Ecosystem Functional Attributes Research Articles

A remote-sensing-based dataset to characterize the ecosystem functioning and functional diversity in the Biosphere Reserve of the Sierra Nevada (southeastern Spain)

Abstract. Conservation biology faces the challenge of safeguarding the ecosystem functions and ecological processes (the water cycle, nutrients, energy flow, and community dynamics) that sustain the multiple facets of biodiversity. Characterization and evaluation of these processes and functions can be carried out through functional attributes or traits related to the exchanges of matter and energy between vegetation and the atmosphere. Based on this principle, satellite imagery can provide integrative spatiotemporal characterizations of ecosystem functions at local to global scales. Here, we provide a multitemporal dataset at protected-area level that characterizes the spatial patterns and temporal dynamics of ecosystem functioning in the Biosphere Reserve of the Sierra Nevada (Spain), captured through the spectral Enhanced Vegetation Index (EVI, using product MOD13Q1.006 from the MODIS sensor) from 2001 to 2018. The database contains, at the annual scale, a synthetic map of Ecosystem Functional Type (EFT) classes from three Ecosystem Functional Attributes (EFAs): (i) descriptors of annual primary production, (ii) seasonality, and (iii) phenology of carbon gains. It also includes two ecosystem functional-diversity indices derived from the above datasets: (i) EFT richness and (ii) EFT rarity. Finally, it provides interannual summaries for all previously mentioned variables, i.e., their long-term means and interannual variability. The datasets are available at two open-source sites (PANGAEA: https://doi.org/10.1594/PANGAEA.924792; Cazorla et al., 2020a; interannual summaries at http://obsnev.es/apps/efts_SN.html, last access: 17 April 2023). This dataset provides scientists, environmental managers, and the public in general with valuable information on the first characterization of ecosystem functional diversity based on primary production developed in the Sierra Nevada, a biodiversity hotspot in the Mediterranean basin and an exceptional natural laboratory for ecological research within the Long-Term Social-Ecological Research (LTER) network.

Effects of input data sources on species distribution model predictions across species with different distributional ranges

AbstractAimA major source of uncertainty in the application of species distribution models (SDMs) is related to input data quality. Citizen‐collected species occurrence data are often used for fitting SDMs when data from standardized and expert‐supported surveys are unavailable. Macroclimate variables are much more commonly used as predictors in SDMs than other sources coming from remote sensing data. Here, we assess the effects of using different data sources (in both response and predictor variables) on SDM performance across a wide range of species with contrasting distributional ranges.LocationIberian Peninsula.TaxonBirds.MethodsA SDM ensemble‐forecasting approach was implemented using bird data from two different data sources: the eBird project and Atlases. We fitted SDMs with three predictor types: macroclimate, remotely sensed ecosystem functional attributes (EFAs) and their combination. Species were grouped in four range size classes. We assessed the uncertainty of model predictions by different evaluation metrics. Generalized linear mixed‐effects models tested the effect on model performance of input data source across distributional range sizes while accounting for different accuracy metrics. Pairwise comparisons between range projections were used to assess their spatial similarity.ResultsData source, size class, predictor and accuracy metric showed significant effects on SDM performance. eBird‐based models outperformed those built with Atlas data for less widespread species. Climate predictors yielded models with the best performance, especially when combined with EFAs. However, the predictor contribution was consistent across bird datasets, being mostly driven by the species range.Main ConclusionsOur models demonstrated the usefulness and complementarity of different input data sources when modelling species distribution across different distributional ranges. These findings highlight the need to integrate different data sources to improve the model predictions at regional scale. Our framework also underlines that model uncertainty should be examined more exhaustively at early stages of the modelling process.

Ecological mechanisms underlying aridity thresholds in global drylands

Abstract With ongoing climate change, the probability of crossing environmental thresholds promoting abrupt changes in ecosystem structure and functioning is higher than ever. In drylands (areas where it rains <65% of what could be potentially evaporated), recent research has shown how the crossing of three aridity thresholds [at aridity (1‐Aridity Index) values of 0.54, 0.70 and 0.80] leads to abrupt changes on ecosystem structural and functional attributes. Despite the importance of these findings and their implications to develop effective monitoring and adaptation actions to combat climate change and desertification, we lack a proper understanding of the mechanisms unleashing these abrupt shifts. Here we review multiple mechanisms that may explain the existence of aridity thresholds observed across global drylands, and discuss the potential amplification mechanisms that may underpin hypothetical abrupt temporal shifts with climate change. We propose that each aridity threshold is caused by different and specific mechanisms. The first threshold is mainly caused by physiological mechanisms of plant adaptation to water shortages. The second threshold is unleashed by different mechanisms involving soil processes and plant–soil interactions such as soil erosion, plant community shifts and nutrient cycling and circulation. The collapse of vegetation observed once the third aridity threshold (0.8) is crossed is caused by the mechanisms related to the survival limits of plants that may cause sudden cover and diversity losses and plant–atmospheric feedbacks that link vegetation collapse with further climate aridification. By identifying, revising and linking relevant mechanisms to each aridity threshold observed, we provide a set of specific hypotheses and identify knowledge gaps concerning the study of threshold emergence in drylands. We were also able to establish plausible factors that are context dependent and may influence the occurrence of abrupt ecosystem changes in time. Our review may help to focus future research efforts on aridity thresholds and to develop strategies to monitor, adapt to or even revert abrupt ecosystem changes across global drylands. A free Plain Language Summary can be found within the Supporting Information of this article.

Ecosystem Functioning Influences Species Fitness at Upper Trophic Levels

Global change is severely affecting ecosystem functioning and biodiversity globally. Remotely sensed ecosystem functional attributes (EFAs) are integrative descriptors of the environmental change—being closely related to the processes directly affecting food chains via trophic cascades. Here we tested if EFAs can explain the species fitness at upper trophic levels. We took advantage of a long-term time series database of the reproductive success of the Golden Eagle (Aquila chrysaetos)—an apex predator at the upper trophic level—over a 17-year period across a bioclimatic gradient (NW Spain; c. 29,575 km2). We computed a comprehensive database of EFAs from three MODIS satellite-products related to the carbon cycle, heat dynamics and radiative balance. We also assessed possible time-lag in the response of the Golden Eagle to fire, a critical disruptor of the surface energy budget in our region. We explored the role of EFAs on the fitness of the Golden Eagle with logistic-exposure nest survival models. Our models showed that the reproductive performance of the Golden Eagle is influenced by spatiotemporal variations in land surface temperature, albedo and vegetation productivity (AUC values from 0.71 to 0.8; ΣWi EFAs from 0.66 to 1). Fire disturbance also affected ecological fitness of this apex predator—with a limited effect at 3 years after fire (a time-lagged response to surface energy budget disruptions; ΣWi Fire = 0.62). Our study provides evidence for the influence of the matter and energy fluxes between land surface and atmosphere on the reproductive success of species at upper trophic levels.

Cascading effects of N fertilization activate biologically driven mechanisms promoting P availability in a semi‐arid grassland ecosystem

Abstract Nitrogen (N) fertilization due to N deposition, N in manure from grazing livestock and direct input to soil by humans are impacting our terrestrial ecosystems globally. However, to date, our understanding of how artificial gradients of N fertilization indirectly affect phosphorus (P) availability by altering the rates and interrelationships of multiple structural and functional attributes of terrestrial ecosystems is still limited. Here, we conducted a 3‐year field experiment to evaluate the direct and indirect effects of multiple level of N addition on a wide range of ecosystem structural and functional attributes associated with >20 plant, soil and microbial variables in a semi‐arid grassland. We found that N fertilization can have multiple cascading effects on ecosystem structures and functions. These cascading events ultimately result in the activation of multiple biologically driven mechanisms to promote P availability (e.g. increased soil organic P mineralization, plant phosphorus resorption, enzymatic and genetic processes of phosphatase). The increasing phosphatase production and its functional gene expression, and decreasing plant and microbial biomass might imply important shifts in the carbon‐use strategies of plants and microbes allocating more resources to high‐C consuming enzymatic and genetic processes and less in plant and microbial biomass. Nitrogen addition decreases fungal community biomass which suggests the decoupling of key symbiotic plant–fungal relationships for nutrient acquirement. Overall, our study advances our understanding of how and why N fertilization simultaneously influences multiple structural and functional attributes, ultimately accelerating phosphorus cycle in terrestrial ecosystems.

Incorporating Ecosystem Functional Diversity into Geographic Conservation Priorities Using Remotely Sensed Ecosystem Functional Types

Conservation biology must set geographic conservation priorities not only based on the compositional or structural but also on the functional dimensions of biodiversity. However, assessing functional diversity is challenging at the regional scale. We propose the use of satellite-derived Ecosystem Functional Types (EFTs), defined here as patches of land surface that share similar primary production dynamics, to incorporate such aspects of ecosystem functional diversity into the selection of protected areas. We applied the EFT approach to the Baja California Peninsula, Mexico, to characterize the regional heterogeneity of primary production dynamics in terms of EFTs; to set conservation priorities based on EFT richness and rarity; and to explore whether such EFT-based conservation priorities were consistent with and/or complementary to previous assessments focused on biodiversity composition and structure. EFTs were identified based on three ecosystem functional attributes derived from seasonal dynamics of the Enhanced Vegetation Index: the annual mean (proxy of primary production), the seasonal coefficient of variation (descriptor of seasonality), and the date of maximum (indicator of phenology). EFT-based priorities identified 26% of the peninsula as being of extreme or high priority and reinforced the value of the ecosystem functional diversity of areas already prioritized by traditional conservation assessments. In addition, our study revealed that biodiversity composition- and structure-based assessments had not identified the full range of important areas for EFT diversity and tended to better capture areas of high EFT rarity than those of high EFT richness. Our EFT-based assessment demonstrates how remotely sensed regional heterogeneity in ecosystem functions could reinforce and complement traditional conservation priority setting.

Thresholds of aridity

Dryland Ecology Increasing aridity due to climate change is expected to affect multiple ecosystem structural and functional attributes in global drylands, which cover ∼45% of the terrestrial globe. Berdugo et al. show that increasing aridity promotes thresholds on the structure and functioning of drylands (see the Perspective by Hirota and Oliveira). Their database includes 20 variables summarizing multiple aspects and levels of ecological organization. They found evidence for a series of abrupt ecological events occurring sequentially in three phases, culminating with a shift to low-cover ecosystems that are nutrient- and species-poor at high aridity values. They estimate that more than 20% of land surface will cross at least one of the thresholds by 2100, which can potentially lead to widespread land degradation and desertification worldwide. Science , this issue p. [787][1]; see also p. [739][2] [1]: /lookup/doi/10.1126/science.aay5958 [2]: /lookup/doi/10.1126/science.aba7115

Mapping Regional Ecosystem Functional Types Based on Sentinel-2 Satellite Imagery

Ecosystem functional types (EFTs) are the patches of land surface showing similar in carbon dynamics. EFTs are not defined by the structure and composition of vegetation and represent the spatial heterogeneity of ecosystem functions. Identifying EFTs based on low-resolution satellite remote sensing data cannot satisfy the needs of fine-scale characterization of regional ecosystem functional patterns. Here, taking Zhenlai County, Northeast China as an example, the heterogeneity in ecosystem functions was characterized by identifying EFTs from Sentinel-2 time series data using ISODATA algorithm. Ecosystem functional attributes derived from dynamics of the normalized difference vegetation index (NDVI), the fraction of absorbed photosynthetically active radiation (FAPAR), and canopy water content (CWC) in the growing season were calculated. The correspondence analysis (CA) method was used to reveal relationships between the EFTs and land cover types. Our results showed that the nine selected remotely sensed variables indicating carbon and water flux of the regional ecosystems could be adopted in ecosystem functions classification. The obtained EFTs based on Sentinel-2 images reflected the internal structure of carbon balance well and the distribution pattern of ecosystem functional diversity a fine scale. This study helps to understand the functional heterogeneity pattern of temperate terrestrial ecosystems.

Bayesian Harmonic Modelling of Sparse and Irregular Satellite Remote Sensing Time Series of Vegetation Indexes: A Story of Clouds and Fires

Vegetation index time series from Landsat and Sentinel-2 have great potential for following the dynamics of ecosystems and are the key to develop essential variables in the realm of biodiversity. Unfortunately, the removal of pixels covered mainly by clouds reduces the temporal resolution, producing irregularity in time series of satellite images. We propose a Bayesian approach based on a harmonic model, fitted on an annual base. To deal with data sparsity, we introduce hierarchical prior distribution that integrate information across the years. From the model, the mean and standard deviation of yearly Ecosystem Functional Attributes (i.e., mean, standard deviation, and peak’s day) plus the inter-year standard deviation are calculated. Accuracy is evaluated with a simulation that uses real cloud patterns found in the Peneda-Gêres National Park, Portugal. Sensitivity to the model’s abrupt change is evaluated against a record of multiple forest fires in the Bosco Difesa Grande Regional Park in Italy and in comparison with the BFAST software output. We evaluated the sensitivity in dealing with mixed patch of land cover by comparing yearly statistics from Landsat at 30m resolution, with a 2m resolution land cover of Murgia Alta National Park (Italy) using FAO Land Cover Classification System 2.

Effects of species traits and environmental predictors on performance and transferability of ecological niche models

The ability of ecological niche models (ENMs) to produce robust predictions for different time frames (i.e. temporal transferability) may be hindered by a lack of ecologically relevant predictors. Model performance may also be affected by species traits, which may reflect different responses to processes controlling species distribution. In this study, we tested four primary hypotheses involving the role of species traits and environmental predictors in ENM performance and transferability. We compared the predictive accuracy of ENMs based upon (1) climate, (2) land-use/cover (LULC) and (3) ecosystem functional attributes (EFAs), and (4) the combination of these factors for 27 bird species within and beyond the time frame of model calibration. The combination of these factors significantly increased both model performance and transferability, highlighting the need to integrate climate, LULC and EFAs to improve biodiversity projections. However, the overall model transferability was low (being only acceptable for less than 25% of species), even under a hierarchical modelling approach, which calls for great caution in the use of ENMs to predict bird distributions under global change scenarios. Our findings also indicate that positive effects of species traits on predictive accuracy within model calibration are not necessarily translated into higher temporal transferability.

Ecosystem Services in a Protected Mountain Range of Portugal: Satellite-Based Products for State and Trend Analysis

Mountains are facing strong environmental pressures, which may jeopardize the supply of various ecosystem services. For sustainable land management, ecosystem services and their supporting functions should thus be evaluated and monitored. Satellite products have been receiving growing attention for monitoring ecosystem functioning, mainly due to their increasing temporal and spatial resolutions. Here, we aim to illustrate the high potential of satellite products, combined with ancillary in situ and statistical data, to monitor the current state and trend of ecosystem services in the Peneda-Gerês National Park, a protected mountain range in Portugal located in a transition climatic zone (Atlantic to Mediterranean). We focused on three ecosystem services belonging to three broad categories: provisioning (reared animals), regulating (of water flows), and cultural (conservation of an endemic and iconic species). These services were evaluated using a set of different satellite products, namely grassland cover, soil moisture, and ecosystem functional attributes. In situ and statistical data were also used to compute final indicators of ecosystem services. We found a decline in the provision of reared animals since year 2000, although the area of grasslands had remained stable. The regulation of water flows had been maintained, and a strong relationship with interannual precipitation pattern was noted. In the same period, conservation of the focal iconic species might have been affected by interannual fluctuations of suitable habitat areas, with a possible influence of wildfires and precipitation. We conclude that satellite products can efficiently provide information about the current state and trend in the supply of various categories of ecosystem services, especially when combined with in situ or statistical data in robust modeling frameworks.

Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling.

Global environmental changes are rapidly affecting species’ distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species’ conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.

Mapa digital del perfil del carbono orgánico en los suelos de Andalucía, España

Armas, D., Guevara, M., Alcaraz-Segura, D., Vargas, R., Soriano-Luna, M.A., Durante, P., Oyonarte, C. 2017. Digital map of the organic carbon profile in the soils of Andalusia, Spain. Ecosistemas 26(3):80-88. Doi.: 10.7818/ECOS.2017.26-3.10 To know and understand the spatial distribution of soil organic carbon (SOC) is the first step for management of this important pool in the global carbon cycle, and to develop actions to address climate change. The objective of this work was to generate maps of percent SOC across Andalucia through the use of consistent models, quantifying the associated uncertainty and identify controls of the spatial variability. We used a legacy soil profile collection with 1500 soil profiles and 20 environmental covariates as prediction factors for climate, topography, and ecosystem functional attributes related to the dynamic of primary production. A combination of linear models and an ensemble of regression trees coupled with geostatistics was used to estimate the spatial distribution (horizontal and vertical) of SOC, maps of SOC distribution across six soil depths (0-5, 5-15, 15-30, 30-60, 60-100 y 100-200 cm). Explained variance of our models varied between 63 to 57 %, with high uncertainty at sites with the highest values of SOC (up to 8%). The variability of SOC corresponded to a complex interaction of factors, whereas precipitation is an outstanding predictive factor across all depths, annual primary production (EVI) at the superficial horizons, and topography across deep horizons. Generated maps result in a useful tool for environmental policy, because they facilitate the periodical update of SOC and provide information for the management of this pool.

Regional patterns of ecosystem functional diversity in the Argentina Pampas using MODIS time-series

The characterization of ecosystem functioning is significant for different purposes such as biodiversity conservation and ecosystem services. A key aspect of ecosystem functioning is carbon gains, since it represents the energy available for upper trophic levels. In this sense, remote-sensing methods have allowed the study of ecosystem dynamics and spatial distribution at different spatial and temporal scales. The objectives were to describe the regional patterns of ecosystem functional diversity and to establish the importance of interannual variability in the definition of Ecosystem Functional Types (EFTs) in the Argentina Pampas. EFTs were obtained from carbon gains using a set of seven functional attributes and their interannual variations, which were retrieved from 14-year NDVI time-series. An ISODATA technique was applied to all the analyzed variables, and the clusters that best separate in the n-dimensional space were selected using discriminant analysis. The Argentina Pampas shows a high heterogeneity in the spatial patterns of ecosystem functional attributes. The annual integral of NDVI (i-NDVI, a linear estimator of net primary productivity), a complex of ecosystem functional attributes that describe the interannual variability, and the annual relative range of NDVI (RREL, ecosystem seasonality) had the highest relevance to distinguish nine EFTs in the study area. This study shows a novel approach for mapping ecosystem functioning, which reveals the importance of interannual variations. This methodology includes the effects of climate variability on ecosystem dynamics, thus enhancing our understanding of ecosystem functional diversity. The results obtained represent a baseline scenario to evaluate the effects of both land use change and climate variability on ecosystem functioning from a temporal perspective.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts

In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001–2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.

Consequences of Cool-Season Drought-Induced Plant Mortality to Chihuahuan Desert Grassland Ecosystem and Soil Respiration Dynamics

Predicted reductions of cool-season rainfall may expand and accelerate drought-induced plant mortality currently unfolding across the Southwest US. To assess how repeated plant mortality affects ecosystem functional attributes, we quantified net ecosystem CO2 exchange (NEE), ecosystem respiration (Reco), and gross ecosystem photosynthesis (GEP) responses to precipitation (P) at a semidesert grassland over spring (Feb 1–Apr 30) and summer (June 15–Oct 1) plant-active periods across eight years, including two with distinct patterns of extensive species-specific mortality. In addition, we quantified daily soil respiration (Rsoil) in high- (56–88%) and low-mortality (8–27%) plots the summer following the most recent mortality event. Plant mortality coincided with severely dry cool-season conditions (Dec 1–Apr 30). We found a positive relationship between springtime P and GEP, and that springtime conditions influenced GEP response to summer rainfall. High springtime Reco/GEP ratios followed plant mortality, suggesting increased available carbon after mortality was rapidly decomposed. Rsoil in low-mortality plots exceeded high-mortality plots over drier summer periods, likely from more root respiration. However, total cumulative Rsoil did not differ between plots, as variation in surviving plant conditions resulted in high and low C-yielding plots within both plot types. Vegetation status in high C-yielding Rsoil plots was similar to that across the grassland, suggesting Rsoil from such areas underlay higher Reco. This, coupled to springtime drought constraints to GEP, resulted in positive NEE under summer P accumulations that previously supported C-sink activity. These findings indicate that predicted lower cool-season precipitation may strongly and negatively affect summer season productivity in these semiarid grasslands.

Ecosystem functional changes associated with land clearing in NW Argentina

We assessed the extension of natural habitat conversion into croplands and grazing lands in subtropical NW Argentina and its impact on two key ecosystem functional attributes. We quantified changes in remotely sensed surrogates of aboveground net primary production (ANPP) and seasonality of carbon gains. Both functional attributes are associated with intermediate ecosystem services sensuFisher et al. (2009). Deforestation was estimated based on photointerpretation of Landsat imagery. The seasonal dynamics of the MODIS satellite Enhanced Vegetation Index (EVI) was used to calculate the EVI annual mean as a surrogate of ANPP, and the EVI seasonal coefficient of variation as an indicator of seasonal variability of carbon gains. The 2000–2007 period showed a high rate of land clearing: 5.9% of NW Argentina (1,757,600ha) was cleared for agriculture and ranching, corresponding to an annual rate of 1.15%. Dry forests experienced the highest rate and humid forests the lowest. Though land clearing for agriculture and ranching had relatively small impacts on total annual ANPP, once deforested, parcels significantly became more seasonal than the natural vegetation replaced. Such increase in seasonality is associated with a reduction of photosynthetic activity during a portion of the year (fallow). Direct consequences of this reduction can be expected on several ecosystem services such as erosion control and water regulation, due to greater exposure of bare soil, and biodiversity, due to the loss or decline in habitat quality and the decrease of green biomass availability for primary consumers during fallow. Land clearing also increased the magnitude of inter-annual differences in C gains, suggesting a greater buffer capacity against climate fluctuations of natural vegetation compared to croplands.

Identifying Thresholds for Ecosystem-Based Management

BackgroundOne of the greatest obstacles to moving ecosystem-based management (EBM) from concept to practice is the lack of a systematic approach to defining ecosystem-level decision criteria, or reference points that trigger management action.Methodology/Principal FindingsTo assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds. A utility threshold is the level of human-induced pressure (e.g., pollution) at which small changes produce substantial improvements toward the EBM goal of protecting an ecosystem's structural (e.g., diversity) and functional (e.g., resilience) attributes. The analytical approach is based on the detection of nonlinearities in relationships between ecosystem attributes and pressures. We illustrate the method with a hypothetical case study of (1) fishing and (2) nearshore habitat pressure using an empirically-validated marine ecosystem model for British Columbia, Canada, and derive numerical threshold values in terms of the density of two empirically-tractable indicator groups, sablefish and jellyfish. We also describe how to incorporate uncertainty into the estimation of utility thresholds and highlight their value in the context of understanding EBM trade-offs.Conclusions/SignificanceFor any policy scenario, an understanding of utility thresholds provides insight into the amount and type of management intervention required to make significant progress toward improved ecosystem structure and function. The approach outlined in this paper can be applied in the context of single or multiple human-induced pressures, to any marine, freshwater, or terrestrial ecosystem, and should facilitate more effective management.

Are Functional Guilds More Realistic Management Units Than Individual Species for Restoration?1

Abstract Categorizing species according to their functional traits, such as spatial and temporal patterns of resource use, effects on ecosystems, and responses to environmental perturbations, can facilitate successful restoration of plant communities. Functional guilds condense species lists by grouping species according to similarities in characteristics we believe to be important in a particular context. These groupings can allow us to (1) ensure community and ecosystem structural and functional attributes, (2) increase competitiveness of the community to deter the establishment of undesirable species, (3) simplify and test models of community assembly including resistance to invasion, succession, and species coexistence, and (4) facilitate cross-site comparisons. As useful as functional guilds can be, we must not overlook the potentially important roles of individual species. In restoration, including multiple species that represent each functional type within a target community may provide a buffer ag...