Variability In Ecosystem Functioning Research Articles

Ecosystem functional types of the circumpolar Arctic tundra based on the seasonal dynamics of vegetation productivity

Biodiversity, when viewed through the combined lenses of compositional, structural, and functional attributes, provides for a holistic understanding of the complexities found within community assemblages and ecosystems. However, advancement in our understanding of how ecosystem functional diversity interacts with structural and compositional diversity metrics is lacking, in part because universally applied methodologies to derive ecosystem functional classifications are still under development and vary widely across scales, extents and biomes. This study presents a methodology to construct ecosystem functional types (EFTs), or areas of the land surface that function similarly, using the MODIS NDVI record, for the terrestrial circumpolar Arctic. EFTs were derived from the seasonal dynamics of NDVI, over the Arctic tundra at 250 m resolution and compared to bioclimate subzones and to structurally and compositionally defined vegetation units of the Circumpolar Arctic Vegetation Map (CAVM). Correspondence analyses of CAVM EFTs to previously delineated CAVM bioclimatic subzones, physiognomic (vegetation) units and floristic provinces revealed a general congruence, indicating convergence across composition, structure, and function; yet also demonstrated substantial functional variability even within bioclimate subzones and vegetation units. Strong latitudinal gradients in ecosystem function are present, with EFT richness ranging from low (34) in northernmost regions to high (45) in southernmost regions. Locally, the mountainous regions of northern Alaska, and eastern and western Siberia had high spatial variability in ecosystem functioning. Aside from these generalities, we found that EFTs varied widely within individual mapped vegetation units, successfully capturing the functional dimension of biodiversity across the circumpolar Arctic tundra.

Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain.Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits.Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %–69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %–50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau.Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.

Effect of increased inundation time on intertidal ecosystem functions of South West Atlantic soft-bottom environments

Soft-bottom intertidal systems are valuable due to the ecosystem services they provide. Although these systems are normally subjected to highly variable environmental conditions, disturbances have become more frequent due to increases in anthropogenic pressure. Sea level rise (SLR) may generate changes in the ecosystem functioning of intertidal systems and in the ecosystem services they provide. In the Argentinean coast (SW Atlantic), SLR analysis shows trends similar to the global ones. It is not known how disturbances may affect the activity of benthic communities and the associated ecosystem functions. Therefore, through a field experiment at the marsh-mudflat edge in northeastern Argentina, we evaluated the effect of increased inundation time on bioturbation intensity, detritus decomposition and microphytobenthic primary production. Sediment physicochemical parameters (pH, temperature, water content and organic matter) were also measured. The results showed that increased inundation time had no effect on microphytobenthic primary production or bioturbation intensity in summer. Nevertheless, inundation time increased the burrowing activity of the intertidal crabNeohelice granulatain winter and spring and greatly decreased the variability inSpartina densifloradecomposition and organic matter content. In the context of a changing world due to global climate change, reduced variability in ecosystem functioning could indicate a decline in ecosystem resilience. As a consequence, vital ecosystem functions could be altered or lost, thus impacting the ecosystem services they deliver.

Review: Monitoring of land cover changes and plant phenology by remote‐sensing in East Asia

AbstractTo achieve a sustainable society and solve the problems caused by climate change and socioeconomic activities, it is necessary to monitor the spatial and temporal variability of ecosystem functions, services, and biodiversity at both regional and global scales. During the last decade, we have seen rapid and significant improvement in satellite and near‐surface remote‐sensing technologies. In this review, we describe how remote‐sensing observations are being used to effectively evaluate the spatial and temporal variability of land use and cover types and of plant phenology in East Asia. We discuss the current status, uncertainties, problems, and future perspectives for terrestrial ecosystem and biodiversity monitoring, and we address the multidisciplinary research by incorporating in situ and satellite observations for East Asia. Recent satellites with advanced optical sensors, such as MultiSpectral Instrument/Sentinel‐2A/2B, Advanced Himawari Imager/Himawari‐8, and PlanetScope, and satellites with synthetic aperture radar, such as Advanced Land Observing Satellite‐2, allow detailed monitoring of land use and cover type changes and plant phenology. These satellite sensors can provide images with high spatial (3–10 m) and high temporal (10 min to 5 days) resolution, at both large (≥1 km2) and small (<1 km2) scales. In particular, researchers are expected to develop discrimination techniques that will enable these advanced satellite technologies to detect evergreen broadleaf trees and ways to estimate the geographic distribution of leaf traits. We encourage more collaborations among ecologists, engineers, and remote‐sensing scientists to share their abundant knowledge and experience and thereby improve the monitoring capabilities.

Co-varying effects of vegetation structure and terrain attributes are responsible for soil respiration spatial patterns in a sandy forest–steppe transition zone

Abstract. Forest–steppe habitats in central Hungary have contrasting canopy structure with strong influence on the spatiotemporal variability of ecosystem functions. Canopy differences also co-vary with terrain feature effects, hampering the detection of key drivers of carbon cycling in this threatened habitat. We carried out seasonal measurements of ecosystem functions (soil respiration and leaf area index), microclimate and soil variables as well as terrain features along transects for 3 years in poplar groves and the surrounding grasslands. We found that the terrain features and the canopy differences co-varyingly affected the abiotic and biotic factors of this habitat. Topography had an effect on the spatial distribution of soil organic carbon content. Canopy structure had a strong modifying effect through allocation patterns and microclimatic conditions, both affecting soil respiration rates. Due to the vegetation structure difference between the groves and grasslands, spatial functional diversity was observed. We found notably different conditions under the groves with high soil respiration, soil water content and leaf area index; in contrast, on the grasslands (especially in E–SE–S directions from the trees) soil temperature and vapor pressure deficit showed high values. Processes of aridification due to climate change threaten these habitats and may cause reduction in the amount and extent of forest patches and decrease in landscape diversity. Owing to habitat loss, reduction in carbon stock may occur, which in turn has a significant impact on the local and global carbon cycles.

Does the use of biological traits predict a smooth landscape of ecosystem functioning?

The biodiversity crisis has increased interest in understanding the role of biodiversity for ecosystem functioning. Functional traits are often used to infer ecosystem functions to increase our understanding of these relationships over larger spatial scales. The links between specific traits and ecosystem functioning are, however, not always well established. We investigated how the choice of analyzing either individual species, selected modalities, or trait combinations affected the spatial patterns observed on a sandflat and how this was related to the natural variability in ecosystem functioning. A large dataset of 400 benthic macrofauna samples was used to explore distribution patterns. We hypothesized that (1) if multiple species (redundancy) represent a trait combination or a modality their spatial patterns would be smoothed out, and (2) the lost spatial variability within a trait combination or modality, due to the smoothing effect, would potentially affect their utility for predicting ecosystem functioning (tested on a dataset of 24 samples). We predicted that species would show heterogeneous small spatial patterns, while modalities and trait combinations would show larger and more homogeneous patterns because they would represent a collection of many distributions. If modalities and trait combinations are better predictors of ecosystem functioning than species, then the smoother spatial patterns of modalities and trait combinations would result in a more homogeneous landscape of ecosystem function and the number of species exhibiting specific traits would provide functional redundancy. Our results showed some smoothing of spatial patterns progressing from species through modalities to trait combinations, but generally spatial patterns reflected a few dominant key species. Moreover, some individual modalities and species explained more or equal proportions of the variance in the ecosystem functioning than the combined traits. The findings thus suggest that only some spatial variability is lost when species are combined into modalities and trait combinations and that a homogeneous landscape of ecosystem function is not likely.

Imaging Spectroscopy of Forest Ecosystems: Perspectives for the Use of Space-borne Hyperspectral Earth Observation Systems

The emerging challenges in preserving and managing forest ecosystems are multiscale in terms of space and time, and therefore require spatially and temporally contiguous information sources. Imaging spectroscopy has the potential to contribute information that cannot be raised by other Earth Observation Systems. In particular, the spectral capacity to monitor the distributions of chemical traits, such as canopy foliar nitrogen distribution, and to track changes in water content or the percentage water in plants, has already opened novel pathways toward assessing the global variability of ecosystem functions and services. However, there is an ongoing debate on how to best extract this type of information from the spectral measurements. Empirical approaches have demonstrated their efficiency in a multitude of local studies, but are criticized with respect to poor generalization capacities. Alternative strategies, such as the use of physically based models of leaf or canopy reflectance, or hybrid approaches, have the potential advantage to be more widely applicable. This paper attempts to assess achievements and shortcomings of these strategies and finds that the often-cited disadvantages of using empirical approaches are becoming less pronounced in the light of recent research results. While retrievals based on physically based models on leaf/needle level are close to laboratory quality, results on canopy level available to date still have considerable deficits. Owing to improved instrumental designs, better data calibration, new approaches for compensating canopy effects, and the use of increasingly efficient methods for establishing data-driven models, the scope of empirical approaches has considerably widened and they have been successfully applied to large areas. The future availability of regularly acquired hyperspectral imagery from Earth orbits will substantially contribute to their generalizability.

Ecosystem functional response across precipitation extremes in a sagebrush steppe.

BackgroundPrecipitation is predicted to become more variable in the western United States, meaning years of above and below average precipitation will become more common. Periods of extreme precipitation are major drivers of interannual variability in ecosystem functioning in water limited communities, but how ecosystems respond to these extremes over the long-term may shift with precipitation means and variances. Long-term changes in ecosystem functional response could reflect compensatory changes in species composition or species reaching physiological thresholds at extreme precipitation levels.MethodsWe conducted a five year precipitation manipulation experiment in a sagebrush steppe ecosystem in Idaho, United States. We used drought and irrigation treatments (approximately 50% decrease/increase) to investigate whether ecosystem functional response remains consistent under sustained high or low precipitation. We recorded data on aboveground net primary productivity (ANPP), species abundance, and soil moisture. We fit a generalized linear mixed effects model to determine if the relationship between ANPP and soil moisture differed among treatments. We used nonmetric multidimensional scaling to quantify community composition over the five years.ResultsEcosystem functional response, defined as the relationship between soil moisture and ANPP, was similar among irrigation and control treatments, but the drought treatment had a greater slope than the control treatment. However, all estimates for the effect of soil moisture on ANPP overlapped zero, indicating the relationship is weak and uncertain regardless of treatment. There was also large spatial variation in ANPP within-years, which contributes to the uncertainty of the soil moisture effect. Plant community composition was remarkably stable over the course of the experiment and did not differ among treatments.DiscussionDespite some evidence that ecosystem functional response became more sensitive under sustained drought conditions, the response of ANPP to soil moisture was consistently weak and community composition was stable. The similarity of ecosystem functional responses across treatments was not related to compensatory shifts at the plant community level, but instead may reflect the insensitivity of the dominant species to soil moisture. These species may be successful precisely because they have evolved life history strategies that buffer them against precipitation variability.

Combining field experiments and predictive models to assess potential for increased plant diversity to climate-proof intensive agriculture.

Agricultural production systems face increasing threats from more frequent and extreme weather fluctuations associated with global climate change. While there is mounting evidence that increased plant community diversity can reduce the variability of ecosystem functions (such as primary productivity) in the face of environmental fluctuation, there has been little work testing whether this is true for intensively managed agricultural systems. Using statistical modeling techniques to fit environment–productivity relationships offers an efficient means of leveraging hard‐won experimental data to compare the potential variability of different mixtures across a wide range of environmental contexts. We used data from two multiyear field experiments to fit climate–soil–productivity models for two pasture mixtures under intensive grazing—one composed of two drought‐sensitive species (standard), and an eight‐species mixture including several drought‐resistant species (complex). We then used these models to undertake a scoping study estimating the mean and coefficient of variation (CV) of annual productivity for long‐term climate data covering all New Zealand on soils with low, medium, or high water‐holding capacity. Our results suggest that the complex mixture is likely to have consistently lower CV in productivity, irrespective of soil type or climate regime. Predicted differences in mean annual productivity between mixtures were strongly influenced by soil type and were closely linked to mean annual soil water availability across all soil types. Differences in the CV of productivity were only strongly related to interannual variance in water availability for the lowest water‐holding capacity soil. Our results show that there is considerable scope for mixtures including drought‐tolerant species to enhance certainty in intensive pastoral systems. This provides justification for investing resources in a large‐scale distributed experiment involving many sites under different environmental contexts to confirm these findings.

Seasonal leaf phenology data for 12 tree species in a cool‐temperate deciduous broadleaved forest in Japan from 2005 to 2014

AbstractThis paper reports seasonal data regarding leaf number, leaf length and width, leaf area, leaf angle, and SPAD (leaf chlorophyll content index) for 11 genera (12 species) in a cool‐temperate deciduous broadleaved forest in Japan. Knowing the leaf phenology of tree species is important for accurately evaluating the temporal variability of ecosystem functions (e.g., photosynthesis and evapotranspiration) under rapid climate change. However, there is a lack of freely available long‐term observation data regarding leaf phenological characteristics for many tree species. We collected leaf phenological data from tagged shoots every 1–4 weeks from April or May to October or November each year from 2005 to 2014 in Takayama, Japan (36°08′46″N, 137°25′23″E, 1420 m a.s.l.). We targeted typical dominant, codominant, and understory tree species at the site. To evaluate differences among individuals and between sunlit and shaded leaves, we measured one to four shoots of some species and individuals. Our data provide input, calibration, and validation parameters for a terrestrial ecosystem and for radiative‐transfer models and remote‐sensing observations.

Lake Fluctuations, Plant Productivity, and Long-Term Variability in High-Elevation Tropical Andean Ecosystems

Environmental trends and ecosystems’ ranges of variability are little known in tropical very high elevation Andean ecosystems (above 4400 m a.s.l.). We combined satellite image analyses and dendrochronological methods with instrumental records at lower elevation to assess changes in lake size and indices of plant productivity of subtropical high-elevation ecosystems in northern Argentina and southern Bolivia. Between 1985 and 2009, interannual lake fluctuations assessed with Landsat images were positively correlated with interannual variations in regional precipitation and de Martonne’s aridity index, showing a decreasing trend in moisture availability during the period. Changes in lake size were positively correlated with radial growth of Polylepis tarapacana, and with MODIS-derived phenological parameters of enhanced vegetation index (EVI; an index of vegetation “greenness”) between 2001 and 2010. This indicates that water balance has a significant effect on ecosystem functioning, which is related to regional scale atmospheric circulation. A long-term tree ring chronology (starting in 1750) showed that tree growth during recent decades was lower than the last 180 years, and were comparable to growth patterns that occurred between 1775 and 1825. These results suggest that if recent climatic trends continue, long-term ranges of variability in ecosystem functioning could be exceeded.

MONITORING PHENOLOGICAL VARIABILITY ACROSS A TROPICAL SAVANNA ARIDITY GRADIENT WITH REMOTE SENSING ACROSS SEASONAL TO ANNUALAND EXTREME EVENTS

Abstract. Tropical savannas are key components of the global carbon and water cycles and understanding their functioning is critical to understanding ecosystem feedbacks to global climate. By observing broad scale vegetation responses to climatic variability, remote sensing offers powerful insights into the patterns and processes underlying savanna behaviour. However, savannas are highly complex, multi-layer and heterogenous ecosystems composed of C3 (herbaceous) and C4 (woodland) components with asynchronous phenological responses to environmental controls. There are concerns about optimizing the detection of savanna functioning as well as in understanding their environmental controls with remote-sensing data due to their coarse resolution. Furthermore, seasonalphenologic variations in satellite observations need to be sufficiently accurate to ensure confidence in interpreting vegetation responses to interannual climatic variation and to aid in constraining models of carbon and water fluxes. In this study, we analysed several years of high temporal frequency MODIS and TRMM satellite data sets of vegetation dynamics and rainfall, respectively, to seasonal and interannual responses of savanna multifunctional components to climate variability across a tropical savanna aridity gradient (1760 to 580 mm annual rainfall) in northern Australia. We compared our results with a series of eddy covariance (EC) tower flux data of gross primary production and analyzed a wide set of ecosystem processes including photosynthesis, net primary productivity, phenological metrics in timing of the growing season, and rain use efficiencies. We found MODIS satellite measurements to yield highly accurate spatial and temporal variability in ecosystem functioning and able to replicate interannual patterns and responses to rainfall observed with the EC tower data. Although these results appear promising for regional extensions of satelliteflux tower relationships at the landscape level, we also observed various issues with footprint matching and hysteresis effects that potentially may limit the utility of remote sensing in scaling fluxes of carbon and water to the regional scales.

Functional biodiversity of macroinvertebrate assemblages along major ecological gradients of boreal headwater streams

Summary1. Biodiversity–environment relationships are increasingly well‐understood in the context of species richness and species composition, whereas other aspects of biodiversity, including variability in functional diversity (FD), have received rather little rigorous attention. For streams, most studies to date have examined either taxonomic assemblage patterns or have experimentally addressed the importance of species richness for ecosystem functioning.2. I examined the relationships of the functional biodiversity of stream macroinvertebrates to major environmental and spatial gradients across 111 boreal headwater streams in Finland. Functional biodiversity encompassed functional richness (FR – the number of functional groups derived from a combination of functional feeding groups and habit trait groups), FD – the number of functional groups and division of individuals among these groups, and functional evenness (FE – the division of individuals among functional groups). Furthermore, functional structure (FS) comprised the composition and abundance of functional groups at each site.3. FR increased with increasing pH, with additional variation related to moss cover, total nitrogen, water colour and substratum particle size. FD similarly increased with increasing pH and decreased with increasing canopy cover. FE decreased with increasing canopy cover and water colour. Significant variation in FS was attributable to pH, stream width, moss cover, substratum particle size, nitrogen, water colour with the dominant pattern in FS being related to the increase of shredder‐sprawlers and the decrease of scraper‐swimmers in acidic conditions.4. In regression analysis and redundancy analysis, variation in functional biodiversity was not only related to local environmental factors, but a considerable proportion of variability was also attributable to spatial patterning of environmental variables and pure spatial gradients. For FR, 23.4% was related to pure environmental effects, 15.0% to shared environmental and spatial effects and 8.0% to spatial trends. For FD, 13.8% was attributable to environmental effects, 15.2% to shared environmental and spatial effects and 5% to spatial trends. For FE, 9.0% was related to environmental variables, 12.7% to shared effects of environmental and spatial variables and 4.5% to spatial variables. For FS, 13.5% was related to environmental effects, 16.9% to shared environmental and spatial effects and 15.4% to spatial trends.5. Given that functional biodiversity should portray variability in ecosystem functioning, one might expect to find functionally rather differing ecosystems at the opposite ends of major environmental gradients (e.g. acidity, stream size). However, the degree to which variation in the functional biodiversity of stream macroinvertebrates truly portrays variability in ecosystem functioning is difficult to judge because species traits, such as feeding roles and habit traits, are themselves strongly affected by the habitat template.6. If functional characteristics show strong responses to natural environmental gradients, they also are likely to do so to anthropogenic environmental changes, including changes in habitat structure, organic inputs and acidifying elements. However, given the considerable degree of spatial structure in functional biodiversity, one should not expect that only the local environment and anthropogenic changes therein are responsible for this variability. Rather, the spatial context, as well as natural variability along environmental gradients, should also be explicitly considered in applied research.

Biodiversity and ecosystem functioning in aquatic microbial systems: a new analysis of temporal variation and species richness‐predictability relations

Studies of microbial communities from aquatic ecosystems provide important insights into relations between various aspects of ecosystem functioning and changes in biodiversity. Aquatic microbial systems provide a valuable counterpoint to studies of terrestrial systems, because patterns reflect consequences of interactions occurring over many generations of community development, and are unlikely to represent artifacts of the initial conditions established in experimental communities. In this paper we re‐analyse our previously published data to separate the contributions of temporal and spatial variation to overall variation in ecosystem functioning. A new analysis based on re‐sampling confirms a negative relationship between richness and the variability of one ecosystem process, carbon dioxide flux. The negative relationship reflects high variation among communities of low species richness, rather than high temporal variation within communities of low richness. We also review the various transformations and summary statistics proposed as alternate measures of variability in ecosystem functioning, to point out that different measures are often appropriate for different kinds of data. Finally, we conclude that arguments about the cosmopolitan distribution of microbes do not preclude the existence of important relations between microbial species richness and ecosystem functioning.

On similarity among local communities in biodiversity experiments

As a potential mechanism to explain how biodiversity loss may influence variability in ecosystem functioning, we examine the hypothesis that biodiversity loss lowers similarity in species composition among local communities and that this decreased similarity in turn lowers ecosystem reliability. Ecosystem reliability refers to the probability that a system will provide a consistent level of performance over a given unit of time. This hypothesis is compared with other hypotheses that make similar predictions, including the sampling effect, insurance, and resource use complementarity hypotheses. We provide evidence for the similarity hypothesis through a reanalysis of a recent experiment and show that a key assumption of the hypothesis may be robust through computer simulations. We also address problems and possible solutions regarding how to separately test the similarity and other hypotheses in biodiversity experiments.