Regional-scale Patterns Research Articles

Detection of functional diversity gradients and their geoclimatic filters is sensitive to data types (occurrence vs. abundance) and spatial scales (sites vs. regions)

Functional diversity (FD) reflects within- and between-site variation of species traits (α- and β-FD, respectively). Understanding how much data types (occurrence-based vs. abundance-weighted) and spatial scales (sites vs. regions) change FD and ultimately interfere with the detection of underlying geoclimatic filters is still debated. To contribute to this debate, we explored the occurrence of 1690 species in 690 sites, abundances of 1198 species in 343 sites, and seven functional traits of the Atlantic Forest woody flora in South America. All FD indices were sensitive and dependent on the data type at both scales, with occurrence particularly increasing α richness and dispersion (occurrence > abundance in 80% of the sites) while abundance increased β total, β replacement, and α evenness (abundance > occurrence in 60% of the sites). Furthermore, detecting the effect of geoclimatic filters depended on the data type and was scale-dependent. At the site scale, precipitation seasonality and soil depth had weak effects on α- and β-FD (max. R2 = 0.11). However, regional-scale patterns of α richness, dispersion, and evenness strongly mirrored the variation in precipitation seasonality, soil depth, forest stability over the last 120 kyr, and cation exchange capacity (correlations > 0.80), suggesting that geoclimatic filters manifest stronger effects at the regional scale. Also, the role of edaphic gradients expands the idea of biogeographical filters beyond climate. Our findings caution functional biogeographic studies to consider the effect of data type and spatial scale before designing and reaching ecological conclusions about the complex nature of FD.

Principal components analysis and K-means clustering of till geochemical data: Mapping and targeting of prospective areas for lithium exploration in Västernorrland Region, Sweden

To achieve the demand for elements used for the green transition energy, such as lithium, it is necessary to recognize the spatial distribution of the concentrations of these elements in different earth materials such as bedrock and soil and to identify areas with anomalous concentrations of such elements (i.e., mineralization) for further exploration and hopefully exploitation. This study carried out multivariate statistical analyses on compositional (i.e., element concentration) data from till samples to recognize areas that likely contain lithium pegmatite mineralization in the Västernorrland region, central Sweden. We applied principal components analysis (PCA) and K-means clustering techniques to reveal regional-scale patterns in the till geochemical data. We demonstrate that these two methods have potential for recognition of geochemical anomalies related to the underlying bedrock geology as well as to mineralization. The results of PCA- and K-means clustering were validated using known occurrences of lithium mineralization. Two different datasets were compared; one containing all available geochemical data and the second containing only available trace elements in the dataset and it was found that anomalous clusters of samples defined by K-means clustering have anomalous multi-element signatures defined by robust PCA. This demonstrated that principal components are the continuous solutions to the discrete cluster members for the K-means clustering. The results show that both PCA and K-means clustering of till geochemical datasets at the early stages of exploration and target generation may reveal useful information that can be used to identify potential areas for more detailed mapping or exploration activities.

Distinct latitudinal patterns and drivers of topsoil nitrogen and phosphorus across urban forests in eastern China.

Nitrogen (N) and phosphorus (P) are the two most important macronutrients supporting forest growth. Unprecedented urbanization has created growing areas of urban forests that provide key ecosystem services for city dwellers. However, the large-scale patterns of soil N and P content remain poorly understood in urban forests. Based on a systematic soil survey in urban forests from nine large cities across eastern China, we examined the spatial patterns and key drivers of topsoil (0-20 cm) total N content, total P content, and N:P ratio. Topsoil total N content was found to change significantly with latitude in the form of an inverted parabolic curve, while total P content showed an opposite latitudinal pattern. Variance partition analysis indicated that regional-scale patterns of topsoil total N and P contents were dominated by climatic drivers and partially regulated by time and pedogenic drivers. Conditional regression analyses showed a significant increase in topsoil total N content with lower mean annual temperature (MAT) and higher mean annual precipitation (MAP), while topsoil total P content decreased significantly with higher MAP. Topsoil total N content also increased significantly with the age of urban park and varied with pre-urban soil type, while no such effects were found for topsoil total P content. Moreover, topsoil N:P ratio showed a latitudinal pattern similar to that of topsoil total N content and also increased significantly with lower MAT and higher MAP. Our findings demonstrate distinct latitudinal trends of topsoil N and P contents and highlight a dominant role of climatic drivers in shaping the large-scale patterns of topsoil nutrients in urban forests.

Predicting the spatial expansion of an animal population with presence-only data.

Predictive models can improve the efficiency of wildlife management by guiding actions at the local, landscape and regional scales. In recent decades, a vast range of modelling techniques have been developed to predict species distributions and patterns of population spread. However, data limitations often constrain the precision and biological realism of models, which make them less useful for supporting decision-making. Complex models can also be challenging to evaluate, and the results are often difficult to interpret for wildlife management practitioners. There is therefore a need to develop techniques that are appropriately robust, but also accessible to a range of end users. We developed a hybrid species distribution model that utilises commonly available presence-only distribution data and minimal demographic information to predict the spread of roe deer (Capreolus caprelous) in Great Britain. We take a novel approach to representing the environment in the model by constraining the size of habitat patches to the home-range area of an individual. Population dynamics are then simplified to a set of generic rules describing patch occupancy. The model is constructed and evaluated using data from a populated region (England and Scotland) and applied to predict regional-scale patterns of spread in a novel region (Wales). It is used to forecast the relative timing of colonisation events and identify important areas for targeted surveillance and management. The study demonstrates the utility of presence-only data for predicting the spread of animal species and describes a method of reducing model complexity while retaining important environmental detail and biological realism. Our modelling approach provides a much-needed opportunity for users without specialist expertise in computer coding to leverage limited data and make robust, easily interpretable predictions of spread to inform proactive population management.

Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency.

Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine (i) if similar abiotic or biotic factors predict both large-scale (across sites) and regional-scale (within sites) patterns in bacterial and fungal community composition, and (ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs. high). Our results revealed that bacteria were associated with particular soil properties (such as base saturation) and both bacteria and fungi were associated with plant community composition across sites and within the majority of sites. Moreover, a discernible microbial community signal emerged, clearly distinguishing high and low-productivity soils across different grasslands independent of their location in the world. Hence, regional productivity differences may be typified by characteristic soil microbial communities across the grassland biome. These results could encourage future research aiming to predict the general effects of global changes on soil microbial community composition in grasslands and to discriminate fertile from infertile systems using generally applicable microbial indicators.

Substantial regional climate change expected following cessation of CO2 emissions

The zero emissions commitment (ZEC) is the expected temperature change following the cessation of anthropogenic emissions of climate altering gases and aerosols. Recent model intercomparison work has suggested that global average ZEC for CO2 is close to zero. However there has thus far been no effort to explore how temperature is expected to change at spatial scales smaller than the global average. Here we analyze the output of nine full complexity Earth System Models which carried out standardized ZEC experiments to quantify the ZEC from CO2. The models suggest that substantial temperature change following cessation of emissions of CO2 can be expected at large and regional spatial scales. Large scale patterns of change closely follow long established patterns seen during modern climate change, with higher variability and more change as one approaches the polar regions, and with more change over land than ocean. The sign of temperature change (warming or cooling) varies by model and climatic zone. At the regional scale patterns of change are far more complex and show little consistency between different models. Analysis of model output suggest that for most models these changes far exceed pre-industrial internal variability, suggesting either higher climate variability, continuing changes to climate dynamics or both. Overall substantial regional changes in climate are expected following cessation of CO2 emissions but the pattern, magnitude and sign of these changes remains highly uncertain.

Regional patterns in demersal fish assemblages among subsea pipelines and natural habitats across north-west Australia

Regional patterns of fish diversity, abundance, distribution, and assemblage composition are driven by a combination of biotic and abiotic conditions in the marine environment, but these conditions can be altered through anthropogenic activities, such as those associated with oil and gas extraction. The present study utilises data on fish relative abundance and diversity obtained from 1546 baited remote underwater video deployments conducted between 2004 – 2019 in depths of 9 – 170 m across 2000 km of coastline in north-west Australia on natural habitats and subsea pipelines to understand the influence of oil and gas infrastructure on fish assemblages. A total of 450 fish taxa from 56 families was observed, with populations dominated by generalist and invertebrate carnivore taxa. At the regional scale, subsea pipelines had lower diversity (lower taxonomic richness) than natural environments, but possessed a higher abundance of piscivorous and herbivorous fish taxa. Clear patterns in fish assemblage composition were observed in multivariate analyses, reflecting the proximity of oceanic shoals and banks, depth, and to a lesser extent, oil and gas infrastructure. Shallow-water and close to shoals assemblages were characterised by a diversity of site-attached (e.g., wrasses, tuskfish), reef-associated taxa (e.g., emperors). Mesophotic fish assemblages were characterised by commercially important (e.g., goldband snapper), wide-ranging (e.g., sharks) and sand-affiliated (e.g., toadfish, threadfin bream) taxa. Proximity to pipelines and platforms ranked low as predictors in the multivariate analyses suggesting a negligible regional influence of these structures on fish communities in comparison to depth and shoal habitats. Local-scale influences of subsea infrastructure, however, may be important for some fish species (infrastructure vs. immediate surrounds). Our study highlights the influence of abiotic factors on regional-scale patterns in fish assemblage structure across north-west Australia.

Increased Central European forest mortality explained by higher harvest rates driven by enhanced productivity

Increasing tree growth and mortality rates in Europe are still poorly understood and have been attributed to a variety of drivers. This study explored the role of climate drivers, management and age structure in driving changes in tree mortality rates in six Central European countries from 1985 to 2010, using the process-based vegetation model LPJ-GUESS. Simulations show a strong positive trend in canopy mortality rates in Central Europe, consistent with satellite observations. This trend was explained by an assumed increase in managed thinning in response to a modelled increase in forest productivity caused by climate change and rising atmospheric CO2 concentration. Simulated rates of canopy mortality were highly sensitive to the minimum tree size threshold applied for inclusion in the rate calculation, agreeing with satellite observations that are likely to only capture the loss of relatively large trees. The calculated trends in mortality rate also differed substantially depending on the metric used (i.e. carbon, stem or canopy mortality), highlighting the challenge of comparing tree mortality trends from different observation types. We conclude that changes in forest productivity and management in combination can profoundly affect regional-scale patterns of tree mortality. Our findings underscore the fact that increasing forest mortality can occur without reductions in forest growth when mediated by management responses to increasing productivity.

Non-growing season drought legacy effects on vegetation growth in southwestern China

Water availability influences terrestrial ecosystems' composition, structure, and function. Recently, climate change increased drought periods frequency and length in many parts of the world, including southwestern China, a biodiversity hotspot. Although the drought impacts on ecosystems are well known, studies are scarce in subtropical areas of China. This work studied the drought legacy effects on vegetation growth in southwestern China using Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI), with a particular focus on non-growing season extreme drought events. Pervasive non-growing season drought legacy effects were found in the first growing season in most parts of southwestern China. The highest impacts were identified in forests, while the effects in grass were less severe. At the regional scale, horizontal and vertical spatial patterns of drought legacy effects were heterogeneous, and the highest impacts were found in warmer and wetter forests and alpine grasslands. Our study highlights that severe drought conditions may dramatically affect vegetation growth in southwestern China.

Spatial Potential of Recreational Services in Western Hubei Region in Light of the “All-for-One Tourism” Development—A Machine Learning Approach Based on Ensemble Model

Under the call for “all-for-one tourism” development, the focus of regional-scale recreational services is shifting from the construction of individual scenic spots and tourist areas towards the comprehensive planning of tourist destinations, so as to propel China’s rural revitalization and regional coordinated development. In research and practice, however, it is still challenging to identity and evaluate spatial locations for developing tourism according their cultural and environmental resource and characteristics and prioritizing the high-potential ones. Employing the whole western Hubei region as a case study, this paper proposes a method of assessing recreation potential within the research framework on cultural ecosystem services, and uses multi-sourced social-ecological data to develop an SDM model via ensemble machine learning. Through analyses of the environmental features of 336 recreational hotspots in the study area, the model predicts the areas with high recreation potential in continuous areas. This study intends to establish a technique path to examine the regional-scale pattern of recreational spaces via numerical analysis of environmental features, and to provide a reference for relevant spatial development strategies of all-for-one tourism and rural revitalization.

Underpinning terroir with data: on what grounds might subregionalisation of the Barossa Zone geographical indication be justified?

Background and Aims Winegrowers in the Barossa Zone geographical indication of South Australia are interested in understanding subregional terroir. A previous analysis of biophysical variation over the entire Barossa Zone was not strongly supportive of the subregionalisation favoured by local winegrowers. Here, we use an updated, contemporary climate data set and focus just on land under vineyard as a platform for better understanding the biophysical component of the Barossa terroir. Methods and Results Clustering (k-means) of digital map layers describing a range of climatic and topographic indices along with soil properties of viticultural importance was used to explore regional-scale patterns of spatial variation. Marked soil, topographic and climatic variation was noted within the Barossa Zone, and the clustering suggested a useful biophysical basis for exploring the merits of dividing the geographical indication more finely than the existing Barossa and Eden Valley regions. Conclusions Whilst there are clear differences between the Barossa and Eden Valleys in terms of temperature, rainfall, soil fertility and the plant available water capacity of soil, the clusters identified suggest that a re-evaluation of the presently proposed subdivision of the Barossa Valley region may be warranted. Wine chemical and sensory data would need to be integrated with the biophysical data to confirm the expression of subregional terroir effects within the Barossa Valley. Significance of the Study This data-driven analysis provides further evidence of the desirability of terroir analysis being free of the bias that is introduced by heuristics, or by examination of historically delineated terroirs, and of focussing solely on the land which is under vine in evaluating terroir.

Ecological considerations for marine spatial management in deep-water Tanzania

The United Republic of Tanzania has jurisdiction over a large marine area (223,000 km2) of which over 92% is deeper than 200 m. These deep areas extend from, in most cases <10 km from shore, have connections to shallow and coastal marine habitats through oceanographic processes, and support important living and non-living resources, which are becoming increasingly exploited to support a valuable blue economy. Recognising the need for sustainable development, implementation of conservation and management measures in Tanzania's offshore waters has begun, with the development of coastal protected areas and marine spatial plans (e.g. the Coastal and Marine Spatial Plan for Zanzibar). As yet, the deeper areas of Tanzania have not been considered in marine spatial planning. Here we present a synthesis of available data on the habitats and biological communities of deep-water Tanzania, including new data collected in collaboration with the deep-water oil and gas industry, to provide an indication of regional-scale patterns and areas of potential importance. We also discuss the value and multiple uses of the deep ocean areas to Tanzania, and assess the ecological effects of impacts in these environments. This information is valuable to the Tanzanian government to help inform development of management measures to continue to make sustainable use of valuable deep-water resources. To facilitate uptake, we provide a series of recommendations on considering the Tanzanian deep ocean areas in marine spatial planning to boost future management of the important and sensitive offshore domain.

Underpinning terroir with data: a quantitative analysis of biophysical variation in the Margaret River region of Western Australia

Background and Aims The wine producers of Margaret River, as in many Australian wine regions, are interested in gaining a better understanding of the terroir of their region. Our aim was to determine whether the variation in soils and climate suggests that subdivision of the region may have merit. Methods and Results Clustering of digital map layers describing a range of climatic indices and soil properties of viticultural importance, using k-means, enabled exploration of regional scale patterns of spatial variation. These methods are the same as those that have been successfully used at within-vineyard scale in support of the development of Precision Viticulture. Whilst there is marked soil and climatic variation within the Margaret River geographical indication (GI), the results obtained from this analysis do not lend weight to previously proposed subdivisions of the Margaret River GI but rather, provide a guide for future targeted sensory analysis within the region. This was especially the case when the analysis was confined to just the 2.8% of the GI land area that is under vineyard. Conclusions Whilst the Margaret River GI shows marked biophysical variation, the data used in this analysis were not sufficiently strongly spatially structured at regional scale to indicate a basis for splitting the GI into subregions. However, some separation based solely on temperature and rainfall might form a useful basis for chemical and sensory analysis of wines and pursuit of understanding of the regional terroir. From both terroir and viticultural management perspectives, soil variation is likely of much greater importance at the within-vineyard and whole of property scales, than at regional scale. Significance of the Study This is one of the first studies which uses purely data driven methods to examine biophysical variation within a wine region. Aside from being free of the bias that is introduced by heuristics, or examination of historically delineated terroirs, the work highlights the importance of focussing solely on the land which is under vine in evaluating terroir, rather than all of the land within a GI.

Habitat Primarily Structures Seagrass Epifaunal Communities: a Regional-Scale Assessment in the Chesapeake Bay

Epifaunal invertebrates play an important role in seagrass systems, both by grazing epiphytic algae from seagrass blades and by acting as a major food source for higher trophic levels. However, while many studies have described epifaunal community properties at small spatial scales (1–10 m2) and across very large gradients (from continental coastlines to the entire globe), few have examined regional-scale (100–1000 km2) patterns or, more importantly, disentangled the drivers of these patterns. Here, we synoptically sampled the epifaunal invertebrates of 16 sites dominated by eelgrass (Zostera marina) across the lower Chesapeake Bay estuary to describe differences in epifaunal community abundance, biomass, richness, and composition. We then used complementary spatial and environmental data to identify potential drivers of these patterns. We found no significant associations between any variable and epifaunal abundance or biomass, but differences in epifaunal species richness correlated most strongly with water temperature, and differences in community composition were best explained by seagrass cover and the biomass of algal resources. Further exploration revealed the relationship between cover and community structure was driven by three specific species of peracarid crustaceans. Furthermore, when only species with direct development were included in the analysis, geographic distance, rather than seagrass cover, became a significant predictor of community composition, suggesting that species with particular traits (i.e., direct developers) are more likely to be found closer together in space.

High-Resolution Imaging of Hydraulic-Fracturing-Induced Earthquake Clusters in the Dawson-Septimus Area, Northeast British Columbia, Canada

Abstract The number of earthquakes in the western Canada sedimentary basin (WCSB) has increased drastically in the last decade related to unconventional energy production. The majority of reported earthquakes are correlated spatially and temporally with hydraulic fracturing (HF) well stimulation. In this study, we use waveform data from a new deployment of 15 broadband seismic stations in a spatial area of roughly 60×70km2, covering parts of the Montney Formation, to study the relationship between earthquakes and HF operations in the Dawson-Septimus area, British Columbia, Canada, where the two largest HF-related earthquakes in WCSB to date, an Mw 4.6 on 17 August 2015 and an ML 4.5 on 30 November 2018, have occurred. We use an automated short-term average/long-term average algorithm and the SeisComP3-software to detect and locate 5757 local earthquakes between 1 July 2017 and 30 April 2019. Using two clustering techniques and double-difference relocations of the initial catalog, we define event families that are spatially associated with specific wells, and exhibit temporal migration along a horizontal well bore and/or multiple fractures close to wells. Relocated clusters align in two dominant orientations: one roughly perpendicular to the maximum horizontal regional stress direction (SH) and several conjugate structures at low angles to SH. Comparing the two predominant seismicity lineations to regional earthquake focal mechanisms suggests that deformation occurs via thrust faulting with fault strike oriented perpendicular to SH and via strike-slip faulting with strike azimuth at low angles to SH. Local scale seismicity patterns exhibit clustering around individual HF wells, whereas regional scale patterns form lineations consistent with deformation on faults optimally oriented in the regional stress field.

Contrasting patterns of genetic differentiation for deep-sea amphipod taxa along New Zealand's continental margins

Intraspecific genetic differentiation reflects processes that underpin biodiversity in deep-sea habitats. We examined the spatial genetic structure of epibenthic amphipod taxa from upper bathyal depths (200–1200 m) along New Zealand's continental margins. Genetic variability in amphipods was assessed using cytochrome c oxidase I (COI) to characterise inter-regional diversity and phylogeographic patterns in the Chatham Rise and Challenger Plateau to the east and west of New Zealand, respectively. Automatic barcode gap discovery methods identified 263 MOTUs, of which 14 were detected in both regions. Population genetic analyses found contrasting patterns of diversity among different MOTUs within and between regions. Overall, a pattern of increasing genetic differentiation (K2P distances) with decreasing depth was observed between regions. Genetic differentiation was highest among MOTUs found at shallow depths, while taxa from deeper waters showed little evidence of divergence. Our results suggest that intraspecific genetic diversity is correlated with amphipod family traits, particularly dispersal abilities inferred from habitat preferences (infaunal, epibenthic or pelagic) and may also be linked to regional geological history. Such insights have important implications for regional-scale patterns of diversity associated with local processes in promoting differentiation among populations of bathyal amphipods on New Zealand's continental margins.

Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil

Evapotranspiration ( E T ) provides a strong connection between surface energy and hydrological cycles. Advancements in remote sensing techniques have increased our understanding of energy and terrestrial water balances as well as the interaction between surface and atmosphere over large areas. In this study, we computed surface energy fluxes using the Surface Energy Balance Algorithm for Land (SEBAL) algorithm and a simplified adaptation of the CIMEC (Calibration using Inverse Modeling at Extreme Conditions) process for automated endmember selection. Our main purpose was to assess and compare the accuracy of the automated calibration of the SEBAL algorithm using two different sources of meteorological input data (ground measurements from an eddy covariance flux tower and reanalysis data from Modern-Era Reanalysis for Research and Applications version 2 (MERRA-2)) to estimate the dry season partitioning of surface energy and water fluxes in a transitional area between tropical rainforest and savanna. The area is located in Brazil and is subject to deforestation and cropland expansion. The SEBAL estimates were validated using eddy covariance measurements (2004 to 2006) from the Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA) at the Bananal Javaés (JAV) site. Results indicated a high accuracy for daily ET, using both ground measurements and MERRA-2 reanalysis, suggesting a low sensitivity to meteorological inputs. For daily ET estimates, we found a root mean square error (RMSE) of 0.35 mm day−1 for both observed and reanalysis meteorology using accurate quantiles for endmembers selection, yielding an error lower than 9% (RMSE compared to the average daily ET). Overall, the ET rates in forest areas were 4.2 mm day−1, while in grassland/pasture and agricultural areas we found average rates between 2.0 and 3.2 mm day−1, with significant changes in energy partitioning according to land cover. Thus, results are promising for the use of reanalysis data to estimate regional scale patterns of sensible heat (H) and latent heat (LE) fluxes, especially in areas subject to deforestation.

Automated multi-classifier recognition of atmospheric turbulent structures obtained by Doppler lidar

We present algorithms and results of automated processing of LiDAR measurements obtained during VEGILOT measuring campaign in Paris in autumn 2014 in order to study horizontal turbulent atmospheric regimes on urban scales. To process images obtained by horizontal atmospheric scanning using Doppler LiDAR, the method is proposed based on texture analysis and classification using supervised machine learning algorithms. The results of the parallel classification by various classifiers were combined using the majority voting strategy. The obtained estimates of accuracy demonstrate the efficiency of the proposed method for solving the problem of remote sensing of regional-scale turbulent patterns in the atmosphere.

Storage and Climatic Controlling Factors of Litter Standing Crop Carbon in the Shrublands of the Tibetan Plateau

Litter is an important component of terrestrial ecosystems and plays a significant role in carbon cycles. Quantifying regional-scale patterns of litter standing crop distribution will improve our understanding of the mechanisms of the terrestrial carbon cycle, and thus enable accurate predictions of the responses of the terrestrial carbon cycle to future climate change. In this study, we aimed to estimate the storage and climatic controlling factors of litter standing crop carbon in the Tibetan Plateau shrublands. We investigated litter standing crop carbon storage and its controlling factors, using a litter survey at 65 shrublands sites across the Tibetan Plateau from 2011–2013. Ordinary least squares regression analyses were conducted to estimate the relationships between litter standing crop carbon, longitude, and latitude. Multiple linear regressions were used to evaluate relationships among litter standing crop carbon, mean annual temperature (MAT), mean annual precipitation (MAP), and aboveground biomass. The litter standing crop carbon storage was 10.93 Tg C, 7.40 Tg C, and 3.53 Tg C in desert shrublands and alpine shrublands, respectively. Litter standing crop carbon decreased with longitude, and was stable with increasing latitude. Most (80%) of the litter standing crop was stored in branches, with only 20% stored in foliage in the shrublands on the Tibetan Plateau. The conversion coefficient was 0.44 for litter standing crop to litter standing crop carbon, and 0.39 and 0.45 for foliage and branch litter standing crop to foliage and branch litter standing crop carbon, respectively. Aboveground biomass can accelerate more inputs of litter and has a positive effect on litter standing crop carbon. MAT had a positive effect on litter standing crop carbon due to stimulating more input of aboveground biomass. However, MAP had a negative relationship with litter standing crop carbon by enhancing litter decomposition.

Saline wetland extents and tidal inundation regimes on a micro-tidal coast, New South Wales, Australia

The microtidal coast of New South Wales (NSW), Australia contains a broad range of estuary types that can be classified according to their internal geomorphology and entrance hydraulic conditions. We present an analysis of intertidal wetland area and the proportion of mangrove and saltmarsh, and investigate the variety of tidal inundation regimes in NSW estuaries. Our work hypothesizes that regional patterns in wetland extent and tidal inundation regimes are related to estuary type, through controls on intra-estuary geomorphology and modification of the open-coast tide. Several styles of tidal inundation regime are identified, which display markedly different combinations of the average frequency, duration and depth of inundation events for a specified elevation in the tidal frame. The regional-scale patterns in saline wetland extent and the tidal inundation regimes identified herein are potentially representative of microtidal estuaries more broadly, including similar estuary types in South Africa and Brazil.