Coupling Biocrusts and Vegetation Dynamics to Improve Predictions of Dryland Change

世界范围内的环境变化已将生态系统推向极限，因此越来越需要更好地预测生态系统对这些外部压力的反应。先前的工作表明，在许多生态系统中发现的空间模式在接近临界点时以可预测的方式发生变化。这些空间格局可能预示着即将发生的整个生态系统的变化。旱地被用作发展这种理论的关键系统。该理论预测，随着气候变得更加干燥，旱地植被的格局从同质植被中的裸露空隙转变为带状或条纹状植被覆盖，然后转变为斑点状格局，最后灾难性地转变为裸露状态。利用这种空间格局运作生态系统变化预警系统需要准确描述重要反馈;否则，“假警报”可能导致代价高昂的资源分配不当。不幸的是，目前理论的预测仅限于全球一小部分旱地。这可能是因为目前的模型忽略了生物土壤结壳或生物结壳。生物结壳是土壤颗粒和活微生物之间的结合体（例如，蓝细菌、地衣、苔藓、细菌），它们生活在土壤表层几毫米的土壤中或紧挨着土壤表层。生物结壳可以覆盖比维管植物更多的表面积，并在水，能量和营养的动态中发挥关键作用。它们还改变了构成植被空间格局基础的核心进程。忽视生物结壳会给预测气候驱动的旱地变化带来很大的不确定性。目前的生态系统空间自组织理论只考虑到一种同质的生物组合，就旱地而言，即维管植物。将旱地概念化为一个完整的生物结壳-维管植物复合体，需要新的理论和模型，将种间相互作用结合起来（例如，竞争、促进）和空间自组织。这项研究以旱地为重点研究领域，发展了这种理论和模式。该项目通过（1）在实验室中操纵降雨状况并跟踪生物结壳斑块的形成和（2）监测美国西南部的旱地来研究生物结壳斑块动态。旱地格局形成模型将维管植物与生物结壳联系起来。将这些模型与先前不考虑生物结壳的模型进行比较，可以阐明生物结壳在旱地恢复力中的作用，并预测生态系统状态（例如，生产力）和空间格局随着气候变化下降雨量的改变而改变。最后，多源遥感图像和深度学习方法指导大规模生物结壳制图。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Environmental changes worldwide have pushed ecosystems towards their limit, and there is a growing need to better predict ecosystem responses to these external pressures. Prior work suggests that spatial patterns found in many ecosystems change in a predictable way when approaching a tipping point. These spatial patterns can be harbingers of imminent whole ecosystem change. Drylands have been used as pivotal systems in developing such a theory. The theory predicts that as the climate becomes drier, patterns of dryland vegetation shift from bare gaps in homogenous vegetation to labyrinthine or striped vegetation cover, then to a spotty pattern, before catastrophically shifting to a bare state. Operationalizing an early warning system of ecosystem change using such spatial patterns requires accurate characterization of significant feedbacks; otherwise, “false alarms” could lead to costly resource misallocations. Unfortunately, predictions from current theory are limited to only a small area of drylands globally. This is likely because models currently ignore biological soil crusts, or biocrusts. Biocrusts are associations between soil particles and living microorganisms (e.g., cyanobacteria, lichens, mosses, bacteria) that live within or immediately on top of, the upper few millimeters of soils. Biocrusts can cover more surface area than vascular plants and play a critical role in the dynamics of water, energy, and nutrients. They also alter core processes that underlie vegetation spatial patterns. Neglecting biocrusts poses significant uncertainties in predicting dryland change driven by climate. Current theory of ecosystem spatial self-organization considers only one homogenous assemblage of organisms, in the case of drylands, vascular plants. Conceptualizing drylands as an integral biocrust-vascular plant complex requires new theories and models that integrate inter-specific interactions (e.g., competition, facilitation) and spatial self-organization. This research develops such theories and models, using drylands as a focal study area. The project investigates biocrust patch dynamics by (1) manipulating rainfall regimes in the lab and tracking biocrust patch formation and (2) monitoring drylands of the U.S. Southwest. Dryland pattern formation models link vascular plants with biocrusts. Comparing these models, with prior models that do not consider biocrusts, elucidates the role of biocrusts in dryland resilience and predicts how ecosystem state (e.g., productivity) and spatial patterns change with altered rainfall regimes under climate change. Lastly, multi-source remote sensing imagery and deep learning approaches guide large-scale biocrust mapping. The resultant models predict changes to drylands in the U.S. Southwest over the next few decades of anticipated climate change.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.