Space For Time Substitution Research Articles

Soil Organic Carbon Stock Prediction: Fate under 2050 Climate Scenarios, the Case of Eastern Ethiopia

Soil Organic carbon (SOC) is vital to the soil’s ecosystem functioning as well as improving soil fertility. Slight variation in C in the soil has significant potential to be either a source of CO2 in the atmosphere or a sink to be stored in the form of soil organic matter. However, modeling SOC spatiotemporal changes was challenging due to lack of data to represent the high spatial heterogeneity in soil properties. Less expensive techniques, digital soil mapping (DSM) combined with space-for-time substitution (SFTS), were applied to predict the present and projected SOC stock for temperature and rainfall projections under different climate scenarios represented by the four Representative Concentration Pathways (RCPs): RCP2.6, RCP4.5, RCP6, and RCP8.5). The relationship between environmental covariates (n = 16) and measured SOC stock (148 samples) was developed using a random forest model. Then, the temporal changes in SOC stock over the baseline were developed for the top 30 cm soil depth of the selected districts (Chiro Zuria, Kuni, Gemechis and Mieso) of West Hararghe Zone at 30 m resolution. The model validation using the random sample of 20% of the data showed that the model explained 44% of the variance (R2) with a root mean square error (RMSE) of 8.96, a mean error (ME) of 0.16, and a Lin’s concordance correlation coefficient (CCC) of 0.88. Temperature was the most important predictor factor influencing the spatial distribution of SOC stock. An overall net gain of SOC stock over the present C stock was expected in the study area by 2050. The gain in areas with the lower baseline SOC stock counterbalanced the loss in areas with the higher baseline stock. The changes in the SOC stock depended on land use land cover (LULC), soil type, and agro-ecological zones. By 2050, cropland is supposed to lose its SOC stock under all RCPs; therefore, appropriate decisions are crucial to compensate for the loss of C.

Evaluation of projected soil organic carbon stocks under future climate and land cover changes in South Africa using a deep learning approach

Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens current mitigation approaches and can jeopardise carbon stock assimilation. To effectively manage and protect SOC stocks, large-scale projections that accurately model both current and future SOC pools are necessary. Hence, this study modelled the effects of simulated climate and land-cover change on SOC inventories across South Africa up to the year 2050. A digital soil mapping strategy in concert with a deep neural network (DNN) was used to model current SOC stocks distribution. Subsequently, WorldClim general circulation models and a space-for-time substitution (SFTS) method were used to derive future SOC stocks under four shared socio-economic emission pathways. Results show a relatively high accuracy with RMSE of 7.44 t/h for current stocks, while future stocks ranged from 11.37 to 13.56 t/h. Depending on emission rates, results showed a reduction in SOC inventories, with overall SOC stocks declining from 5.64 Pg to between 4.97 and 5.38 Pg by 2050. Meanwhile, forests, which account for approximately 1.2 Pg of total SOC in South Africa, were found to have lost more than 1% of their total coverage by 2050. These findings provide a glimpse into the state of South Africa's current and future SOC stock inventories and the influence of climate and land-use change. These findings are valuable to among others policymakers, land use managers and climate change experts in assessing the long-term feasibility of South Africa's existing SOC management protocols and land-use planning agenda. However, to adequately protect future SOC stocks, current land-use planning frameworks need to be re-adjusted to prioritize pressing environmental concerns.

Forest stand-by-environment interaction invalidates the use of space-for-time substitution for site index modeling under climate change

Quantification and prediction of forest site productivity potential under climate changes are core issues of growth and yield modelling and crucial for the effective management of forest stands. Climatic factors typically enter these models as long-term baseline data of mean air temperature and sum of precipitation. Such models frequently are parameterized using spatially distributed data, an approach that can be considered as indirect space-for-time substitution (SFTS), which is based on the assumption that the growth response across spatial environmental gradients is equivalent to the dynamic growth response in time when site factors shift in situ due to environmental changes over time. In site index modelling this assumption has never been thoroughly tested. We applied procedures to test the validity of the SFTS approach using altitudinal transect analysis of data from long-term experimental plots with Norway spruce (Picea abies) in southwest Germany. The following procedures were applied 1. Partitioning of spatial and temporal variance components of site index and air temperature; 2. Test of the equivalence of spatial and temporal variation in models predicting site index from air temperature; 3. Bias analysis of the SFTS- and the altitudinal range-specific individual models. The results show that the response of site index to changes in growing season air temperature as estimated by the SFTS-based approach is significantly different from the observed temporal dynamics within the plots. The estimated sensitivity of site index to changes in growing season air temperature is significantly larger in the SFTS-model. Bias trends increase with increasing air temperature in all altitudinal ranges. We found significant effects of stand-by-environment interaction on site index responses to changing growing season air temperature. Possible reasons for the found differences are discussed. Furthermore, based on an independent data set from the German National Forestry Inventory (NFI), a SFTS-based climate-sensitive site index model was compared to a state-space modelling approach (SSM) which considers the dynamics of environmental changes over time. The results show that the SSM is statistically superior to the SFTS approach, corroborating the findings of the altitudinal transect analysis. Finally, future site index dynamics of Norway spruce were simulated on the basis of climate change scenarios using the SSM approach. We recommend for all climate sensitive forest growth and yield models based on spatially and temporally distributed data to properly account for within- and between-group effects to avoid erroneous model predictions under climate change.

Applying space-for-time substitution to infer the growth response to climate may lead to overestimation of tree maladaptation: Evidence from the North American White Spruce Network.

Under climate change circumstances, increasing studies have reported the temporal instability of tree growth responses to climate, which poses a major challenge to linearly extrapolating past climate and future growth dynamics using tree-ring data. Space-for-time substitution (SFTS) is a potential solution to this problem that is widely used in the dendrochronology field to project past or future temporal growth response trajectories from contemporary spatial patterns. However, the projected accuracy of the SFTS in the climate effects on tree growth remains uncertain. Here, we empirically test the SFTS method by comparing the effect of spatial and temporal climate variations on climate responses of white spruce (Picea glauca), which has a transcontinental range in North America. We first applied a response surface regression model to capture the variations in growth responses along the spatial climate gradients. The results showed that the relationships between growth and June temperature varied along spatial climate gradients in a predictable way. And their relationships varied mainly along with local temperate condition. Then, the projected correlation coefficients between growth and climate using SFTS were compared against the observed. We found that the growth response changes caused by spatial versus temporal climate variations showed opposite trends. Moreover, the projected correlation coefficients using the SFTS were significantly lower than the observed. This finding suggests that applying the SFTS to project the growth response of white spruce might lead to an overestimation of the degree of tree maladaptation in future climate scenarios. And the overestimation is likely to get weaker from Alaska and Yukon Territory in the west to Quebec in the east. Although this is only a case study of the SFTS method for projecting tree growth response, our findings suggest that direct application of the SFTS method may not be applicable to all regions and all tree species.

Deep soil water storage and drainage following conversion of deep rooted to shallow rooted vegetation

Deep soil water management is important for agroforests to combat frequent droughts. However, little is known about how deep soil water (up to 15.0 m) and its deep drainage after trees fell evolves with time (< 20 years) in deep vadose zone. Therefore, this study was aimed at evaluating the impact of orchards removal on the replenishment of deep soil water and its deep drainage in a sub-humid region on the Loess Plateau, China (LPC). We established paired experimental plots between cultivated farmlands after deforested land and mature/aged orchards. Soil water storage and deep drainage were calculated from the measured soil water contents based on deep soil sampling (down to 6–15.0 m). Then, the time evolution of soil water storage and deep drainage rates were obtained based on the space for time substitution. Results showed that the replenishing front (indicated by the increase of soil water) deepened with time after orchard removal, which progressively increased deep soil water content. The drainage rates increased suddenly right after orchard removal and attained a constant value of 22.0 ± 3.1 mm yr−1 after the conversion. With this deep drainage rate, deep soil water deficit created by prior mature orchards would require 48–69 years of annual crop cultivation. Therefore, this study helps improve the further understanding of ecohydrological process under land use and management of deep soil water storage for increasing resiliency of agroforests to climate change.

Signatures of Wetland Impact: Spatial Distribution of Forest Aboveground Biomass in Tumen River Basin

The Tumen River Basin, located in the cross-border region of China, North Korea, and Russia, constitutes an important ecological barrier in China. Forest here is mainly distributed around wetland, with the distribution of wetland having the potential to regulate regional forest carbon storage. However, the spatially explicit map of forest aboveground biomass (AGB) and potential impact of drivers, i.e., wetland distribution and climate, is still lacking. We thus use a deep neural network and multi-source remote sensing data to quantify forest AGB in the Tumen River Basin. Our results show the mean forest AGB is 103.43 Mg ha−1, with divergent spatial variation along its distance to wetland. The results of correlation analysis showed that with sufficient soil moisture supply, temperature dominant spatial variation of forest aboveground biomass. Noted that using the space for time substitution, we find when wetland decreased by less than 11.1%, the forest AGB decreased by more than 8%. Our result highlight the signatures of wetland impact on its nearby forest carbon storage, and urge the wetland protection, especially under the warming and drying future.

Landscape index for indicating water quality and application to master plan of regional lake cluster restoration

Understanding the relation between landscape pattern and water quality is essential to making a master plan for restoration of regional lake and wetland clusters, which has not yet been well resolved. Here, we studied the impacts of landscape pattern changes on water quality over lake clusters, taking the aquaculture area in the Lixia River hinterland of China as a case. Multi-temporal Landsat series of remote sensing data from 1985 to 2018 was used and space-for-time substitution (SFTS) method was applied to explore the relationship between landscape pattern and water quality. Results showed that wetland and free water surface were the dominant classes of the lake cluster in 1985 and 1990, but they began to rapidly decrease from 1995 to 2000. The enclosure aquaculture increased rapidly since 1995 and became the dominant class between 1995 and 2018. The patch density of aquaculture water (PD_A) increased from 0.09n/km2 in 1985 to 0.34n/km2 in 2018, with the largest degree of fragmentation in 2000. However, the growth rate of PD_A declined significantly after the enactment of the lake ecological protection policies. The SFTS results showed that PD_A had positive correlation with total nitrogen (TN) (r = 0.26), ammonia nitrogen (NH3-N) (r = 0.21), and Chlorophyta (r = 0.33), and the water quality degraded with increasing PD_A. Hence, PD_A could be a water quality indicator of lakes in the Lixia River hinterland. The study is expected to provide a viable method to design regional restoration plan for degraded and over-developed wetland areas.

Temporal heterogeneity has no effect on the direction of succession in abandoned croplands in a semiarid area of northwest China

AbstractSpace for time substitution has been widely used in the study of succession in abandoned croplands worldwide but it is often accompanied by time heterogeneity. However, the effect of temporal heterogeneity on succession dynamics over decades is not well understood. Here, we studied croplands with the same history that were abandoned in 1998, 1999, and 2000 in northwest China (temporal heterogeneity) and continuously monitored for vegetation characteristics for 10 years. Aboveground biomass, taxonomic, and functional diversity were compared in the three cropland groups over time. Our results showed that the direction of succession in the three cropland groups was similar, from a community with single dominant species with higher aboveground biomass to a community with multiple dominant species with lower aboveground biomass. Taxonomic and functional diversity increased rapidly in the first 5–6 years, followed by slow increase, decrease, or stabilization. In years 1–5, aboveground biomass, taxonomic, and functional diversity were affected by rainfall, time of abandonment, time since abandonment, or their interactions. However, in years 6–10, biomass was only affected by rainfall, and functional evenness was affected by rainfall and time since abandonment; there was no time of abandonment effect. We conclude that temporal heterogeneity can initially affect the succession process but has no effect on the direction of community succession in the longer term. Our findings provide evidence for using space for time substitution with temporal heterogeneity to study succession in abandoned croplands in semiarid areas.

Continental-scale tree-ring-based projection of Douglas-fir growth: Testing the limits of space-for-time substitution.

A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree-ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space-for-time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today. Here we evaluated an SFTS approach to projecting future growth of Douglas-fir (Pseudotsuga menziesii), a species that occupies an exceptionally large environmental space in North America. We fit a hierarchical mixed-effects model to capture ring-width variability in response to spatial and temporal variation in climate. We found opposing gradients for productivity and climate sensitivity with highest growth rates and weakest response to interannual climate variation in the mesic coastal part of Douglas-fir's range; narrower rings and stronger climate sensitivity occurred across the semi-arid interior. Ring-width response to spatial versus temporal temperature variation was opposite in sign, suggesting that spatial variation in productivity, caused by local adaptation and other slow processes, cannot be used to anticipate changes in productivity caused by rapid climate change. We thus substituted only climate sensitivities when projecting future tree growth. Growth declines were projected across much of Douglas-fir's distribution, with largest relative decreases in the semiarid U.S. Interior West and smallest in the mesic Pacific Northwest. We further highlight the strengths of mixed-effects modeling for reviving a conceptual cornerstone of dendroecology, Cook's 1987 aggregate growth model, and the great potential to use tree-ring networks and results as a calibration target for next-generation vegetation models.

Stability characteristics of soil organic carbon pool following development of sand-fixing forest in Mu Us sandy land, China

The study aimed to reveal the cumulative effects and stability characteristics of soil organic carbon (SOC) during forest development at the Mu Us sandy land, China. Using space for time substitution, surface soil samples were collected from semi-fixed sandy lands and restored arbor and shrub lands with the ages of 22, 32 and 53 years in the Yulin sand control region in Northern Shaanxi Province. The content of total organic carbon (TOC), oxidizable labile organic carbon, and resistant carbon and the characteristics of mineralized carbon emission and decomposition ratio were analyzed. The results showed that the increment of TOC for 22 to 53 years shrub and arbor lands from resistant carbon were 3.5-6.2 g·kg-1 and 3.2-7.7 g·kg-1, and from oxidized labile carbon were 2.8-3.4 g·kg-1 and 1.3-2.8 g·kg-1, respectively, compared with semi-fixed sand land. The ratio of soil oxidizable labile carbon in shrub land and arbor land were stable and maintained at 37.0% and 26.8%, respectively. However, the ratio decreased to 25.7% and 17.4% after incubated at a constant temperature for 60 days. The mineralization rate of shrub and arbor lands with 22-53 years was not significant at the ending of soil incubation. Carbon losses from oxidized liable carbon were 76.9%-98.7%, and only 1.3%-23.5% from resistant carbon in all sand-fixing forest plots. Compared with the maximum carbon emission rate, the soil cumulative carbon release exhibited a higher correlation with soil enzyme activities of β-glucosidase and dehydrogenase, but the enzyme activities did not change from 32-53 years. In conclusion, SOC pool showed stable characteristics of lower emission and higher sequestration with the increases of sand-fixing forest stand age. The carbon fixation effect of arbor sand-fixing forest was better than that of shrub sand-fixing forest.

Using natural laboratories to study evolution to global warming: contrasting altitudinal, latitudinal, and urbanization gradients.

Demonstrating the likelihood of evolution in response to global warming is important, yet challenging. We discuss how three spatial thermal gradients (latitudinal, altitudinal, and urbanization) can be used as natural laboratories to inform about the gradual thermal evolution of populations by applying a space-for-time substitution (SFTS) approach. We compare thermal variables and confounding non-thermal abiotic variables, methodological approaches and evolutionary aspects associated with each type of gradient. On the basis of an overview of recent insect studies, we show that a key assumption of SFTS, local thermal adaptation along these gradients, is often but not always met, requiring explicit validation. To increase realism when applying SFTS, we highlight the importance of integrating daily temperature fluctuations, multiple stressors and multiple interacting species. Finally, comparative studies, especially across gradient types, are important to provide more robust inferences of evolution under gradual global warming. Integrating these research directions will further strengthen the still underused, yet powerful SFTS approach to infer gradual evolution under global warming.

Changes in Soil Nitrogen, Phosphorus, and Carbon Stocks in a Forest Ecosystem at Different Successional Stages in Leyte, Philippines

Forests play a vital role in the global carbon cycle since these are sources and sinks of carbon. This study was conducted to evaluate the changes in soil carbon stocks and some essential nutrients of different succession stages in two different soil types in Leyte Province. A space-fortime substitution approach was done in this study. Measurements of the physical, chemical, and biological properties of the soils were done following standard methods. The sites were characterized as Ultisol (Site 1 – Baybay, Leyte) and Andisol (Site 2 – Ormoc City). Results showed no significant differences among all the soil properties in the different forest succession stages in each site. However, variation in soil properties between sites was clearly observed. Site 2 had higher soil porosity and water holding capacity, but had lower bulk density than Site 1. Soils in Site 2 were more acidic, had higher total organic carbon, total N, and CEC but had pot, lower exchangeable bases and CEC than in Site 1. Both sites had low eff available P. The C:N ratios in all forest successions were significantly lower in Site 1 than in Site 2. This conforms to the results of substrate-induced respiration, where Site 1 was more active in CO evolution than Site 2. 2 Moreover, the soils in Site 2 significantly contained more SOC stocks (108- -1 -1 180 Mg C ha ) than in Site 1 (49-76 Mg C ha ). However, SOC stocks did not vary significantly in both sites. This result implies that the determination of soil physico-chemical properties is important in evaluating the changes of C:N ratios as well as of SOC stocks. In this study, Andisols had higher potential in storing organic C than Ultisols.

High‐speed colonization of bare ground—Permanent plot studies on primary succession of plants in recently deglaciated glacier forelands

AbstractGlacier forelands are highly suitable environments to study vegetation dynamics. Due to time constraints, the method of ‘space for time substitution’ is commonly employed, using spatially different sites to reconstruct a temporal sequence. However, migration patterns, growth performance, shifts in frequency or abundance of species, changes in biological traits, setbacks, etc. can only be detected by long‐term monitoring on permanent plots. In 2005, a set of permanent plots were established immediately in front of two glacier termini in the European Alps (Goldbergkees, Austria; Lenksteinferner, Italy), which were revisited every second year thereafter. Changes in ground cover and individual numbers of vascular plants as well as structural features such as life‐form composition and dispersal biology types are recorded. The six visits between 2005 and 2015 allow for a detailed appraisal of early vegetation development in glacier forelands, which is surprisingly swift and primarily progressive, but locally interrupted by temporary setbacks due to disturbances. This study contributes to a better understanding of high alpine vegetation dynamics in paraglacial landscapes, that is, transitional landscapes characterized by particular rate and direction of change.

Responses of competitive understorey species to spatial environmental gradients inaccurately explain temporal changes

Understorey plant communities play a key role in the functioning of forest ecosystems. Under favourable environmental conditions, competitive understorey species may develop high abundances and influence important ecosystem processes such as tree regeneration. Thus, understanding and predicting the response of competitive understorey species as a function of changing environmental conditions is important for forest managers. In the absence of sufficient temporal data to quantify actual vegetation changes, space-for-time (SFT) substitution is often used, i.e. studies that use environmental gradients across space to infer vegetation responses to environmental change over time. Here we assess the validity of such SFT approaches and analysed 36 resurvey studies from ancient forests with low levels of recent disturbances across temperate Europe to assess how six competitive understorey plant species respond to gradients of overstorey cover, soil conditions, atmospheric N deposition and climatic conditions over space and time. The combination of historical and contemporary surveys allows (i) to test if observed contemporary patterns across space are consistent at the time of the historical survey, and, crucially, (ii) to assess whether changes in abundance over time given recorded environmental change match expectations from patterns recorded along environmental gradients in space. We found consistent spatial relationships at the two periods: local variation in soil variables and overstorey cover were the best predictors of individual species’ cover while interregional variation in coarse-scale variables, i.e. N deposition and climate, was less important. However, we found that our SFT approach could not accurately explain the large variation in abundance changes over time. We thus recommend to be cautious when using SFT substitution to infer species responses to temporal changes.

A Space-For-Time approach to study the effects of increasing temperature on leaf litter decomposition under natural conditions

Decomposition processes influence the formation of soil organic carbon stocks, and it is necessary to understand how both will respond to climate change. A Space-For-Time (SFT) substitution allows the comparison of litter decomposition under current and future conditions in the field, using a spatial gradient of environmental conditions. Here we used a SFT approach to study the effects of a difference in temperature similar to the predicted increase of 3.2–3.5 °C in Central Europe until 2100. To simulate this difference, we setup a five-fold replicated SFT substitution along mountain slopes and compared decomposition in two sites differing in ∿3.6 °C (600 vs 1200 m a.s.l). With this setup we compared the decomposition of high-quality (nettle) and low-quality (hay) litter, with and without fauna access, during summer, in five mountains in the Austrian Alps (Salzburg). Temperature loggers placed in one of the mountains indicated that the actual difference between the two altitudes was only ∿1.8 °C during summer. Nonetheless, decomposition of low-quality litter was 12% faster at 600 m than at 1200 m; altitude alone explained 19% of total variance. On the contrary, decomposition of high-quality litter was 9% faster at 1200 m. Fauna was the main driver of the high-quality litter decomposition at both altitudes and explained 26% of total variance, whereas altitude explained only 10%. Decomposition rates of the high-quality litter (21.4 ± 2.9 mg g−1 d−1; ±s.d.) was much higher than that of the low-quality (7.9 ± 1.0 mg g−1 d−1). Overall, the decomposition of the low-quality, slow-decomposing litter was more sensitive to warming and less influenced by the activity of detritivores, compared to a litter of higher quality. Through the use of the SFT substitution, we detected that a large part of the variance explained by the models was due to the variability between blocks and mountains, highlighting the important effect of spatial heterogeneity and the need for more replicated, field-based studies, to estimate the responses of decomposition processes to climate change.

Evapotranspiration sensitivity to air temperature across a snow-influenced watershed: Space-for-time substitution versus integrated watershed modeling

Changes in long-term, montane actual evapotranspiration (ET) in response to climate change could impact future water supplies and forest species composition. For scenarios of atmospheric warming, predicted changes in long-term ET tend to differ between studies using space-for-time substitution (STS) models and integrated watershed models, and the influence of spatially varying factors on these differences is unclear. To examine this, we compared warming-induced (+2 to +6 °C) changes in ET simulated by an STS model and an integrated watershed model across zones of elevation, substrate available water capacity, and slope in the snow-influenced upper San Joaquin River watershed, Sierra Nevada, USA. We used the Soil Water and Assessment Tool (SWAT) for the watershed modeling and a Budyko-type relationship for the STS modeling. Spatially averaged increases in ET from the STS model increasingly surpassed those from the SWAT model in the higher elevation zones of the watershed, resulting in 2.3–2.6 times greater values from the STS model at the watershed scale. In sparse, deep colluvium or glacial soils on gentle slopes, the SWAT model produced ET increases exceeding those from the STS model. However, watershed areas associated with these conditions were too localized for SWAT to produce spatially averaged ET-gains comparable to the STS model. The SWAT model results nevertheless demonstrate that such soils on high-elevation, gentle slopes will form ET “hot spots” exhibiting disproportionately large increases in ET, and concomitant reductions in runoff yield, in response to warming. Predicted ET responses to warming from STS models and integrated watershed models may, in general, substantially differ (e.g., factor of 2–3) for snow-influenced watersheds exhibiting an elevational gradient in substrate water holding capacity and slope. Long-term water supplies in these settings may therefore be more resilient to warming than STS model predictions would suggest.

Assessment ecological risk of heavy metal caused by high-intensity land reclamation in Bohai Bay, China.

The article examines the detailed spatial and temporal distributions of coastal reclamation in the northwest coast of Bohai Bay experiencing rapid coastal reclamation in China from 1974 to 2010 in annual intervals. Moreover, soil elements properties and spatial distribution in reclaimed area and inform the future coastal ecosystems management was also analyzed. The results shows that 910.7 km2 of coastal wetlands have been reclaimed and conversed to industrial land during the past 36 years. It covers intertidal beach, shallow sea and island with a percentage of 76.0%, 23.5% and 0.5%, respectively. The average concentration of Mn is 686.91mg/kg and the order of concentration of heavy metal are Cr>Zn>As>Ni>Cu>Pb>Cd>Hg. We used the "space for time substitution" method to test the soil properties changes after reclamation. The potential ecological risk of heavy metal is in low level and the risk of Cd and As is relatively higher. The ecosystem-based coastal protection and management are urgent to support sustainable coastal ecosystems in Bohai bay in the future.

Change in Soil Organic Carbon Stocks under 12 Climate Change Projections over New South Wales, Australia

Core Ideas Potential changes in soil organic C to 2070 mapped (100‐m grid) and examined. The direction and magnitude of change varied between the 12 climate projections. Differing changes revealed for 36 current climate–parent material–land use regimes. Digital soil mapping–space‐for‐time substitution is useful for climate change study Digital soil mapping (DSM) techniques combined with space‐for‐time substitution (SFTS) processes were used to map and examine soil organic carbon (SOC) changes caused by projected climate change over New South Wales, Australia until ∼2070. Twelve projections were derived from four global climate models downscaled with three regional climate models. A marked variation in the direction and magnitude of SOC change was demonstrated with the different projections. Mean state‐wide predictions (0–30 cm depth) ranged between 2.9 Mg ha‐1 gain and 8.7 Mg ha‐1 SOC loss. Greater consistency among climate change projections is required before we can confidently predict SOC changes. By using averaged results from the 12 projections, broad trends were revealed for the change in SOC over two intervals (0–30 and 30–100 cm). A mean loss rate of 2.0 Mg ha‐1 for the upper interval was demonstrated and a total loss of 737 Tg of CO2 equivalent for the entire depth to 100 cm but the 95% confidence interval was wide. Although changes are primarily controlled by the balance between changing temperatures and rainfall, the extent of change also depends on the environmental regime, with differing changes demonstrated over 36 current climate–parent material–land use combinations (e.g., projected mean SOC decline is &lt;1 Mg ha‐1 for dry–highly siliceous–cropping but &gt;15 Mg ha‐1 for wet–mafic–native vegetation). This DSM–SFTS technique offers a viable alternative to dynamic simulation techniques for predicting and identifying patterns in the change of soil properties caused by climate change.

Initial species composition predicts the progress in the spontaneous succession on post-mining sites

Although research has demonstrated that spontaneous succession of vegetation can be useful for the restoration of post-mining sites, spontaneous succession has only rarely been taken advantage of because of its low predictability. Spontaneous succession is difficult to predict because it depends, especially in the first stages, on many stochastic processes. Our goal was to determine whether the succession can be predicted based on the study of the chronosequence (space for time substitution) and whether the predictability of spontaneous succession can be improved by inventorying the plant community at disturbed sites during the initial stages of succession. After investigating successional changes by annual resampling of 50 permanent plots during 8 years (2007–2014) at chronosequence of five post-mining sites (created in 1965, 1987, 1990, 1995, and 2003) and located in the Sokolov coal mining district (northwestern Czech Republic), we found that species composition of younger chronosequence sites changes predictably towards the older sites. Simple parameters of initial species composition (cover of woody species, cover of the dominant grass Calamagrostis epigejos, total plant cover, and number of species) explained 24% of the variability in species composition in the last year of observation. The best predictor was cover of woody species. In the first years of succession, the post-mining sites are usually colonized by herbaceous vegetation but often also by pioneer trees. Over the next 20 years, succession may proceed to a forest stage or may be arrested in a non-forest stage, and this can be predicted based on woody species establishment early in succession. We demonstrate that inventorying vegetation before selecting restoration activities might improve the ability to predict the outcome of spontaneous succession and might therefore simplify its use in restoration.

Do space‐for‐time assessments underestimate the impacts of logging on tropical biodiversity? An Amazonian case study using dung beetles

Summary Human alteration of the global environment is leading to a pervasive loss of biodiversity. Most studies evaluating human impacts on biodiversity occur after the disturbance has taken place using spatially distinct sites to determine the undisturbed reference condition. This approach is known as a space‐for‐time (SFT) substitution. However, SFT substitution could be underestimating biodiversity loss if spatial controls fail to provide adequate inferences about pre‐disturbance conditions. We compare the SFT substitution with a before–after control–impact (BACI) approach by assessing dung beetles before and after a logging exploration in the Brazilian Amazon. We sampled 34 logging management units, of which 29 were selectively logged with different intensities after our first collection. We used dung beetle species richness, species composition and biomass as our biodiversity response metrics and the gradient of selective logging intensity as our explanatory metric. Only the BACI approach consistently demonstrated the negative impacts of logging intensification on all dung beetle community metrics. Moreover, the BACI approach explained significantly more of the variance in all the relationships and it doubled the estimates of species loss along the gradient of logging intensity when compared to SFT. Synthesis and applications. Our results suggest that space‐for‐time (SFT) substitution may greatly underestimate the consequences on local species diversity and community turnover. These results have important implications for researchers investigating human impacts on biodiversity. Incentivizing before–after control–impact (BACI) approaches will require longer‐term funding to gather the data and stronger links between researchers and landowners. However, BACI approaches are accompanied by many logistical constraints, making the continued use of SFT studies inevitable in many cases. We highlight that non‐significant results and weak effects should be viewed with caution.