Deciphering trophic interactions in a mid-Cambrian assemblage

A deep learning classification framework for research methods of marine protected area management

The latest emerging transdisciplinary marine protected area (MPA) research scheme requires efficient approaches for theoretically based and data-driven method integration. However, due to the rapid development and diversification of research methods, it is growingly difficult to locate new methods in methodological dimensions and integrate them to the utmost utility. This study proposes a deep learning-based classification framework for MPA management methods focused particularly on data and theory capabilities using natural language processing (NLP). It extracted keywords from academic sources and performed clustering based on semantic similarity, generating benchmark texts for abstract labeling. By training the deep learning NLP model and analyzing the abstracts of 9049 MPA management empirical research articles from 1986 to 2024, the data and theory scores were attributed to each article, and a total of 19 major method categories and 110 segment branches were identified in qualitative, quantitative, and mixed genres. Combination types of research methods were summarized, yielding the data-theory neutralization principle where the average data and theory scores tend to approximate 0.50. Applying the principle broadens traditional boundaries for method integration and extends method synthesis to higher numbers, generating a practical research 2paradigm for future MPA research. Implications include bridging social and ecological data, theorizing emergent challenges in complex systems and integrating theory construction and data science. The framework is applicable to quantification of other environmental management disciplines and can serve as guidance for multidisciplinary method integration. © 2017 Elsevier Inc. All rights reserved.

Raptorial appendages of the Cambrian apex predator Anomalocaris canadensis are built for soft prey and speed

The stem-group euarthropod Anomalocaris canadensis is one of the largest Cambrian animals and is often considered the quintessential apex predator of its time. This radiodont is commonly interpreted as a demersal hunter, responsible for inflicting injuries seen in benthic trilobites. However, controversy surrounds the ability of A. canadensis to use its spinose frontal appendages to masticate or even manipulate biomineralized prey. Here, we apply a new integrative computational approach, combining three-dimensional digital modelling, kinematics, finite-element analysis (FEA) and computational fluid dynamics (CFD) to rigorously analyse an A. canadensis feeding appendage and test its morphofunctional limits. These models corroborate a raptorial function, but expose inconsistencies with a capacity for durophagy. In particular, FEA results show that certain parts of the appendage would have experienced high degrees of plastic deformation, especially at the endites, the points of impact with prey. The CFD results demonstrate that outstretched appendages produced low drag and hence represented the optimal orientation for speed, permitting acceleration bursts to capture prey. These data, when combined with evidence regarding the functional morphology of its oral cone, eyes, body flaps and tail fan, suggest that A. canadensis was an agile nektonic predator that fed on soft-bodied animals swimming in a well-lit water column above the benthos. The lifestyle of A. canadensis and that of other radiodonts, including plausible durophages, suggests that niche partitioning across this clade influenced the dynamics of Cambrian food webs, impacting on a diverse array of organisms at different sizes, tiers and trophic levels.

Late Cenozoic cooling restructured global marine plankton communities

The geographic ranges of marine organisms, including planktonic foraminifera¹, diatoms, dinoflagellates², copepods³ and fish⁴, are shifting polewards owing to anthropogenic climate change⁵. However, the extent to which species will move and whether these poleward range shifts represent precursor signals that lead to extinction is unclear⁶. Understanding the development of marine biodiversity patterns over geological time and the factors that influence them are key to contextualizing these current trends. The fossil record of the macroperforate planktonic foraminifera provides a rich and phylogenetically resolved dataset that provides unique opportunities for understanding marine biogeography dynamics and how species distributions have responded to ancient climate changes. Here we apply a bipartite network approach to quantify group diversity, latitudinal specialization and latitudinal equitability for planktonic foraminifera over the past eight million years using Triton, a recently developed high-resolution global dataset of planktonic foraminiferal occurrences⁷. The results depict a global, clade-wide shift towards the Equator in ecological and morphological community equitability over the past eight million years in response to temperature changes during the late Cenozoic bipolar ice sheet formation. Collectively, the Triton data indicate the presence of a latitudinal equitability gradient among planktonic foraminiferal functional groups which is coupled to the latitudinal biodiversity gradient only through the geologically recent past (the past two million years). Before this time, latitudinal equitability gradients indicate that higher latitudes promoted community equitability across ecological and morphological groups. Observed range shifts among marine planktonic microorganisms^1,2,8 in the recent and geological past suggest substantial poleward expansion of marine communities even under the most conservative future global warming scenarios.