• Energy Research

AbstractClimate and land‐use change are key drivers of global change. Full‐factorial field experiments in which both drivers are manipulated are essential to understand and predict their potentially interactive effects on the structure and functioning of grassland ecosystems. Here, we present 8 years of data on grassland dynamics from the Global Change Experimental Facility in Central Germany. On large experimental plots, temperature and seasonal patterns of precipitation are manipulated by superimposing regional climate model projections onto background climate variability. Climate manipulation is factorially crossed with agricultural land‐use scenarios, including intensively used meadows and extensively used (i.e., low‐intensity) meadows and pastures. Inter‐annual variation of background climate during our study years was high, including three of the driest years on record for our region. The effects of this temporal variability far exceeded the effects of the experimentally imposed climate change on plant species diversity and productivity, especially in the intensively used grasslands sown with only a few grass cultivars. These changes in productivity and diversity in response to alterations in climate were due to immigrant species replacing the target forage cultivars. This shift from forage cultivars to immigrant species may impose additional economic costs in terms of a decreasing forage value and the need for more frequent management measures. In contrast, the extensively used grasslands showed weaker responses to both experimentally manipulated future climate and inter‐annual climate variability, suggesting that these diverse grasslands are more resistant to climate change than intensively used, species‐poor grasslands. We therefore conclude that a lower management intensity of agricultural grasslands, associated with a higher plant diversity, can stabilize primary productivity under climate change.

Existing methodologies for estimating woody aboveground biomass and carbon stored therein have been developed for forests but are not tailored to the vast dryland ecosystems where vegetation is heterogenous and highly disturbed. Still, those methods are widely applied with questionable results and possible problematic implications, not only for biomass quantification but also for disturbance ecology, biodiversity research, and ecosystem service assessments. We hereby propose a new methodology especially designed to encompass small, disturbed, and irregular woody growth while keeping sampling effort within reasonable limits. Meaningful demographic growth classes are deployed which enable a stratified sampling design and structure a practicable workflow for integration of different allometric models. To account for the high natural and anthropogenic disturbance levels typically shaping dryland vegetation, our method incorporates a detailed damage assessment by harnessing the ecological archive contained in trees. This allows for quantification of biomass losses to certain disturbance agents, uncovers interactive effects between disturbance agents, and enables assessing the impact of disturbance regime shifts. Extrapolation of biomass losses to stand or landscape level also greatly improves the usual reference state comparison approach. Here, we review the problems of conventional methodologies being applied to drylands, develop and present the improved method proposed by us, and perform a formal method comparison between the two. Results indicate that the conventional allometric method is systematically underestimating biomass and carbon storage in disturbed dryland ecosystems. The bias is highest where general biomass density is lowest and disturbance impacts are severest. Damage assessment demonstrates a dependency between main disturbance agents (elephants and fire) while generally biomass is decreased by increasing elephant densities. The method proposed by us is more time consuming than a conventional allometric approach, yet it can cover sufficient areas within reasonable timespans. Consequent higher data accuracy with concomitant applicability to a wider range of research questions are worth the effort. The proposed method can easily be attuned to other ecosystems or research questions, and elements of it may be adapted to fit alternative sampling schemes. This article is a preprint and has not been certified by peer review. The finally published paper can be accessed at: https://doi.org/10.1016/j.ecolind.2021.108466

This research was funded by the European Research Council (ERC Grant agreement 647038, BIODESERT), the Spanish Ministry of Science and Innovation (PID2020-116578RB-I00) and Generalitat Valenciana (CIDEGENT/2018/041), with additional support by the University of Alicante (UADIF22-74 and VIGROB22-350). F.T.M. acknowledges support from the King Abdullah University of Science and Technology (KAUST) and the KAUST Climate and Livability Initiative. D.J.E. is supported by the Hermon Slade Foundation. H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. L.W. acknowledges support from the US National Science Foundation (EAR 1554894). B.B. and S.S. were supported by the Taylor Family–Asia Foundation Endowed Chair in Ecology and Conservation Biology. M.B. acknowledges support from a Ramón y Cajal grant from the Spanish Ministry of Science (RYC2021-031797-I). A.L. and L.K. acknowledge support from the German Research Foundation, DFG (grant CRC TRR228) and German Federal Government for Science and Education, BMBF (grants 01LL1802C and 01LC1821A). L.K. acknowledges travel funds from the Hans Merensky Foundation. A.N. and C. Branquinho acknowledge support from FCT—Fundação para a Ciência e a Tecnologia (CEECIND/02453/2018/CP1534/CT0001, PTDC/ASP-SIL/7743/2020, UIDB/00329/2020), from AdaptForGrazing project (PRR-C05-i03-I-000035) and from LTsER Montado platform (LTER_EU_PT_001). S.C.R. was supported by NASA (NNH22OB92A) and is grateful to E. Geiger, A. Howell, R. Reibold, N. Melone and M. Starbuck for field support. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the US Government. We thank the landowners for granting access to the sites and many people and their institutions for supporting our fieldwork activities: L. Eloff, J. J. Jordaan, E. Mudongo, V. Mokoka, B. Mokhou, T. Maphanga, D. Thompson (SAEON), A. S. K. Frank, R. Matjea, F. Hoffmann, C. Goebel, the University of Limpopo, South African Environmental Observation Network (SAEON), the South African Military and the Scientific Services Kruger National Park. Mineral-associated organic carbon (MAOC) constitutes a major fraction of global soil carbon and is assumed less sensitive to climate than particulate organic carbon (POC) due to protection by minerals. Despite its importance for long-term carbon storage, the response of MAOC to changing climates in drylands, which cover more than 40% of the global land area, remains unexplored. Here we assess topsoil organic carbon fractions across global drylands using a standardized field survey in 326 plots from 25 countries and 6 continents. We find that soil biogeochemistry explained the majority of variation in both MAOC and POC. Both carbon fractions decreased with increases in mean annual temperature and reductions in precipitation, with MAOC responding similarly to POC. Therefore, our results suggest that ongoing climate warming and aridification may result in unforeseen carbon losses across global drylands, and that the protective role of minerals may not dampen these effects. 19 páginas total artículo.- 3 figuras.- 33 referencias y 4 figuras.- 2 tablas.- 68 referencias.- The online version contains supplementary material available and extended data is available for this paper at https://doi.org/10.1038/s41558-024-02087-y No

AbstractNature conservation and restoration in terrestrial ecosystems is often focused on increasing the numbers of megafauna, expecting them to have positive impacts on ecological self‐regulation processes and biodiversity. In sub‐Saharan Africa, conservation efforts also aspire to protect and enhance biodiversity with particular focus on elephants. However, elephant browsing carries the risk of woody biomass losses. In this context, little is known about how increasing elephant numbers affects carbon stocks in soils, including the subsoils. We hypothesized that (1) increasing numbers of elephants reduce tree biomass, and thus the amount of C stored therein, resulting (2) in a loss of soil organic carbon (SOC). If true, a negative carbon footprint could limit the sustainability of elephant conservation from a global carbon perspective. To test these hypotheses, we selected plots of low, medium, and high elephant densities in two national parks and adjacent conservancies in the Namibian component of the Kavango Zambezi Transfrontier Area (KAZA), and quantified carbon storage in both woody vegetation and soils (1 m). Analyses were supplemented by the assessment of soil carbon isotopic composition. We found that increasing elephant densities resulted in a loss of tree carbon storage by 6.4 t ha−1. However, and in contrast to our second hypothesis, SOC stocks increased by 4.7 t ha−1 with increasing elephant densities. These higher SOC stocks were mainly found in the topsoil (0–30 cm) and were largely due to the formation of SOC from woody biomass. A second carbon input source into the soils was megaherbivore dung, which contributed with 0.02–0.323 t C ha−1 year−1 to ecosystem carbon storage in the low and high elephant density plots, respectively. Consequently, increasing elephant density does not necessarily lead to a negative C footprint, as soil carbon sequestration and transient C storage in dung almost compensate for losses in tree biomass.

Increases in the abundance of woody species have been reported to affect the provisioning of ecosystem services in drylands worldwide. However, it is virtually unknown how multiple biotic and abiotic drivers, such as climate, grazing, and fire, interact to determine woody dominance across global drylands. We conducted a standardized field survey in 304 plots across 25 countries to assess how climatic features, soil properties, grazing, and fire affect woody dominance in dryland rangelands. Precipitation, temperature, and grazing were key determinants of tree and shrub dominance. The effects of grazing were determined not solely by grazing pressure but also by the dominant livestock species. Interactions between soil, climate, and grazing and differences in responses to these factors between trees and shrubs were key to understanding changes in woody dominance. Our findings suggest that projected changes in climate and grazing pressure may increase woody dominance in drylands, altering their structure and functioning.

Earth harbours an extraordinary plant phenotypic diversity1 that is at risk from ongoing global changes2,3. However, it remains unknown how increasing aridity and livestock grazing pressure-two major drivers of global change4-6-shape the trait covariation that underlies plant phenotypic diversity1,7. Here we assessed how covariation among 20 chemical and morphological traits responds to aridity and grazing pressure within global drylands. Our analysis involved 133,769 trait measurements spanning 1,347 observations of 301 perennial plant species surveyed across 326 plots from 6 continents. Crossing an aridity threshold of approximately 0.7 (close to the transition between semi-arid and arid zones) led to an unexpected 88% increase in trait diversity. This threshold appeared in the presence of grazers, and moved toward lower aridity levels with increasing grazing pressure. Moreover, 57% of observed trait diversity occurred only in the most arid and grazed drylands, highlighting the phenotypic uniqueness of these extreme environments. Our work indicates that drylands act as a global reservoir of plant phenotypic diversity and challenge the pervasive view that harsh environmental conditions reduce plant trait diversity8-10. They also highlight that many alternative strategies may enable plants to cope with increases in environmental stress induced by climate change and land-use intensification.