Man Qi

Ecosystem collapse is often attributed to the absence of stress-tolerant species, yet many climate-stressed systems fail even when these species remain regionally present. This raises a critical, unresolved question: does collapse result from species pool depletion, or from failed recruitment? We addressed this by combining vegetation surveys and a three-year transplant experiment in sea level rise–threatened brackish marshes of Chesapeake Bay, USA. We first showed that replacement failure (i.e. suitable species exist in the regional species pool but failed to colonize) intensified along a gradient of increasing inundation, where flood-tolerant species exhibited lower occupancy and colonization of dieback patches compared to flood-sensitive species. By transplanting a dominant flood-tolerant species, Juncus roemerianus, into marsh zones of different stages of degradation, we found three main constraints on colonization: (1) competition from established species such as the sedge Schoenoplectus americanus, (2) dispersal inefficiency or establishment failure in dieback areas, and (3) post-dieback peat collapse, which rapidly renders unoccupied habitats physically uninhabitable. Our findings reveal that marsh collapse arises from compounded recruitment bottlenecks—not regional species exhaustion. This finding challenges species distribution assumptions that infer future presence from current occupancy without accounting for failed recruitment. Restoration must intervene early to reopen recruitment pathways—by managing competitors, stabilizing substrate, and enhancing propagule delivery—before physical degradation locks ecosystems into collapse.

Resource competition theory predicts coexistence and exclusion patterns based on species R*s, the minimum resource values required for a species to persist. A central assumption of the theory is that all species have equal access to resources. However, many systems are characterized by preemption exploitation, where some species deplete resources before their competitors can access them (e.g., asymmetric light competition, contest competition among animals). We hypothesize that coexistence under preemption requires an R*-preemption tradeoff, i.e., the species with the priority access should have a higher R* (lower efficiency). Thus, we developed an extension of resource competition theory to investigate partial and total preemption (in the latter, the preemptor is unaffected by species with lower preemption rank). We found that an R*-preemption tradeoff is a necessary condition for coexistence in all models. Moreover, under total preemption, the tradeoff alone is sufficient for coexistence. In contrast, under partial preemption, more conditions are needed, which restricts the parameter space of coexistence. Finally, we discussed the implications of our finding for seemingly distinct tradeoffs, which we view as special cases of R*-preemption tradeoff. These tradeoffs include the digger-grazer, the competition-colonization, and tradeoffs related to light competition between trees and understories.

Terrestrial laser scanning (TLS) is an important part of urban reconstruction and terrain surveying. In TLS applications, 4-point congruent set (4PCS) technology is widely used for the global registration of point clouds. However, TLS point clouds usually enjoy enormous data and uneven density. Obtaining the congruent set of tuples in a large point cloud scene can be challenging. To address this concern, we propose a registration method based on the voxel grid of the point cloud in this paper. First, we establish a voxel grid structure and index structure for the point cloud and eliminate uneven point cloud density. Then, based on the point cloud distribution in the voxel grid, keypoints are calculated to represent the entire point cloud. Fast query of voxel grids is used to restrict the selection of calculation points and filter out 4-point tuples on the same surface to reduce ambiguity in building registration. Finally, the voxel grid is used in our proposed approach to perform random queries of the array. Using different indoor and outdoor data to compare our proposed approach with other 4-point congruent set methods, according to the experimental results, in terms of registration efficiency, the proposed method is more than 50% higher than K4PCS and 78% higher than Super4PCS.