A candidate vegetation index of biological integrity based on species dominance and habitat fidelity

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas of the USA and are used in some states to make critical management decisions. An underlying concept of all VIBIs is that they respond negatively to disturbance. The Ohio VIBI (OVIBI) is calculated from 10 metrics, which are different for each wetland vegetation class. We present a candidate vegetation index of biotic integrity based on floristic quality (VIBI-FQ) that requires only two metrics to calculate an overall score regardless of vegetation class. These metrics focus equally on the critical ecosystem elements of diversity and dominance as related to a species’ degree of fidelity to habitat requirements. The indices were highly correlated but varied among vegetation classes. Both indices responded negatively with a published index of wetland disturbance in 261 Ohio wetlands. Unlike VIBI-FQ, however, errors in classifying wetland vegetation may lead to errors in calculating OVIBI scores. This is especially critical when assessing the ecological condition of rapidly developing ecosystems typically associated with wetland restoration and creation projects. Compared to OVIBI, the VIBI-FQ requires less field work, is much simpler to calculate and interpret, and can potentially be applied to all habitat types. This candidate index, which has been “standardized” across habitats, would make it easier to prioritize funding because it would score the “best” and “worst” of all habitats appropriately and allow for objective comparison across different vegetation classes.     

Moss and vascular plant indices in Ohio wetlands have similar environmental predictors

Mosses and vascular plants have been shown to be reliable indicators of wetland habitat delineation and environmental quality. Knowledge of the best ecological predictors of the quality of wetland moss and vascular plant communities may determine if similar management practices would simultaneously enhance both populations. We used Akaike's Information Criterion to identify models predicting a moss quality assessment index (MQAI) and a vascular plant index of biological integrity based on floristic quality (VIBI-FQ) from 27 emergent and 13 forested wetlands in Ohio, USA. The set of predictors included the six metrics from a wetlands disturbance index (ORAM) and two landscape development intensity indices (LDIs). The best single predictor of MQAI and one of the predictors of VIBI-FQ was an ORAM metric that assesses habitat alteration and disturbance within the wetland, such as mowing, grazing, and agricultural practices. However, the best single predictor of VIBI-FQ was an ORAM metric that assessed wetland vascular plant communities, interspersion, and microtopography. LDIs better predicted MQAI than VIBI-FQ, suggesting that mosses may either respond more rapidly to, or recover more slowly from, anthropogenic disturbance in the surrounding landscape than vascular plants. These results supported previous predictive studies on amphibian indices and metrics and a separate vegetation index, indicating that similar wetland management practices may result in qualitatively the same ecological response for three vastly different wetland biological communities (amphibians, vascular plants, and mosses).     

Effect of time on consistent and repeatable macrophyte index for wetland condition

The vegetation portion of the Florida Wetland Condition Index (FWCI), an index of biological integrity, provided consistent and repeatable measures of condition at eighteen wetlands sampled in two consecutive growing seasons. The sample wetlands reflected a gradient of adjacent land use from non-impacted reference areas to wetlands imbedded within silviculture, cattle pasture and residential areas. Wetlands were described as herbaceous depression (n = 6), forested depression (n = 5) and forested strand or floodplain wetlands (n = 7), and represented different states of succession. Even though the wetlands were unique from one another and occurred across a large geographic area in Florida, the FWCI results calculated for all the wetlands were representative of adjacent land use impacts and not sensitive to natural variation. During the duration of this study, changes in weather from drought to tropical storm conditions, as well as management activities such as fire and herbivory, impacted wetlands. These effects were apparent in the change of species composition between sampling periods; 23–56% of species were different when resampled. Even though composition changed, the proportion of indicators remained consistent. The resulting condition scores suggested a one-to-one relationship between sampling periods.     

适应白洋淀湿地健康评价的IBI方法

IBI指数法是美国湿地生态系统健康评价的常用方法之一,在国内应用较少,目前为止只有少数学者尝试了底栖动物完整性指数(B-IBI)和鱼类完整性指数进行河流生态系统健康评价。试图建立适合白洋淀地区的生物完整性指数湿地健康状况评价的方法。在白洋淀的23个淀区进行土壤、水体、植物的实地调查与采样分析。根据已有研究所选择的植物属性,选择了30个植物属性作为备选参数。通过考察备选参数与人类干扰的相关性,最后确定了9个对人类干扰敏感的IBI参数。通过分析,建立了适合白洋淀湿地健康评价的标准:IBI,35-45,好;27-34,一般;19-26,差;＜18,极差。评价结果表明,白洋淀23个淀区中,6个健康状况好,5个一般,7个差,5个很差。     

Temporal stability of vegetation indicators of wetland condition

Vegetation indices are widely employed to evaluate wetland ecological condition, and are expected to provide sensitive and specific detection of environmental change. Most studies evaluate the performance of condition assessment metrics in the context of the data used to calibrate them. Here we examined the temporal stability of the Florida Wetland Condition Index (FWCI) for vegetation of depressional forested wetlands by resampling sites in 2008 that were previously sampled to develop the FWCI in 2001. Our objective was to determine if FWCI, a composite of six vegetation-based metrics, provides a robust measure of condition given inter-annual variation in environmental conditions (i.e., rainfall) between sampling periods. To that end, we sampled 22 geographically isolated wetlands in north Florida that spanned a wide land use/land cover intensity gradient. Our results suggested the FWCI is robust. We observed no significant paired difference in FWCI across or within land use categories, and the relationship between FWCI in 2001 and 2008 was strong (r² = 0.88, p < 0.001). This was despite surprisingly high composition change. Mean Jaccard community similarity within sites between years was 0.30, suggesting that most of the herbaceous taxa were replaced, possibly because of different antecedent rainfall conditions or sampling during different phenological periods; both are contingencies to which condition indices must be robust. We did observe some evidence of convergence toward the mean in 2008, with the fitted slope relating 2001 and 2008 FWCI scores significantly below one (0.63, 95% CI = 0.53–0.73). The most variable FWCI component metric was the proportional representation of obligate wetland taxa, suggesting that systematic changes may have been induced by different hydrologic conditions prior to sampling; notably, however, FWCI computed without this component still exhibited a slope significantly less than 1 (0.72, 95% CI = 0.61–0.88). Moreover, there was evidence that species lost from reference sites (higher condition) were replaced by taxa of lower floristic quality, while species lost from agricultural sites (consistently the lowest condition land use category) were replaced by species of higher quality. A significant positive association between FWCI and the ratio of coefficients of conservatism (CC) of species lost to those gained suggests some overfitting in FWCI development. However, despite modest evidence of overfitting, FWCI provides temporally consistent estimates of wetland condition, even under conditions of substantial taxonomic turnover.     

Mosses in Ohio wetlands respond to indices of disturbance and vascular plant integrity

We examined the relationships between an index of wetland habitat quality and disturbance (ORAM score) and an index of vascular plant integrity (VIBI-FQ score) with moss species richness and a moss quality assessment index (MQAI) in 45 wetlands in three vegetation types in Ohio, USA. Species richness of mosses and MQAI were positively associated with ORAM and VIBI-FQ scores. VIBI-FQ score was a better predictor of both moss species richness and MQAI than was either ORAM score or vegetation type. This result was consistent with the strict microhabitat requirements for many moss species, which may be better assessed by VIBI-FQ than ORAM. Probability curves as a function of VIBI-FQ score were then generated for presence of groups of moss species having the same degree of fidelity to substrate and plant communities relative to other species in the moss flora (coefficients of conservatism, CCs). Species having an intermediate- or high degree of fidelity to substrate and plant communities (i.e., species with CC ≥ 5) had a 50% probability of presence (P₅₀) and 90% probability of presence (P₉₀) in wetlands with intermediate- and high VIBI-FQ scores, respectively. Although moss species richness, probability of presence of species based on CC, and MQAI may reflect wetland habitat quality, the 95% confidence intervals around P₅₀ and P₉₀ values may be too wide for regulatory use. Moss species richness, MQAI, and presence of groups of mosses may be more useful for evaluating moss habitat quality in wetlands than a set of “indicator species.”     

Comparing disturbance gradients and bird-based indices of biotic integrity for ranking the ecological integrity of Great Lakes coastal wetlands

We compared different methods for generating indices of biotic integrity (IBIs) for Great Lakes coastal wetlands using bird community data collected by participants in Bird Studies Canada's Great Lakes Marsh Monitoring Program (GLMMP) including: rank sum and multivariate approaches for defining landscape disturbance gradients; and generalist-specialist (IBI-1), multimetric (IBI-2), and probabilistic (IBI-3) approaches for calculating IBIs. Scores from the multivariate disturbance gradient, IBI-1, and IBI-3 increased rapidly at the impaired and unimpaired ends of the impaired-to-unimpaired spectrum, whereas scores from the rank sum disturbance gradient and IBI-2 increased rapidly only at the unimpaired end. IBIs with metrics that both increased and decreased along the landscape disturbance gradient were more sensitive for identifying especially impaired and unimpaired sites (i.e., IBI-1 and IBI-3) compared to IBIs with metrics that only increased (i.e., IBI-2). Scores from all but one of the IBIs were significantly correlated with scores of at least one of the landscape disturbance gradients and scores from all three of the IBIs were significantly moderately correlated with each other (r_s = 0.3–0.7). Site ranks arranged from impaired to unimpaired differed by 25–50 positions out of 142 possible positions depending on the pair of IBIs chosen. Much of the variation that we observed could be explained by differences among IBIs in the metrics that contributed most to impaired and unimpaired sites. Thus, we recommend the following not only for IBI users assessing the integrity of Great Lakes coastal wetlands, but also any other ecosystem where multiple landscape disturbance gradients and IBIs are available for use: (1) use multivariate instead of rank sum approaches for defining landscape disturbance gradients; (2) use IBIs with metrics that both increase and decrease along the landscape disturbance gradient instead of IBIs with metrics that only increase or only decrease; and (3) ensure that site-level species lists are reasonably complete, particularly for species that disproportionately contribute to especially impaired and unimpaired scores. Following these guidelines will increase the sensitivity and accuracy of IBIs for identifying especially impaired and unimpaired sites and ultimately result in better conservation.     

Wetland habitat disturbance best predicts metrics of an amphibian index of biotic integrity

Regression and classification trees were used to identify the best predictors of the five component metrics of the Ohio Amphibian Index of Biotic Integrity (AmphIBI) in 54 wetlands in Ohio, USA. Of the 17 wetland- and surrounding landscape-scale variables considered, the best predictor for all AmphIBI metrics was habitat alteration and development within the wetland. The results were qualitatively similar to the best predictors for a wetland vegetation index of biotic integrity, suggesting that similar management practices (e.g., reducing or eliminating nutrient enrichment from agriculture, mowing, grazing, logging, and removing down woody debris) within the boundaries of the wetland can be applied to effectively increase the quality of wetland vegetation and amphibian communities.     

Development issues in extending plant-based IBIs to forested wetlands in the Midwestern United States

Most plant-based indices of biotic integrity (IBIs) developed for wetlands have focused on emergent wetlands. A Vegetation Index of Biotic Integrity (VIBI-Forest) was developed for forested wetlands in the four large ecoregions of the Ohio. Assessing the effect of human disturbance on the ecological condition of wetland forests is complicated by several factors. First, forest canopies can remain largely intact even after significant degradation of the herb and shrub stratum. Second, increases in total diversity may not be good. In forested wetlands, a major artifact of disturbance is the addition of non-wetland or wetland native or adventive plant species adapted to full sun conditions to their floras. Initial versions of the VIBI-Forest metrics were very sensitive to disturbance-induced increases in diversity. Correcting this problem required modifying or replacing metrics so that only forest dependent species were included in metric calculations. The final VIBI-Forest included metrics which evaluated each forest stratum including the ground layer (% bryophyte), herb layer (shade or seed-less vascular plant species), shrub layer (subcanopy importance value (IV), relative density of young trees), canopy (canopy IV), and composite metrics for all vertical strata (Floristic Quality Assessment Index score, % hydrophytes, % sensitive, % tolerant). Assessing wetland forest condition is further complicated by the fact that some successional communities after canopy death or destruction (shrub swamp, marsh, wet meadow) may have intrinsic value as wetland community types. The solution is not to attempt to derive a one-size-fits-all assessment method but to derive separate protocols for other successional phases that are of value or interest.     

Transferability of bioassessment indices among water body types and ecoregions: A California experiment in wetland assessment

Biological assessment of aquatic resources requires the availability of bioassessment tools that work in all waterbody types and regions of interest. Developing new assessment tools may require several years of data collection and substantial investment of resources, which may not be an option for some aquatic resource managers. Adapting tools developed for different regions or wetland types may be an attractive alternative to developing new indices, provided they work well in the novel setting. In this study, we explore the transferability of two bioassessment indices for application to depressional wetlands in California, which are wetland type of management concern but for which bioassessment tools don’t currently exist. We tested the applicability of a depressional wetland invertebrate index of biotic integrity (IBI) developed in the San Francisco Bay region of northern California for application in the drier regions of southern California (i.e. geographic transferability), and the ability to apply a riverine benthic diatom IBI to benthic diatoms in depressional wetlands (i.e. water body type transferability). We evaluated the accuracy and responsiveness of the existing Indices for use in depressional wetlands and refined reference definitions and recalibrated thresholds relative to stressor gradients to maximize index performance. Performance of the adapted indices was compared to that of an existing habitat assessment tool (the California Rapid Assessment Method; CRAM) that has been developed for statewide application of depressional wetlands. Finally, we demonstrate application of the revised indices for ambient assessment of depressional wetland condition in southern California. Recalibrating both the macroinvertebrate and diatom indices to reference thresholds based on nutrient concentrations resulted in lower coefficient of variation among reference sites, greater differentiation between reference and non-reference and stronger relationship with stressors than when reference thresholds were based on landscape disturbance. Overall, the simple adjustment of the reference definition allowed us to transfer the indices with no structural changes to the metrics. This approach can facilitate future index adaptations that allow practitioners to include waterbody types for which there is no current index into routine biomonitoring programs.     

Transferable species distribution modelling: Comparative performance of Generalised Functional Response models

Predictive species distribution models (SDMs) are becoming increasingly important in ecology, in the light of rapid environmental change. However, the predictions of most current SDMs are specific to the habitat composition of the environments in which they were fitted. This may limit SDM predictive power because species may respond differently to a given habitat depending on the availability of all habitats in their environment, a phenomenon known as a functional response in resource selection. The Generalised Functional Response (GFR) framework captures this dependence by formulating the SDM coefficients as functions of habitat availability. The original GFR implementation used global polynomial functions of habitat availability to describe the functional responses. In this study, we develop several refinements of this approach and compare their predictive performance using two simulated and two real datasets. We first use local radial basis functions (RBF), a more flexible approach than global polynomials, to represent the habitat selection coefficients, and balance bias with precision via regularization to prevent overfitting. Second, we use the RBF-GFR and GFR models in combination with the classification and regression tree CART, which has more flexibility and better predictive powers for non-linear modelling. As further extensions, we use random forests (RFs) and extreme gradient boosting (XGBoost), ensemble approaches that consistently lead to variance reduction in generalization error. We find that the different methods are ranked consistently across the datasets for out-of-data prediction. The traditional stationary approach to SDMs and the GFR model consistently perform at the bottom of the ranking (simple SDMs underfit, and polynomial GFRs overfit the data). The best methods in our list provide non-negligible improvements in predictive performance, in some cases taking the out-of-sample R2 from 0.3 up to 0.7 across datasets. At times of rapid environmental change and spatial non-stationarity ignoring the effects of functional responses on SDMs, results in two different types of prediction bias (under-prediction or mis-positioning of distribution hotspots). However, not all functional response models perform equally well. The more volatile polynomial GFR models can generate biases through over-prediction. Our results indicate that there are consistently robust GFR approaches that achieve impressive gains in transferability across very different datasets.     

生物完整性指数与水生态系统健康评价

生物完整性指数是目前水生态系统健康评价中应用最广泛的一个生态指标。本文扼要介绍了生物完整性指数的概念、水生态系统健康评价的原理以及大型底栖无脊椎动物完整性指数的构建方法,介绍了生物完整性指数在水生态系统健康评价中的应用及我国开展这方面工作的建议。     

长江中游浅水湖泊生物完整性时空变化

介绍了采用 Karr提出、经 Fausch等修订后的生物完整性指数 (IBI)进行水环境质量评价的原理和概念 ,并根据长江中游鱼类种类组成特征、可获得数据的类型和资料的性质 ,初步建立了适合长江中游浅水湖泊的 IBI体系。同时 ,以基本保持了长江中游浅水湖泊自然属性的五湖 1978年的调查数据为参照 ,选择长江中游不同类型的浅水湖泊进行了生物完整性时空变化的比较研究。结果表明 :以洪湖为例进行纵向比较 ,在 196 4、1981、1993年和 1998年等 4个不同的年代 ,其生物完整性呈逐步下降的趋势 ;以 2 0世纪 90年代初期的资料进行横向比较 ,三湖连江水库和保安湖的生物完整性表现为一般 ,洪湖为差 ,东湖则很差。上述湖泊所呈现的生物完整性的时空变化趋势与其它相关研究所反映的湖泊水环境质量互为补充验证 ,可以为湖泊管理、持续发展和利用以及水环境保护提供更为充分的科学依据     

流域景观类型及配置对大型底栖动物完整性的影响

通过对滦河流域66个河段大型底栖动物采集和生境指标监测,基于大型底栖动物完整性评价和13种景观指数构建,探讨了不同景观指数对于大型底栖无脊椎动物完整性的解释能力。景观指数类型包括流域及欧式距离缓冲区土地利用百分比、水流路径缓冲区土地利用百分比、局部区域土地利用百分比和基于水流路径的反距离权重指数。基于多元线性逐步回归模型,根据调整R2(Square of the coefficient)来判断不同指数的解释能力。研究结果表明基于水流路径的反距离权重指数对于大型底栖动物完整性的解释能力最好,其次为基于水流路径的缓冲区和局部区域的土地利用百分比指数,全流域及欧氏距离缓冲区内土地利用百分比解释能力最差。农田是影响大型底栖动物完整性最重要的景观类型,距离河流越近的农田对大型底栖动物完整性的影响越大,因此流域及河岸带农田的控制和管理对于滦河流域大型底栖动物完整性的恢复具有重要的作用。     

Constructing multimetric indices and testing ability of landscape metrics to assess condition of freshwater wetlands in the Northeastern US

Using data collected for the Environmental Protection Agency's (EPA) 2011 National Wetland Condition Assessment (NWCA), we developed separate multimetric indices (MMIs) for vegetation, soil, algae taxa, and water to assess condition of freshwater wetlands in the northeastern US. This study represents the first attempt at developing multiple biotic and abiotic MMIs of wetland condition over this large of an area, and is only possible because of the high quality data collected by the NWCA. We chose metrics that distinguished between reference and most disturbed sites, had a signal:noise ratio > 2, and were not strongly correlated with other metrics, latitude, or longitude. The vegetation and soil MMIs were the best performing indices, with good separation between reference and most disturbed sites, and included commonly used condition metrics (e.g., pH and P concentration for soil, and percent cover of exotic species for vegetation). The algae MMI was the weakest index, with considerable overlap between reference and most disturbed sites. For areas smaller than our study, algae taxa may be suitable for wetland MMIs. However, in our study area, many algae taxa followed strong latitudinal or longitudinal gradients, and could not be considered for the algae MMI. Small sample size and several metrics with a high signal:noise ratio were the major limitations of the water MMI. We also examined how well landscape (level 1) and rapid assessment (level 2) metrics predicted MMIs using random forest regression. Agricultural land use surrounding wetlands was an important predictor for all four MMIs, although the soil, algae and water MMI models performed best when intensive (level 3) vegetation metrics were also included in the random forest regression models. Based on these results, we recommend wetland assessment programs employ a combination of landscape and rapid assessment monitoring at many sites, along with level 3 monitoring at a subset of sites. We developed these MMIs to evaluate freshwater wetland condition for a long-term monitoring program in Acadia National Park. These MMIs are also applicable to a range of wetland types covering 11 states in the northeastern United States and can be calculated using a downloadable spreadsheet that calculates and rates each MMI using raw metric values.     

渭河丰、枯水期底栖动物群落特征及综合健康评价

以渭河为研究范例,分别于丰水期(2011年10月)和枯水期(2012年4月)对渭河全流域范围内45个样点的底栖动物群落进行跟踪调查,并在此基础上应用丰、枯水期底栖动物生物完整性评价指数(B-IBI)对渭河流域水生态系统进行综合健康评价。结果表明,渭河流域底栖动物群落结构具有明显的空间异质性,枯水期底栖动物群落结构单一,物种数量、生物量和香农多样性明显少于丰水期,但单位密度差异不显著。综合健康评价结果表明,渭河上游、洛河中上游地区的健康状况较好,而渭河中下游、泾河全流域及洛河下游地区的健康状况较差。相关分析显示,渭河全流域范围内丰水期和枯水期底栖动物群落的B-IBI得分呈现明显的正相关性,表明在不同水文过程时期,渭河全流域大尺度范围内底栖动物群落的生物完整性特征较为一致。在河流丰、枯水期,底栖动物群落结构的变化趋势并对比分析了渭河流域不同区域水生态系统健康水平差异的原因。     

Improving biological indicators to better assess the condition of streams

Biological indicators of stream condition are in use by water resource managers worldwide. The State of Maryland and many other organizations that use Indices of Biotic Integrity (IBIs) must determine when and how to refine their IBIs so that better stream condition information is provided. With completion of the second statewide round in 2004, the Maryland Biological Stream Survey (MBSS) had collected data from 2500 stream sites, more than doubling the number of sites that were available for the original IBI development. This larger dataset provided an opportunity for the MBSS to address the following shortcomings in the original IBIs: (1) substantial disturbance apparent in some reference sites, (2) fish IBIs could not be applied to very small streams, (3) natural variability within IBIs (based on regions) resulted in some stream types (e.g., coldwater and blackwater streams) receiving lower IBI scores and (4) one IBI was not able to discriminate degradation as desired (i.e., Coastal Plain fish IBI). Therefore, development of new fish and benthic macroinvertebrate IBIs was undertaken to achieve the goals of: (1) increased confidence that the reference conditions are minimally disturbed, (2) including more natural variation (such as stream size) across the geographic regions and stream types of Maryland and (3) increased sensitivity of IBIs by using more classes (strata) and different metric combinations. New fish IBIs were developed for four geographical and stream type strata: Coastal Plain, Eastern Piedmont, warmwater Highlands and coldwater Highlands streams; new benthic macroinvertebrate IBIs were developed for three geographical strata: Coastal Plain, Eastern Piedmont and Highlands streams. The addition of one new fish IBI and one new benthic macroinvertebrate IBI partitioned natural variability into more homogeneous strata. At the same time, smaller streams (i.e., those draining catchments <300 ac), which constituted a greater proportion of streams (25%) sampled in Round Two (2000–2004) than Round One (1995–1997), because of the finer map scale, were included in the reference conditions used to develop the new IBIs. The resulting new IBIs have high classification efficiencies of 83–96% and are well balanced between Type I and Type II errors. By scoring coldwater streams, smaller streams and to some extent blackwater streams higher, the new IBIs improve on the original IBIs. Overall, the new IBIs provide better assessments of stream condition to support sound management decisions, without requiring substantial changes by cooperating stream assessment programs.     

Assessing the performance of NDVI as a proxy for plant biomass using non-linear models: a case study on the Kerguelen archipelago

Numerous ecological studies, including of the polar environment, are now using the remotely sensed normalized difference vegetation index (NDVI, e.g. PAL-NDVI or MODIS-NDVI) as a proxy of vegetation productivity rather than performing direct vegetation assessments. Even though previous data strongly suggested a saturation of NDVI at high biomass values, few studies have explicitly included this characteristic in the modelling process. Here, we developed a generalized non-linear model to explicitly model the relationship between temporal variations of NDVI (Pathfinder AVHRR Land 8 km dataset) and empirical field data. We illustrated our approach on the Kerguelen archipelago by using a green biomass index (point-intercept protocol) sampled at a small scale relative to PAL-NDVI data, and in presence of spatial (water) and temporal (cloud contamination, snow) heterogeneity, i.e. field conditions encountered in many ecological studies. We showed a strong relationship (r _pred.obs = 0.89 [0.77; 0.95]_95%) between this index and the seasonal component of NDVI time series (NDVI_comp). Despite the absence of lignified species in the stand, the NDVI_comp reached an asymptote (0.54 ± 0.05) for high values of green biomass index stressing the need to account for non-linearity when relating NDVI and plant measurements. We provided here a new methodological framework to standardize comparisons between studies assessing performance of NDVI as a proxy of vegetation data.

Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes

Assessing the spatial variability of ecosystem structure and functioning is an important step towards developing monitoring systems to detect changes in ecosystem attributes that could be linked to desertification processes in drylands. Methods based on ground-collected soil and plant indicators are being increasingly used for this aim, but they have limitations regarding the extent of the area that can be measured using them. Approaches based on remote sensing data can successfully assess large areas, but it is largely unknown how the different indices that can be derived from such data relate to ground-based indicators of ecosystem health. We tested whether we can predict ecosystem structure and functioning, as measured with a field methodology based on indicators of ecosystem functioning (the landscape function analysis, LFA), over a large area using spectral vegetation indices (VIs), and evaluated which VIs are the best predictors of these ecosystem attributes. For doing this, we assessed the relationship between vegetation attributes (cover and species richness), LFA indices (stability, infiltration and nutrient cycling) and nine VIs obtained from satellite images of the MODIS sensor in 194 sites located across the Patagonian steppe. We found that NDVI was the VI best predictor of ecosystem attributes. This VI showed a significant positive linear relationship with both vegetation basal cover (R² = 0.39) and plant species richness (R² = 0.31). NDVI was also significantly and linearly related to the infiltration and nutrient cycling indices (R² = 0.36 and 0.49, respectively), but the relationship with the stability index was weak (R² = 0.13). Our results indicate that VIs obtained from MODIS, and NDVI in particular, are a suitable tool for estimate the spatial variability of functional and structural ecosystem attributes in the Patagonian steppe at the regional scale.