RecruitNet: A global database of plant recruitment networks.

Plant recruitment interactions (i.e., what recruits under what) shape the composition, diversity, and structure of plant communities. Despite the huge body of knowledge on the mechanisms underlying recruitment interactions among species, we still know little about the structure of the recruitment networks emerging in ecological communities. Modeling and analyzing the community-level structure of plant recruitment interactions as a complex network can provide relevant information on ecological and evolutionary processes acting both at the species and ecosystem levels. We report a data set containing 143 plant recruitment networks in 23 countries across five continents, including temperate and tropical ecosystems. Each network identifies the species under which another species recruits. All networks report the number of recruits (i.e., individuals) per species. The data set includes >850,000 recruiting individuals involved in 118,411 paired interactions among 3318 vascular plant species across the globe. The cover of canopy species and open ground is also provided. Three sampling protocols were used: (1) The Recruitment Network (RN) protocol (106 networks) focuses on interactions among established plants ("canopy species") and plants in their early stages of recruitment ("recruit species"). A series of plots was delimited within a locality, and all the individuals recruiting and their canopy species were identified; (2) The paired Canopy-Open (pCO) protocol (26 networks) consists in locating a potential canopy plant and identifying recruiting individuals under the canopy and in a nearby open space of the same area; (3) The Georeferenced plot (GP) protocol (11 networks) consists in using information from georeferenced individual plants in large plots to infer canopy-recruit interactions. Some networks incorporate data for both herbs and woody species, whereas others focus exclusively on woody species. The location of each study site, geographical coordinates, country, locality, responsible author, sampling dates, sampling method, and life habits of both canopy and recruit species are provided. This database will allow researchers to test ecological, biogeographical, and evolutionary hypotheses related to plant recruitment interactions. There are no copyright restrictions on the data set; please cite this data paper when using these data in publications.

Greenhouse gas emissions from global production and use of nitrogen synthetic fertilisers in agriculture.

The global agri-food system relies on synthetic nitrogen (N) fertilisation to increase crop yields, yet the use of synthetic N fertiliser is unsustainable. In this study we estimate global greenhouse (GHG) emissions due to synthetic N fertiliser manufacture, transportation, and field use in agricultural systems. By developing the largest field-level dataset available on N2O soil emissions we estimate national, regional and global N2O direct emission factors (EFs), while we retrieve from the literature the EFs for indirect N2O soil emissions, and for N fertiliser manufacturing and transportation. We find that the synthetic N fertiliser supply chain was responsible for estimated emissions of 1.13 GtCO2e in 2018, representing 10.6% of agricultural emissions and 2.1% of global GHG emissions. Synthetic N fertiliser production accounted for 38.8% of total synthetic N fertiliser-associated emissions, while field emissions accounted for 58.6% and transportation accounted for the remaining 2.6%. The top four emitters together, China, India, USA and EU28 accounted for 62% of the total. Historical trends reveal the great disparity in total and per capita N use in regional food production. Reducing overall production and use of synthetic N fertilisers offers large mitigation potential and in many cases realisable potential to reduce emissions.

Active restoration accelerates the carbon recovery of human-modified tropical forests.

More than half of all tropical forests are degraded by human impacts, leaving them threatened with conversion to agricultural plantations and risking substantial biodiversity and carbon losses. Restoration could accelerate recovery of aboveground carbon density (ACD), but adoption of restoration is constrained by cost and uncertainties over effectiveness. We report a long-term comparison of ACD recovery rates between naturally regenerating and actively restored logged tropical forests. Restoration enhanced decadal ACD recovery by more than 50%, from 2.9 to 4.4 megagrams per hectare per year. This magnitude of response, coupled with modal values of restoration costs globally, would require higher carbon prices to justify investment in restoration. However, carbon prices required to fulfill the 2016 Paris climate agreement [$40 to $80 (USD) per tonne carbon dioxide equivalent] would provide an economic justification for tropical forest restoration.

Changes in soil organic carbon under perennial crops.

This study evaluates the dynamics of soil organic carbon (SOC) under perennial crops across the globe. It quantifies the effect of change from annual to perennial crops and the subsequent temporal changes in SOC stocks during the perennial crop cycle. It also presents an empirical model to estimate changes in the SOC content under crops as a function of time, land use, and site characteristics. We used a harmonized global dataset containing paired-comparison empirical values of SOC and different types of perennial crops (perennial grasses, palms, and woody plants) with different end uses: bioenergy, food, other bio-products, and short rotation coppice. Salient outcomes include: a 20-year period encompassing a change from annual to perennial crops led to an average 20% increase in SOC at 0-30 cm (6.0 ± 4.6 Mg/ha gain) and a total 10% increase over the 0-100 cm soil profile (5.7 ± 10.9 Mg/ha). A change from natural pasture to perennial crop decreased SOC stocks by 1% over 0-30 cm (-2.5 ± 4.2 Mg/ha) and 10% over 0-100 cm (-13.6 ± 8.9 Mg/ha). The effect of a land use change from forest to perennial crops did not show significant impacts, probably due to the limited number of plots; but the data indicated that while a 2% increase in SOC was observed at 0-30 cm (16.81 ± 55.1 Mg/ha), a decrease in 24% was observed at 30-100 cm (-40.1 ± 16.8 Mg/ha). Perennial crops generally accumulate SOC through time, especially woody crops; and temperature was the main driver explaining differences in SOC dynamics, followed by crop age, soil bulk density, clay content, and depth. We present empirical evidence showing that the FAO perennialization strategy is reasonable, underscoring the role of perennial crops as a useful component of climate change mitigation strategies.

Trade-Offs Among Aboveground, Belowground, and Soil Organic Carbon Stocks Along Altitudinal Gradients in Andean Tropical Montane Forests.

Tropical montane forests (TMFs) play an important role as a carbon reservoir at a global scale. However, there is a lack of a comprehensive understanding on the variation in carbon storage across TMF compartments [namely aboveground biomass (AGB), belowground biomass (BGB), and soil organic matter] along altitudinal and environmental gradients and their potential trade-offs. This study aims to: 1) understand how carbon stocks vary along altitudinal gradients in Andean TMFs, and; 2) determine the influence of climate, particularly precipitation seasonality, on the distribution of carbon stocks across different forest compartments. The study was conducted in sixty 0.1 ha plots along two altitudinal gradients at the Podocarpus National Park (Ecuador) and Río Abiseo National Park (Peru). At each plot, we calculated the amount of carbon in AGB (i.e. aboveground carbon stock, AGC), BGB (i.e. belowground carbon stock, BGC), and soil organic matter (i.e. soil organic carbon stock, SOC). The mean total carbon stock was 244.76 ± 80.38 Mg ha-1 and 211.51 ± 46.95 Mg ha-1 in the Ecuadorian and Peruvian plots, respectively. Although AGC, BGC, and SOC showed different partitioning patterns along the altitudinal gradient both in Ecuador and Peru, total carbon stock did not change with altitude in either site. The combination of annual mean temperature and precipitation seasonality explained differences in the observed patterns of carbon stocks across forest compartments between the two sites. This study suggests that the greater precipitation seasonality of colder, higher altitudes may promote faster turnover rates of organic matter and nutrients and, consequently, less accumulation of SOC but greater AGC and BGC, compared to those sites with lesser precipitation seasonality. Our results demonstrate the capacity of TMFs to store substantial amounts of carbon and suggest the existence of a trade-off in carbon stocks among forest compartments, which could be partly driven by differences in precipitation seasonality, especially under the colder temperatures of high altitudes.

A global, empirical, harmonised dataset of soil organic carbon changes under perennial crops.

A global, unified dataset on Soil Organic Carbon (SOC) changes under perennial crops has not existed till now. We present a global, harmonised database on SOC change resulting from perennial crop cultivation. It contains information about 1605 paired-comparison empirical values (some of which are aggregated data) from 180 different peer-reviewed studies, 709 sites, on 58 different perennial crop types, from 32 countries in temperate, tropical and boreal areas; including species used for food, bioenergy and bio-products. The database also contains information on climate, soil characteristics, management and topography. This is the first such global compilation and will act as a baseline for SOC changes in perennial crops. It will be key to supporting global modelling of land use and carbon cycle feedbacks, and supporting agricultural policy development.

Evaluation of four modelling approaches to estimate nitrous oxide emissions in China's cropland.

Process-based models are useful tools to integrate the effects of detailed agricultural practices, soil characteristics, mass balance, and climate change on soil N2O emissions from soil - plant ecosystems, whereas static, seasonal or annual models often exist to estimate cumulative N2O emissions under data-limited conditions. A study was carried out to compare the capability of four models to estimate seasonal cumulative N2O fluxes from 419 field measurements representing 65 studies across China's croplands. The models were 1) the DAYCENT model, 2) the DNDC model, 3) the linear regression model (YLRM) of Yue et al. (2018), and 4) IPCC Tier 1 emission factors. The DAYCENT and DNDC models estimated crop yields with R2 values of 0.60 and 0.66 respectively, but both models showed significant underestimation for all measurements. The estimated seasonal N2O emissions with R2 of 0.31, 0.30, 0.21 and 0.17 for DAYCENT, DNDC, YLRM, and IPCC, respectively. Based on RMSE, modelling efficiency and bias analysis, YLRM performed well on N2O emission prediction under no fertilization though bias still existed, while IPCC performed well for cotton and rapeseed and DNDC for soybean. The DAYCENT model accurately predicted the emissions with no bias across other crop and fertilization types whereas the DNDC model underestimated seasonal N2O emissions by 0.42 kg N2O-N ha-1 for all observed values. Model evaluation indicated that the DAYCENT and DNDC models simulated temporal patterns of daily N2O emissions effectively, but both models had difficulty in simulating the timing of the N2O fluxes following some events such as fertilization and water regime. According to this evaluation, algorithms for crop production and N2O emission should be improved to increase the accuracy in the prediction of unfertilized fields both for DAYCENT and DNDC. The effects of crop types and management modes such as fertilizations should also be further refined for YLRM.

Re-evaluation of individual diameter : height allometric models to improve biomass estimation of tropical trees.

Accurate estimation of tree biomass is necessary to provide realistic values of the carbon stored in the terrestrial biosphere. A recognized source of errors in tree aboveground biomass (AGB) estimation is introduced when individual tree height values (H) are not directly measured but estimated from diameter at breast height (DBH) using allometric equations. In this paper, we evaluate the performance of 12 alternative DBH : H equations and compare their effects on AGB estimation for three tropical forests that occur in contrasting climatic and altitudinal zones. We found that fitting a three-parameter Weibull function using data collected locally generated the lowest errors and bias in H estimation, and that equations fitted to these data were more accurate than equations with parameters derived from the literature. For computing AGB, the introduced error values differed notably among DBH : H allometric equations, and in most cases showed a clear bias that resulted in either over- or under-estimation of AGB. Fitting the three-parameter Weibull function minimized errors in AGB estimates in our study and we recommend its widespread adoption for carbon stock estimation. We conclude that many previous studies are likely to present biased estimates of AGB due to the method of H estimation.

Nature and Age of Neighbours Matter: Interspecific Associations among Tree Species Exist and Vary across Life Stages in Tropical Forests.

Detailed information about interspecific spatial associations among tropical tree species is scarce, and hence the ecological importance of those associations may have been underestimated. However, they can play a role in community assembly and species diversity maintenance. This study investigated the spatial dependence between pairs of species. First, the spatial associations (spatial attraction and spatial repulsion) that arose between species were examined. Second, different sizes of trees were considered in order to evaluate whether the spatial relationships between species are constant or vary during the lifetime of individuals. Third, the consistency of those spatial associations with the species-habitat associations found in previous studies was assessed. Two different tropical ecosystems were investigated: a montane cloud forest and a lowland moist forest. The results showed that spatial associations among species exist, and these vary among life stages and species. The rarity of negative spatial interactions suggested that exclusive competition was not common in the studied forests. On the other hand, positive interactions were common, and the results of this study strongly suggested that habitat associations were not the only cause of spatial attraction among species. If this is true, habitat associations and density dependence are not the only mechanisms that explain species distribution and diversity; other ecological interactions, such as facilitation among species, may also play a role. These spatial associations could be important in the assembly of tropical tree communities and forest succession, and should be taken into account in future studies.

Disturbance and clonal reproduction determine liana distribution and maintain liana diversity in a tropical forest.

Negative density dependence (NDD) and habitat specialization have received strong empirical support as mechanisms that explain tree species diversity maintenance and distribution in tropical forests. In contrast, disturbance appears to play only a minor role. Previous studies have rarely examined the relative strengths of these diversity maintenance mechanisms concurrently, and few studies have included plant groups other than trees. Here we used a large, spatially explicit data set from Barro Colorado Island, Panama (BCI) to test whether liana and tree species distribution patterns are most consistent with NDD, habitat specialization, or disturbance. We found compelling evidence that trees responded to habitat specialization and NDD; however, only disturbance explained the distribution of the majority of liana species and maintained liana diversity. Lianas appear to respond to disturbance with high vegetative (clonal) reproduction, and liana species' ability to produce clonal stems following disturbance results in a clumped spatial distribution. Thus, clonal reproduction following disturbance explains local liana spatial distribution and diversity maintenance on BCI, whereas negative density dependence and habitat specialization, two prominent mechanisms contributing to tree species diversity and distribution, do not.

Liana abundance, diversity, and distribution on Barro Colorado Island, Panama.

Lianas are a key component of tropical forests; however, most surveys are too small to accurately quantify liana community composition, diversity, abundance, and spatial distribution - critical components for measuring the contribution of lianas to forest processes. In 2007, we tagged, mapped, measured the diameter, and identified all lianas ≥1 cm rooted in a 50-ha plot on Barro Colorado Island, Panama (BCI). We calculated liana density, basal area, and species richness for both independently rooted lianas and all rooted liana stems (genets plus clones). We compared spatial aggregation patterns of liana and tree species, and among liana species that varied in the amount of clonal reproduction. We also tested whether liana and tree densities have increased on BCI compared to surveys conducted 30-years earlier. This study represents the most comprehensive spatially contiguous sampling of lianas ever conducted and, over the 50 ha area, we found 67,447 rooted liana stems comprising 162 species. Rooted lianas composed nearly 25% of the woody stems (trees and lianas), 35% of woody species richness, and 3% of woody basal area. Lianas were spatially aggregated within the 50-ha plot and the liana species with the highest proportion of clonal stems more spatially aggregated than the least clonal species, possibly indicating clonal stem recruitment following canopy disturbance. Over the past 30 years, liana density increased by 75% for stems ≥1 cm diameter and nearly 140% for stems ≥5 cm diameter, while tree density on BCI decreased 11.5%; a finding consistent with other neotropical forests. Our data confirm that lianas contribute substantially to tropical forest stem density and diversity, they have highly clumped distributions that appear to be driven by clonal stem recruitment into treefall gaps, and they are increasing relative to trees, thus indicating that lianas will play a greater role in the future dynamics of BCI and other neotropical forests.