significantly lower in the younger grasslands (<20 yr), had increased in the older grasslands (30 yr), and at 30 years SOC had increased to pre-abandonment levels. For a thirty year period following abandonment the soil C/N value remained at 10. Our results indicate that soil C and TN were significantly and positively correlated, indicating that studies on the storage of soil OC and TN needs to focus on deeper soil and not be restricted to the uppermost (0–30 cm) soil levels.
Soil is commonly composed of particles of different sizes, and soil particle size may greatly affect the growth of plants because it affects soil physical and chemical properties. However, no study has tested the effects of soil particle heterogeneity on the growth of clonal plants. We conducted a greenhouse experiment in which individual ramets of the wetland plant Bolboschoenus planiculmis were grown in three homogeneous soil treatments with uniformly sized quartz particles (small: 0.75 mm, medium: 1.5 mm, or large: 3 mm), one homogeneous treatment with an even mixture of large and medium particles, and two heterogeneous treatments consisting of 16 or 4 patches of large and medium particles. Biomass, ramet number, rhizome length and spacer length were significantly greater in the treatment with only medium particles than in the one with only large particles. Biomass, ramet number, rhizome length and tuber number in the patchy treatments were greater in patches of medium than of large particles; this difference was more pronounced when patches were small than when they were large. Soil particle size and soil particle heterogeneity can greatly affect the growth of clonal plants. Thus, studies to test the effects of soil heterogeneity on clonal plants should distinguish the effects of nutrient heterogeneity from those of particle heterogeneity.
Forest-to-rubber plantation conversion is an important land-use change in the tropical region, for which the impacts on soil carbon stocks have hardly been studied. In montane mainland southeast Asia, monoculture rubber plantations cover 1.5 million ha and the conversion from secondary forests to rubber plantations is predicted to cause a fourfold expansion by 2050. Our study, conducted in southern Yunnan province, China, aimed to quantify the changes in soil carbon stocks following the conversion from secondary forests to rubber plantations. We sampled 11 rubber plantations ranging in age from 5 to 46 years and seven secondary forest plots using a space-for-time substitution approach. We found that forest-to-rubber plantation conversion resulted in losses of soil carbon stocks by an average of 37.4±4.7 (SE) Mg C ha−1 in the entire 1.2-m depth over a time period of 46 years, which was equal to 19.3±2.7% of the initial soil carbon stocks in the secondary forests. This decline in soil carbon stocks was much larger than differences between published aboveground carbon stocks of rubber plantations and secondary forests, which range from a loss of 18 Mg C ha−1 to an increase of 8 Mg C ha−1. In the topsoil, carbon stocks declined exponentially with years since deforestation and reached a steady state at around 20 years. Although the IPCC tier 1 method assumes that soil carbon changes from forest-to-rubber plantation conversions are zero, our findings show that they need to be included to avoid errors in estimating overall ecosystem carbon fluxes.
Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs). However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT) that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagussylvatica L., Quercusrobur L. and Pinussylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
Increasing atmospheric CO2 and nitrogen (N) deposition across the globe may affect ecosystem CO2 exchanges and ecosystem carbon cycles. Additionally, it remains unknown how increased N deposition and N addition will alter the effects of elevated CO2 on wetland ecosystem carbon fluxes.
Beginning in 2010, a paired, nested manipulative experimental design was used in a temperate wetland of northeastern China. The primary factor was elevated CO2, accomplished using Open Top Chambers, and N supplied as NH4NO3 was the secondary factor. Gross primary productivity (GPP) was higher than ecosystem respiration (ER), leading to net carbon uptake (measured by net ecosystem CO2 exchange, or NEE) in all four treatments over the growing season. However, their magnitude had interannual variations, which coincided with air temperature in the early growing season, with the soil temperature and with the vegetation cover. Elevated CO2 significantly enhanced GPP and ER but overall reduced NEE because the stimulation caused by the elevated CO2 had a greater impact on ER than on GPP. The addition of N stimulated ecosystem C fluxes in both years and ameliorated the negative impact of elevated CO2 on NEE.
In this ecosystem, future elevated CO2 may favor carbon sequestration when coupled with increasing nitrogen deposition.
Oak decline is a process induced by complex interactions of predisposing factors, inciting factors, and contributing factors operating at tree, stand, and landscape scales. It has greatly altered species composition and stand structure in affected areas. Thinning, clearcutting, and group selection are widely adopted harvest alternatives for reducing forest vulnerability to oak decline by removing susceptible species and declining trees. However, the long-term, landscape-scale effects of these different harvest alternatives are not well studied because of the limited availability of experimental data. In this study, we applied a forest landscape model in combination with field studies to evaluate the effects of the three harvest alternatives on mitigating oak decline in a Central Hardwood Forest landscape. Results showed that the potential oak decline in high risk sites decreased strongly in the next five decades irrespective of harvest alternatives. This is because oak decline is a natural process and forest succession (e.g., high tree mortality resulting from intense competition) would eventually lead to the decrease in oak decline in this area. However, forest harvesting did play a role in mitigating oak decline and the effectiveness varied among the three harvest alternatives. The group selection and clearcutting alternatives were most effective in mitigating oak decline in the short and medium terms, respectively. The long-term effects of the three harvest alternatives on mitigating oak decline became less discernible as the role of succession increased. The thinning alternative had the highest biomass retention over time, followed by the group selection and clearcutting alternatives. The group selection alternative that balanced treatment effects and retaining biomass was the most viable alternative for managing oak decline. Insights from this study may be useful in developing effective and informed forest harvesting plans for managing oak decline.
Mistletoes are aerial hemiparasitic plants which occupy patches of favorable habitat (host trees) surrounded by unfavorable habitat and may be possibly modeled as a metapopulation. A metapopulation is defined as a subdivided population that persists due to the balance between colonization and extinction in discrete habitat patches. Our aim was to evaluate the dynamics of the mistletoe Psittacanthus robustus and its host Vochysia thyrsoidea in three Brazilian savanna areas using a metapopulation approach. We also evaluated how the differences in terms of fire occurrence affected the dynamic of those populations (two areas burned during the study and one was fire protected). We monitored the populations at six-month intervals. P. robustus population structure and dynamics met the expected criteria for a metapopulation: i) the suitable habitats for the mistletoe occur in discrete patches; (ii) local populations went extinct during the study and (iii) colonization of previously non-occupied patches occurred. The ratio of occupied patches decreased in all areas with time. Local mistletoe populations went extinct due to two different causes: patch extinction in area with no fire and fire killing in the burned areas. In a burned area, the largest decrease of occupied patch ratios occurred due to a fire event that killed the parasites without, however, killing the host trees. The greatest mortality of V. thyrsoidea occurred in the area without fire. In this area, all the dead trees supported mistletoe individuals and no mortality was observed for parasite-free trees. Because P. robustus is a fire sensitive species and V. thyrsoidea is fire tolerant, P. robustus seems to increase host mortality, but its effect is lessened by periodic burning that reduces the parasite loads.