Global Patterns of agricultural land-use intensity and vertebrate diversity

Article · August 2015with357 Reads
DOI: 10.1111/ddi.12359
Abstract
AimLand-use change is the single biggest cause of biodiversity loss. With a rising demand for resources, understanding how and where agriculture threatens biodiversity is of increasing importance. Agricultural expansion has received much attention, but where high agricultural land-use intensity (LUI) threatens biodiversity remains unclear. We address this knowledge gap with two main research questions: (1) Where do global patterns of LUI coincide with the spatial distribution of biodiversity? (2) Where are regions of potential conflict between different aspects of high LUI and high biodiversity?LocationGlobal.Methods We overlaid thirteen LUI metrics with endemism richness, a range size-weighted species richness indicator, for mammals, birds and amphibians. We then used local indicators of spatial association to delineate statistically significant (P < 0.05) areas of high and low LUI associated with biodiversity.ResultsPatterns of LUI are heterogeneously distributed in areas of high endemism richness, thus discouraging the use of a single metric to represent LUI. Many regions where high LUI and high endemism richness coincide, for example in South America, China and Eastern Africa, are not within currently recognized biodiversity hotspots. Regions of currently low LUI and high endemism richness, found in many parts of Mesoamerica, Eastern Africa and Southeast Asia, may be at risk as intensification accelerates.Main conclusionsWe provide a global view of the geographic patterns of LUI and its concordance with endemism richness, shedding light on regions where highly intensive agriculture and unique biodiversity coincide. Past assessments of land-use impacts on biodiversity have either disregarded LUI or included a single metric to measure it. This study demonstrates that such omission can substantially underestimate biodiversity threat. A wider spectrum of relevant LUI metrics needs to be considered when balancing agricultural production and biodiversity.
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    • Surprisingly, only few trade-off studies applied such methods so far (e.g.Delzeit et al., 2016), whereas promising applications in related topics can be found. In one of the few examples,Kehoe et al. (2015)used the Local Indicator of Spatial Association (LISA;Anselin, 1995) to quantify the relationship between thirteen indicators of agricultural land-use intensity and measures of biodiversity at a global scale. This analysis allowed identifying areas where the focus on a single provisioning ES (e.g.
    [Show abstract] [Hide abstract] ABSTRACT: Ecosystem services (ES), the benefits that humans obtain from nature, are of great importance for human well-being. The challenge of meeting the growing human demands for natural resources while sustaining essential ecosystem functions and resilience requires an in-depth understanding of the complex relationships between ES. These conflicting (‘trade-offs’) or synergistic (‘synergies’) relationships mean that changes in one ES can cause changes in other ES. By synthesizing the growing body of literature on ES relationships, we identified the following four main study objectives: (i) the identification and characterization of co-occurrences of ES, (ii) the identification of drivers that shape ES relationships, (iii) the exploration of biophysical constraints of landscapes and limitations to their multifunctionality, and (iv) the support of environmental planning, management and policy decisions. For each of these objectives we here describe the key concepts, including viewpoints of different disciplines, and highlight the major challenges that need to be addressed. We identified three cross-cutting themes being relevant to all four main types of studies. To help guiding researchers towards more systematic analyses of ES trade-offs and synergies, we conclude with an outlook on suggested future research priorities.
    Full-text · Article · Aug 2017
    • In terms of LUI metrics, we found diverse interactions with SARs both in predictive ability and relationship between high, medium and low LUI and species richness. This adds evidence to research suggesting that metrics of LUI have distinct global patterns (Kehoe, et al. 2015) and relationships with biodiversity (Alkemade, et al. 2012, Felton, et al. 2010, Yamaguchi and Blumwald 2005). Finally, we found that HANPP, our only overall metric of LUI, was the best predictor of species richness when compared to other LUI metrics.
    [Show abstract] [Hide abstract] ABSTRACT: Species-area relationships (SARs) provide an avenue to model patterns of species richness and have recently been shown to vary substantially across regions of different climate, vegetation, and land cover. Given that a large proportion of the globe has been converted to agriculture, and considering the large variety in agricultural management practices, a key question is whether global SARs vary across gradients of agricultural intensity. We developed SARs for mammals that account for geographic variation in biomes, land cover and a range of land-use intensity indicators representing inputs (e.g. fertilizer, irrigation), outputs (e.g. yields) and system-level measures of intensity (e.g. human appropriation of net primary productivity - HANPP). We systematically compared the resulting SARs in terms of their predictive ability. Our global SAR with a universal slope was significantly improved by the inclusion of any one of the three variable types: biomes, land cover, and land-use intensity. The latter, in the form of human appropriation of net primary productivity (HANPP), performed as well as biomes and land-cover in predicting species richness. Other land-use intensity indicators had a lower predictive ability. Our main finding that land-use intensity performs as well as biomes and land cover in predicting species richness emphasizes that human factors are on a par with environmental factors in predicting global patterns of biodiversity. While our broad-scale study cannot establish causality, human activity is known to drive species richness at a local scale, and our findings suggest that this may hold true at a global scale. The ability of land-use intensity to explain variation in SARs at a global scale had not previously been assessed. Our study suggests that the inclusion of land-use intensity in SAR models allows us to better predict and understand species richness patterns. This article is protected by copyright. All rights reserved.
    Full-text · Article · Aug 2016
    • Amphibians are an integral part of aquatic biota, at least in one developmental stage, and they are sensitive to any change in the environment not only at the species level but also according to the developmental stage. Several studies have demonstrated that these vertebrates can be used as valid indicator species for environmental monitoring (Brodeur et al. 2012; Kehoe et al. 2015 ). Nevertheless, in recent decades, amphibian populations have been reported to suffer a significant decline worldwide, a phenomenon in several cases committed to pollution of both natural and agricultural areas due to the use of pesticides (Mann et al. 2009; Wagner et al. 2014).
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    Full-text · Article · Jun 2016
    • One proposed solution to this problem is to increase the intensity and homogenization of agricultural and forestry landscapes (Robinson and Sutherland, 2002; Benton et al., 2003). Although landscape homogenization has the potential to increase crop yield and efficiency (Green et al., 2005), increased agricultural intensity is also irrefutably one of the main causes of biodiversity loss (Adger et al., 2002; Roulston and Goodell, 2011; Kehoe et al., 2015). As a result, within intensely managed, homogeneous agricultural landscapes, yields often increase at the expense of biodiversity.
    [Show abstract] [Hide abstract] ABSTRACT: Cotton is the most economically and culturally important fiber crop worldwide. Though cotton may potentially benefit from animal mediated pollination, it is unknown if the species is indeed pollen limited across agroecological landscapes. Our study had three objectives: (1) identify the land use attributes that impact wild pollinator abundance and diversity, (2) investigate the relationship between pollinator community composition and cotton pollen limitation and (3) determine the extent of direct and indirect effects of land use on pollinator community composition and pollination service. To address these objectives, we used a combination of pollinator community surveys, GIS analysis, and pollen limitation experiments across 12 cotton landscapes in South Texas. Overall, we found that pollinator community composition was closely related to the abundance of natural areas (250 m radius). We also found evidence of substantial cotton pollen limitation, as significantly larger bolls were produced with the addition of outcross pollen. Further, we reveal that pollen limitation was negatively correlated with pollinator abundance and richness. Path analysis confirmed the two direct effects of land use composition on pollinator community and pollinator community composition on pollen limitation. Overall, our results reveal potential for increased crop yields via wild pollinator-mediated fruit set, equivalent to more than $108/acre with a regional gain of over $1.1 million USD. Further, our research provides insight into the specific land management practices that support pollinator communities within cotton agroecosystems. Cotton landscapes that maintain natural areas promote wild pollinator abundance and diversity, and subsequently experience reduced pollination limitation and increased crop yields.
    Full-text · Article · Jun 2016
    • One component of land use that is currently missing from our downscaled maps is the intensity of anthropogenic use. The intensity of a particular land use can have major effects on the outcomes for local biodiversity (Klein et al. 2002; Kleijn et al. 2009; Newbold et al. 2013; Tuck et al. 2014; Kehoe et al. 2015) and the ability to divide our maps into different intensities would be a major improvement. Defining and mapping land-use intensity of multiple land-use classes, particularly at global extents, is challenging (Kuemmerle et al. 2013) and doing this well will require methodological advances on several fronts.
    [Show abstract] [Hide abstract] ABSTRACT: Land-use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land-use mapping. Assessments of land-use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land-use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land-use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km2) estimates of five land-use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio-realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine-grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land-use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio-realms produced global fine-grained layers from the 2005 time step of the Land-use Harmonization dataset. Coarse-scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R2: 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land-use layers improved discrimination of all five classes at PREDICTS sites (P < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R2 improvement of 0.12 compared with the Land-use Harmonization data. The downscaling method presented here produced the first global land-use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land-use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse-resolution data for other environmental variables.
    Full-text · Article · Mar 2016
    • We quantify changes of potential (assuming no human intervention) net primary production (NPP; i.e. annual biomass production by vegetation; [24] ) due to cropland conversion as a system level metric of land use intensity. NPP changes due to land use resemble the share of trophic energy that is available for other food webs and are thus indicative for biodiversity impacts [25][26][27][28]. In line with the definition by Erb et al [23] and Haberl et al [29] we use the potential NPP (NPP pot ) as a reference value for actual NPP (NPP act ).
    [Show abstract] [Hide abstract] ABSTRACT: Meeting expected surges in global biomass demand while protecting pristine ecosystems likely requires intensification of current croplands. Yet many uncertainties relate to the potentials for cropland intensification, mainly because conceptualizing and measuring land use intensity is intricate, particularly at the global scale. We present a spatially explicit analysis of global cropland use intensity, following an ecological energy flow perspective. We analyze (a) changes of net primary production (NPP) from the potential system (i.e. assuming undisturbed vegetation) to croplands around 2000 and relate these changes to (b) inputs of (N) fertilizer and irrigation and (c) to biomass outputs, allowing for a three dimensional focus on intensification. Globally the actual NPP of croplands, expressed as per cent of their potential NPP (NPPact%), amounts to 77%. A mix of socio-economic and natural factors explains the high spatial variation which ranges from 22.6% to 416.0% within the inner 95 percentiles. NPPact% is well below NPPpot in many developing, (Sub-) Tropical regions, while it massively surpasses NPPpot on irrigated drylands and in many industrialized temperate regions. The interrelations of NPP losses (i.e. the difference between NPPact and NPPpot), agricultural inputs and biomass harvest differ substantially between biogeographical regions. Maintaining NPPpot was particularly N-intensive in forest biomes, as compared to cropland in natural grassland biomes. However, much higher levels of biomass harvest occur in forest biomes. We show that fertilization loads correlate with NPPact% linearly, but the relation gets increasingly blurred beyond a level of 125 kgN ha−1. Thus, large potentials exist to improve N-efficiency at the global scale, as only 10% of global croplands are above this level. Reallocating surplus N could substantially reduce NPP losses by up to 80% below current levels and at the same time increase biomass harvest by almost 30%. However, we also show that eradicating NPP losses globally might not be feasible due to the high input costs and associated sustainability implications. Our analysis emphasizes the necessity to avoid mono-dimensional perspectives with respect to research on sustainable intensification pathways and the potential of integrated socio-ecological approaches for consistently contrasting environmental trade-offs and societal benefits of land use intensification.
    Full-text · Article · Jan 2016
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