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Rising competition for crop usage presents policy challenges exacerbated by poor understanding of where crops are harvested for various uses. Here we create high-resolution global maps showing where crops are harvested for seven broad use categories—food, feed, processing, export, industrial, seed and losses. Yields for food crops are low relative to other crop-use categories. It is unlikely, given current trends, that the minimum calorie requirement to eliminate projected food undernourishment by 2030 will be met through crops harvested for direct food consumption, although enough calories will be harvested across all usages. Sub-Saharan African nations will probably fall short of feeding their increased population and eliminating undernourishment in 2030, even if all harvested calories are used directly as food.

Estimating the distribution of phenotypes in populations and communities is central to many questions in ecology and evolutionary biology. These distributions can be characterized by their moments: the mean, variance, skewness, and kurtosis. Typically, these moments are calculated using a community-weighted approach (e.g. community-weighted mean) which ignores intraspecific variation. As an alternative, bootstrapping approaches can incorporate intraspecific variation to improve estimates, and also quantify uncertainty in the estimate. Here, we compare the performance of different approaches for estimating the moments of trait distributions across a variety of sampling scenarios, taxa, and datasets. We introduce the traitstrap R package to facilitate inferences of trait distributions via bootstrapping. Our results suggest that randomly sampling ~9 individuals per sampling unit and species, focusing on covering all species in the community, and analysing the data using nonparametric bootstrapping generally enables reliable inference on trait distributions, including the central moments, of communities.

Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability. Satellite measures of vegetation greenness, together with animal stocking data and key climatic factors, reveal interannual precipitation variability to be a significant constraint on global pasture productivity.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) shows promise for monitoring the productivity of global agricultural systems. SIF-based primary productivity metrics have demonstrated higher fidelity to large-scale patterns of crop productivity than reflectance-based vegetation indices when averaged across the growing season. In-season crop yield forecasting typically relies upon reflectance-based vegetation indices, raising the question of whether in-season monitoring could be improved by utilizing SIF. Here, we analyze patterns of US agricultural productivity from USDA surveys and their in-season relationships with coarse-resolution GOME-2 SIF, high-resolution downscaled SIF, SIF-based primary productivity metrics, MODIS NDVI, and MODIS GPP. We find that coarse-resolution SIF-based metrics and NDVI exhibit similar out-of-sample in-season (April–July and April–August) predictive ability, even when spatially filtering higher-resolution NDVI data to cropland areas. The downscaled SIF product performed more poorly than the coarse-resolution SIF, and MODIS GPP performed more poorly than MODIS NDVI. All forecasts are improved by incorporating county fixed effects to control for cross-sectional differences between counties. NDVI-based metrics allow for significantly better yield predictions during drought conditions than SIF-based metrics, suggesting limited added value of SIF for early warning of drought impacts. The benefits of SIF for crop monitoring should be continually evaluated as the frequency and quality of SIF measurements continue to improve.

The inverse relationship between size and abundance is a well‐documented pattern in forests, and the form of size–density relationships depends on the balance between growth and mortality rates in the community. Traditionally, studies of plant size distributions have focused on single‐species populations and forests, but here we examine diverse communities dominated by plants with varied life histories, including grasses, forbs, shrubs, and succulents. In particular, we test whether the parameters of the individual size distribution differ systematically across community types, whether they fit the contrasting predictions of metabolic or demographic theories, and whether they share a common cross‐community scaling relationship with forest communities and crop populations. All thirteen of our study sites better fit the predictions of demographic equilibrium theory, but interestingly, fits of both demographic and metabolic models showed little systematic variation across community types, despite large differences in environmental conditions and dominant life forms. Finally, analysis of the cross‐community scaling relationship demonstrates that natural and restored non‐forest communities conform to patterns of size and abundance observed among forest, plantation, and crop systems. Taken together, our results suggest that common ecological mechanisms govern plant community size structure across broad environmental gradients, regardless of the dominant plant life forms or limiting resources.

Many studies have estimated the adverse effects of climate change on crop yields, however, this literature almost universally assumes a constant geographic distribution of crops in the future. Movement of growing areas to limit exposure to adverse climate conditions has been discussed as a theoretical adaptive response but has not previously been quantified or demonstrated at a global scale. Here, we assess how changes in rainfed crop area have already mediated growing season temperature trends for rainfed maize, wheat, rice, and soybean using spatially-explicit climate and crop area data from 1973 to 2012. Our results suggest that the most damaging impacts of warming on rainfed maize, wheat, and rice have been substantially moderated by the migration of these crops over time and the expansion of irrigation. However, continued migration may incur substantial environmental costs and will depend on socio-economic and political factors in addition to land suitability and climate., Extreme high temperature events are increasing in frequency and severity, threatening the capacity for crops and farmers alike to adapt. Here Sloat and colleagues track the movement of cereal crops over the past 40 years, finding a global migration away from warming climates.

Rangelands are one of the Earth’s major ice-free land cover types. They provide food and support livelihoods for millions of people in addition to delivering important ecosystems services. However, rangelands are at threat from climate change, although the extent and magnitude of the potential impacts are poorly understood. Any declines in vegetation biomass and fluctuations in grazing availability would be of concern for food production and ecosystem integrity and functionality. In this study, we use a global rangeland model in combination with livestock and socio-economic datasets to identify where and to what extent rangeland systems may be at climatic risk. Overall, mean herbaceous biomass is projected to decrease across global rangelands between 2000 and 2050 under RCP 8.5 (−4.7%), while inter- (year-to-year) and intra- (month-to-month) annual variabilities are projected to increase (+21.3% and +8.2%, respectively). These averaged global estimates mask large spatial heterogeneities, with 74% of global rangeland area projected to experience a decline in mean biomass, 64% an increase in inter-annual variability and 54% an increase in intra-annual variability. Half of global rangeland areas are projected to experience simultaneously a decrease in mean biomass and an increase in inter-annual variability—vegetation trends both potentially harmful for livestock production. These regions include notably the Sahel, Australia, Mongolia, China, Uzbekistan and Turkmenistan and support 376 million people and 174 million ruminant Tropical Livestock Units. Additionally, the rangeland communities currently the most vulnerable (here, with the lowest livestock productivities and economic development levels and with the highest projected increases in human population densities) are projected to also experience the most damaging vegetation trends for livestock production. Although the capacity of rangeland systems to adapt is highly complex, analyses such as these generate some of the information required to inform options to facilitate pastoral system mitigation and adaptation strategies under climate change.

Climate in subalpine meadows of the Rocky Mountains can be characterized by an early (foresummer) drought that occurs after snowmelt (May) and lasts until the start of the summer monsoon season (July). Climate change models predict an increase in the length and severity of this dry period due to earlier snowmelt dates, rising air temperatures, and shifts in the start and/or intensity of the North American monsoon. However, it is unknown how changes in the severity of this early season dry period will affect ecosystem carbon exchange. To address the importance of early season drought, we combined a watering manipulation with 11 years of ecosystem carbon exchange data across an elevational gradient at the Rocky Mountain Biological Laboratory in Gothic, Colorado. Long-term trends reveal that earlier snowmelt dates lead to a decrease in net ecosystem productivity (NEP), in part because of the positive effect on early growing season drought conditions. Manipulating the strength of the foresummer drought by watering revealed that the timing of growing season precipitation is more important than the total amount for determining cumulative NEP. The strength of the foresummer drought did not significantly impact ecosystem respiration rates, but plants that experienced a strong foresummer drought exhibited more water stress, and lower instantaneous rates of NEP, even during the rainy season. Our results highlight the central role of the foresummer drought in determining rates of carbon exchange throughout the growing season, and the potential for an increasingly negative balance of carbon in subalpine meadows under future climate change.

 Premise of the study: Darwin fi rst proposed that species with larger ecological breadth have greater phenotypic variation. We tested this hypothesis by comparing intraspecifi c variation in specifi c leaf area (SLA) to species’ local elevational range and by assessing how external (abiotic) fi lters may infl uence observed differences in ecological breadth among species. Understanding the patterns of individual variation within and between populations will help evaluate differing hypotheses for structuring of communities and distribution of species.  Methods: We selected 21 species with varying elevational ranges and compared the coeffi cient of variation of SLA for each species against its local elevational range. We examined the infl uence of external fi lters on local trait composition by determining if intraspecifi c changes in SLA with elevation have the same direction and similar rates of change as the change in community mean SLA value.  Key results: In support of Darwin’s hypothesis, we found a positive relationship between species’ coeffi cient of variation for SLA with species’ local elevational range. Intraspecifi c changes in SLA had the same sign, but generally lower magnitude than the community mean SLA.  Conclusions: The results indicate that wide-ranging species are indeed characterized by greater intraspecifi c variation and that species’ phenotypes shift along environmental gradients in the same direction as the community phenotypes. However, across species, the rate of intraspecifi c trait change, refl ecting plastic and/or adaptive changes across populations, is limited and prevents species from adjusting to environmental gradients as quickly as interspecifi c changes resulting from community assembly.

Seasonally, snow-covered forests are a critical source of water in the Western United States and are subject to major disturbances, including fire, harvest, disease and insect-caused mortality, that have relatively unknown effects on water availability. In this study, we investigated changes in winter season snow accumulation and ablation in a forest following the Las Conchas fire in the Jemez Mountains of New Mexico. We investigated two competing sets of processes that should determine the peak annual snowpack prior to snowmelt: (1) reduced interception by forest canopy results in greater new snow accumulation and (2) increased winter season ablation of the snowpack results in reduced peak snowpack volumes. These processes were evaluated with approximately 800 spatially distributed manual observations of new snow, 1500 manual observations of peak snowpack, and light detection and ranging-derived snow depth, vegetation and terrain datasets collected prior to the fire. A single snowfall event yielded significantly larger snow depths in the post-burn area versus the unburned area (p< 0.001), with 25% to 45% interception in the unburned area and near zero in the post-burn area. Conversely, the peak snowpack depths were significantly larger in the unburned area compared with the post-burn area (mean of 55 and 47 cm, respectively), despite nearly identical peak snowpacks prior to the fire (72 and 72 cm, respectively). The lack of strong vegetation controls led to less variability at peak snowpack in the post-burn area and a shift towards topographically controlled variability, caused by differences in elevation and aspect, occurring at larger spatial scales. The unburned area had roughly 10% more water available for melt than the post-burn area, with winter season ablation reducing snowpacks by nearly 50% prior to melt in the post-burn area. The relative importance of shortwave radiation to the snowpack energy balance and sublimation suggests that the 10% reductions in peak snow water storage found in these north-facing areas could be a conservative estimate for winter season ablation following fire. Further work is necessary to assess the role that topography plays in altering water partitioning following forest disturbance and the potential implications for ecological health and downstream water resources. Copyright © 2013 John Wiley & Sons, Ltd. Supporting information may be found in the online version of this article.

 Premise of the Study: Leaf area is a key trait that links plant form, function, and environment. Measures of leaf area can be biased because leaf area is often estimated from dried or fossilized specimens that have shrunk by an unknown amount. We tested the common assumption that this shrinkage is negligible.  Methods: We measured shrinkage by comparing dry and fresh leaf area in 3401 leaves of 380 temperate and tropical species and used phylogenetic and trait-based approaches to determine predictors of this shrinkage. We also tested the effects of rehydration and simulated fossilization on shrinkage in four species.  Key Results: We found that dried leaves shrink in area by an average of 22% and a maximum of 82%. Shrinkage in dried leaves can be predicted by multiple morphological traits with a standard deviation of 7.8%. We also found that mud burial, a proxy for compression fossilization, caused negligible shrinkage, and that rehydration, a potential treatment of dried herbarium specimens, eliminated shrinkage.  Conclusions: Our fi ndings indicate that the amount of shrinkage is driven by variation in leaf area, leaf thickness, evergreenness, and woodiness and can be reversed by rehydration. The amount of shrinkage may also be a useful trait related to ecologically and physiological differences in drought tolerance and plant life history.

The upper half of flowers in Commelina communis deceptively lures potential pollinators with its showy petals and staminodes on the false promise of abundant pollen. This paper presents evidence that staminodization in the upper half is associated with a severe retardation of the entire upper floral hemisphere early in development. Possible consequences of this developmental retardation are seen also in the gynoecium, where the upper carpel of the three-carpellate ovary is underdeveloped and sterile at maturity. Only late in development do the upper petals and staminodes expand and acquire pigments necessary for their attractive function. We surmise that retardations of this severity are unlikely to be found for functionally fertile organs such as stamens and ovule-producing carpels, because key preparatory events preceding sporogenesis might otherwise be disrupted. Such differential growth about the floral apex resembles that known in some eudicots to be regulated by the TCP gene family; thus, future molecular developmental studies in Commelina may help to extend our understanding of the evolutionary genetics of floral monosymmetry to monocots.

Theories of biodiversity rest on several macroecological patterns describing the relationship between species abundance and diversity. A central problem is that all theories make similar predictions for these patterns despite disparate assumptions. A troubling implication is that these patterns may not reflect anything unique about organizational principles of biology or the functioning of ecological systems. To test this, we analyze five datasets from ecological, economic, and geological systems that describe the distribution of objects across categories in the United States. At the level of functional form ('first-order effects'), these patterns are not unique to ecological systems, indicating they may reveal little about biological process. However, we show that mechanism can be better revealed in the scale-dependency of first-order patterns ('second-order effects'). These results provide a roadmap for biodiversity theory to move beyond traditional patterns, and also suggest ways in which macroecological theory can constrain the dynamics of economic systems.

Despite being a fundamental aspect of biodiversity, little is known about what controls species range sizes. This is especially the case for hyperdiverse organisms such as plants. We use the largest botanical data set assembled to date to quantify geographical variation in range size for ~85000 plant species across the New World. We assess prominent hypothesised range-size controls, finding that plant range sizes are codetermined by habitat area and long- and short-term climate stability. Strong short- and long-term climate instability in large parts of North America, including past glaciations, are associated with broad-ranged species. In contrast, small habitat areas and a stable climate characterise areas with high concentrations of small-ranged species in the Andes, Central America and the Brazilian Atlantic Rainforest region. The joint roles of area and climate stability strengthen concerns over the potential effects of future climate change and habitat loss on biodiversity.