Cover crops do not increase soil organic carbon stocks as much as has been claimed: What is the way forward?

When compared to virgin land (forest and grassland), croplands store significantly lower amounts of organic carbon (OC), mainly as a result of soil tillage, and decreased plant inputs to the soil over the whole year. Doubts have been expressed over how much reduced and zero tillage agriculture can increase OC in soils when the whole soil profile is considered. Consequently, cover-crops that are grown in-between crops instead of leaving soils bare appear as the “last man standing” in our quest to enhance cropland OC stocks. Despite the claim by numerous meta-analyses of a mean carbon sequestration rate by cover crops to be as high as 0.32 ± 0.08 ton C ha⁻¹ year⁻¹, the present analysis showed that all of the 37 existing field studies worldwide only sampled to a depth of 30 cm or less and did not compare treatments on the basis of equivalent soil mass. Thirteen studies presented information on OC content only and not on OC stocks, had inappropriate controls (n = 14), had durations of 3 years or lower (n = 5), considered only one to two data points per treatment (n = 4), or used cover crops as cash crops (i.e., grown longer that in-between two crops) instead of catch crops (n = 2), which in all cases constitutes shortcomings. Of the remaining six trials, four showed non-significant trends, one study displayed a negative impact of cover crops, and one study displayed a positive impact, resulting in a mean OC storage of 0.03 ton ha⁻¹ year⁻¹. Models and policies should urgently adapt to such new figure. Finally, more is to be done not only to improve the design of cover-crop studies for reaching sound conclusions but also to understand the underlying reasons of the low efficiency of cover crops for improved carbon sequestration into soils, with possible strategies being suggested.     

HomeRange: A global database of mammalian home ranges

Motivation

Home range is a common measure of use of space by animals because it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of use of space by animals. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has historically been biased towards terrestrial mammals. The use of aggregated numbers and the terrestrial focus limit our ability to examine home-range patterns across different environments, their variation in time and variation between different levels of organization. Here, we introduce HomeRange, a global database with 75,611 home-range values across 960 different species of mammals, including terrestrial, aquatic and aerial species.

Main types of variables contained

The dataset contains estimates of home ranges of mammals, species names, methodological information on data collection, method of home-range estimation, period of data collection, study coordinates and name of location, in addition to species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit.

Spatial location and grain

The collected data are distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1°.

Time period and grain

The data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies; some studies report start and end dates specific to the day, whereas for other studies only the month or year is reported.

Major taxa and level of measurement

Mammalian species from 24 of the 27 different taxonomic orders. Home-range estimates range from individual-level values to population-level averages.

Software format

Data are supplied as a comma-delimited text file (.csv) and can be loaded directly into R using the “HomeRange” R package ( https://github.com/SHoeks/HomeRange ).     

Human appropriation of net primary production as driver of change in landscape-scale vertebrate richness

Aim

Land use is the most pervasive driver of biodiversity loss. Predicting its impact on species richness (SR) is often based on indicators of habitat loss. However, the degradation of habitats, especially through land-use intensification, also affects species. Here, we evaluate whether an integrative metric of land-use intensity, the human appropriation of net primary production, is correlated with the decline of SR in used landscapes across the globe.

Location

Global.

Time period

Present.

Major taxa studied

Birds, mammals and amphibians.

Methods

Based on species range maps (spatial resolution: 20 km × 20 km) and an area-of-habitat approach, we calibrated a “species–energy model” by correlating the SR of three groups of vertebrates with net primary production and biogeographical covariables in “wilderness” areas (i.e., those where available energy is assumed to be still at pristine levels). We used this model to project the difference between pristine SR and the SR corresponding to the energy remaining in used landscapes (i.e., SR loss expected owing to human energy extraction outside wilderness areas). We validated the projected species loss by comparison with the realized and impending loss reconstructed from habitat conversion and documented by national Red Lists.

Results

Species–energy models largely explained landscape-scale variation of mapped SR in wilderness areas (adjusted R²-values: 0.79–0.93). Model-based projections of SR loss were lower, on average, than reconstructed and documented ones, but the spatial patterns were correlated significantly, with stronger correlation in mammals (Pearson's r = 0.68) than in amphibians (r = 0.60) and birds (r = 0.57).

Main conclusions

Our results suggest that the human appropriation of net primary production is a useful indicator of heterotrophic species loss in used landscapes, hence we recommend its inclusion in models based on species–area relationships to improve predictions of land-use-driven biodiversity loss.     

基于遗传算法的土地利用优化：NSGA-Ⅱ和NSGA-Ⅲ的对比研究

土地利用优化通常要兼顾不同群体的多种要求,理论上是复杂的超多目标(4个及以上)优化问题。但实际操作中却往往被简化为多目标(2—3个)优化问题,通过一种流行的多目标优化算法第Ⅱ代非支配排序遗传算法(NSGA-Ⅱ)求解。究其原因是对超多目标优化算法认知的缺失和与多目标优化算法理论对比的匮乏。对NSGA系列中应用最广泛的多目标优化算法NSGA-Ⅱ和最新提出、面向超多目标优化的算法NSGA-Ⅲ进行探究,从理论和实验两方面对Ⅲ和Ⅱ进行对比,从而探究二者进行土地利用优化时的优劣。在理论上,对比两种算法原理的异同。在实验中,分别设计多目标(3个目标)和超多目标(13个目标)土地利用优化问题,利用两种算法进行求解。对实验结果采用四层架构、六大指标进行全面评价,以对比两种算法的可用性。理论对比发现,两个算法只有种群多样性保护的方法不同,其中NSGA-Ⅲ是基于与固定的参考点的距离,而NSGA-Ⅱ则是基于相邻解间的距离。通过实验对比发现,NSGA-Ⅲ在超多目标优化时运算速度快,且产生的最优方案实用价值更高,NSGA-Ⅱ在算法的有效性方面更有优势。     

Identifying Mozambique's most critical areas for plant conservation: An evaluation of protected areas and Important Plant Areas

Successful protected area networks must represent biodiversity across taxonomic groups. However, too often plant species are overlooked in conservation planning, and the resulting protected areas may, as a result, fail to encompass the most important sites for plant diversity. The Mozambique Tropical Important Plant Areas project sought to promote the conservation of Mozambique's flora through the identification of Important Plant Areas (IPAs). Here, we use the Weighted Endemism including Global Endangerment (WEGE) index to identify the richest areas for rare and endemic plants in Mozambique and subsequently evaluate how well represented these hotspots are within the current protected area and IPA networks. We also examine the congruence between IPA and protected areas to identify opportunities for strengthening the conservation of plants in Mozambique. We found that high WEGE scores, representing areas rich in endemic/near-endemic and threatened species, predict the presence of IPAs in Mozambique, but do not predict the presence of protected areas. We also find that there is limited overlap between IPAs and protected areas in Mozambique. We demonstrate how IPAs could be an important tool for ensuring priority sites for plant diversity are included within protected area network expansions, particularly following the adoption of the “30 by 30” target agreed within the post-2020 Convention on Biological Diversity framework, with great potential for this method to be replicated elsewhere in the global tropics.     

Arbuscular Mycorrhizal Fungal Colonization at Different Succession Stages in Songnen Saline-Alkali Grassland

Arbuscular mycorrhizal (AM) fungi can form symbiosis with 90% of the vascular plants and play important roles in ecosystem. To realize the AM fungal colonization at different succession stages in saline-alkali land and screen AM fungi species with great functions, roots and soil samples were collected from the three succession stages of Songnen saline-alkali grassland. The soil properties and AM fungal colonization were measured, and the fungus distributed extensively in three stages was annotated by sequencing for AML1/AML2 target, subsequently, maize was selected as the host to verify its colonization. The results showed that the soil properties improved with the succession of saline-alkali grassland. The plants’ communities of the three stages could be colonized by AM fungi, and the colonization rate of Leymus chinensis (the third stage) ranged from 66.67% to 100%, Puccinellia tenuiflora (the second stage) ranged from 50% to 80%, while the Suaeda glauca (the first stage) was only 35%–60%. Glomeraceae sp1 was identified as the dominant AM fungi species which occurred frequently in the succession of saline-alkali land with the isolation frequency, relative abundance, and importance value of 100%, 18.1%, and 59.1%, respectively. The colonization rate of Glomeraceae sp1 in maize ranged from 80% to 87% and similar mycorrhizal characteristics were detected in the roots of P. tenuiflora, S. glauca, and L. chinensis, indicating that Glomeraceae sp1 colonized the samples in the field. The correlation matrix indicated that colonization rate, colonization intensity, and vesicle abundance were closely related to soil conditions most, and they were related significantly to all the soil properties except cellulase activity. Besides, redundancy analysis (RDA) showed that soil properties drove the changes of AM fungal colonization and sporulation. These results will provide theoretical support for realizing the relationship between AM fungal colonization and soil conditions, and also for the exploration of AM fungi species with great functions.

     

Mammal use of riparian corridors in semi-arid Sonora,Mexico

Wildlife populations in semi-arid regions are increasingly challenged by human activities and dependent on the connectivity of riparian corridors for access to surface water. The Madrean Archipelago is a biodiversity hotspot along the arid United States–Mexico borderlands that support both Neotropical and Nearctic wildlife. Infrastructure development (e.g., the border wall and the expansion of Mexican Federal Highway 2) in this region inhibits wildlife movement along the transnational mountain archipelago by disconnecting habitat. To explore the relationship between habitat variables and mammal use of riparian corridors in northern Sonora, Mexico, we collected data from 19 motion-sensitive cameras between October 2018 and April 2019 and used single-season occupancy models and Royle-Nichols abundance estimation models to analyze our data. We recorded 21 species of mammals, including the first sighting of jaguar (Panthera onca) in this region in 25 years. River characteristics (distance from river, riparian corridor width, water availability), remoteness (distance from highway, productivity, elevation), and topographic variety (vertical elevation difference) influenced patterns of occupancy probability and estimated abundance of mammals >1 kg, but the strength and direction of these relationships varied by species. Additionally, intermittently wet desert washes were comparable in species richness to the perennial system. These results highlight the importance of examining physical and biological aspects of habitat. This is especially true when identifying corridors where mitigation structures should be placed to improve wildlife connectivity in biodiversity hotspots like the Madrean Archipelago and semi-arid ecosystems worldwide.     

Experimental and computational characterization of mass transfer in high turndown bioreactors

Single-use bioreactors (SUBs, or disposable bioreactors) are extensively used for the clinical and commercial production of biologics. Despite widespread application, minimal results have been reported utilizing the turndown ratio; an operation mode where the working range of the bioreactor can be expanded to include low fluid volumes. In this work, a systematic investigation into free surface mass transfer and cell growth in high turndown single-use bioreactors is presented. This approach, which combines experimental mass transfer measurements with numerical simulation, deconvolutes the combined effects of headspace mixing and the free surface convective mass transfer on cell growth. Under optimized conditions, mass transfer across the interface alone may be sufficient to satisfy oxygen demands of the cell culture. Within the context of high turndown bioreactors, this finding provides a counterpoint to traditional sparge-based bioreactor operational philosophy. Multiple monoclonal antibody-producing cell lines grown using this high turndown approach showed similar viable cell densities to those cells expanded using a traditional cell bag rocker. Furthermore, cells taken directly from the turndown expansion and placed into production showed identical growth characteristics to traditionally expanded cultures. Taken together, these results suggest that the Xcellerex SUB can be run at a 5:1 working volume as a seed to itself, with no need for system modifications, potentially simplifying preculture operations.     

BLOEM: A spatially explicit model of bioenergy and carbon capture and storage,applied to Brazil

Bioenergy could play a major role in decarbonizing energy systems in the context of the Paris Agreement. Large-scale bioenergy deployment could be related to sustainability issues and requires major infrastructure investments. It, therefore, needs to be studied carefully. The Bioenergy and Land Optimization Spatially Explicit Model (BLOEM) presented here allows for assessing different bioenergy pathways while encompassing various dimensions that influence their optimal deployment. In this study, BLOEM was applied to the Brazilian context by coupling it with the Brazilian Land Use and Energy Systems (BLUES) model. This allowed investigating the most cost-effective ways of attending future bioenergy supply projections and studying the role of recovered degraded pasture lands in improving land availability in a sustainable and competitive manner. The results show optimizing for limiting deforestation and minimizing logistics costs results in different outcomes. It also indicates that recovering degraded pasture lands is attractive from both logistics and climate perspectives. The systemic approach of BLOEM provides spatial results, highlighting the trade-offs between crop allocation, land use and the logistics dynamics between production, conversion, and demand, providing valuable insights for regional and national climate policy design. This makes it a useful tool for mapping sustainable bioenergy value chain pathways.