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Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade‐off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real‐world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low‐cost, and open‐source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area‐wide ecosystem mapping tasks, thereby providing an exemplary cost‐efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystem

Prescribed burning and pyric herbivory play pivotal roles in mitigating wildfire risks, underscoring the imperative of consistent biomass monitoring for assessing fuel load reductions. Drone-derived surface models promise uninterrupted biomass surveillance but require complex photogrammetric processing. In a Mediterranean mountain shrubland burning experiment, we refined a Structure from Motion (SfM) and Multi-View Stereopsis (MVS) workflow to diminish biases in 3D modeling and RGB drone imagery-based surface reconstructions. Given the multitude of SfM-MVS processing alternatives, stringent quality oversight becomes paramount. We executed the following steps: (i) calculated Root Mean Square Error (RMSE) between Global Navigation Satellite System (GNSS) checkpoints to assess SfM sparse cloud optimization during georeferencing; (ii) evaluated elevation accuracy by comparing the Mean Absolute Error (MAE) of six surface and thirty terrain clouds against GNSS readings and known box dimensions; and (iii) complemented a dense cloud quality assessment with density metrics. Balancing overall accuracy and density, we selected surface and terrain cloud versions for high-resolution (2 cm pixel size) and accurate (DSM, MAE = 57 mm; DTM, MAE = 48 mm) Digital Elevation Model (DEM) generation. These DEMs, along with exceptional height and volume models (height, MAE = 12 mm; volume, MAE = 909.20 cm3) segmented by reference box true surface area, substantially contribute to burn impact assessment and vegetation monitoring in fire management systems.

PURPOSE. Reports of lymphatics in the anterior human uvea are contradictory. This might be caused due to a certain topography, which has not been considered yet. Therefore, here we systematically analyze iris and adjacent ciliary body with immunohistochemistry by combining various lymphatic markers. METHODS. Human iris and ciliary body were obtained from cornea donors and prepared for cryosectioning. Cross sections of tissue blocks at 12/3/6/9 o'clock position and at corresponding intersections (1:30/4:30/7:30/10:30) were processed for immunohistochemistry of LYVE-1, PDPN, PROX1, FOXC2, VEGFR3, and CCL21, and when necessary, these lymphatic markers were combined with CD31, alpha-smooth muscle-actin, CD68, and 4',6-diamidino-2 phenylindole dihydrochloride (DAPI). Double, triple, and quadruple marker combinations were documented using confocal microscopy. RESULTS. Numerous podoplanin+ cells were mainly located at the anterior border of the iris while LYVE-1+ cells were distributed throughout the nonpigmented part. Both cell populations were PROX1/FOXC2/CCL21/VEGFR3-. Blood vessels, iris smooth muscles, and individual cells were VEGFR3+. While PDPN+ cells were rarely detected posteriorly of the iris root, many LYVE1+ cells were present within the ciliary body muscle and villi. Within the muscle, occasionally PDPN+ vessel-like structures were detectable, but these were never colocalized with LYVE-1. Similar vessel-like structures were VEGFR3+/PROX1-/CCL21-, but CD31+. Further, ciliary muscle fibers and ciliary epithelium were immunoreactive for VEGFR3/CCL21, but were LYVE1/PDPN-. A certain topography of structures at the various uvea-positions investigated was not obvious. The majority of LYVE-1+ cells displayed immunoreactivity for CD68. CONCLUSIONS. Lymphatic vessels colocalizing for at least two lymphatic markers were not detectable. Therefore, if present, putative lymphatic channels of the anterior uvea might display a different marker panel than generally presumed.

PURPOSE. Reports of lymphatics in the posterior human uvea are contradictory. We systematically analyzed the choroid by combining various lymphatic markers, following recently established guidelines for the immunohistochemical detection of ocular lymphatics. METHODS. Human choroids were prepared for flat mount serial cryosectioning. Sections were processed for immunohistochemistry of the lymphatic markers LYVE-1, PDPN, PROX1, FOXC2, VEGFR3, CCL21, and combined with alpha-smooth muscle-actin and 40,6-diamidino-2-phenylendole (DAPI). Single, double, and triple marker combinations were documented using confocal microscopy. Messenger RNA analysis for CCL21, FOXC2, LYVE-1, PDPN, PROX, and VEGFR3 was performed in choroid and skin. RESULTS. In the choroid, CCL21 immunoreactivity was detected in choroidal blood vessels, intrinsic choroidal neurons, and numerous small cells of the choroidal stroma. These small cells were not colocalized with PROX1 and PDPN, while a subpopulation of cells showed immunoreactivity for CCL21 and LYVE-1, and very occasionally PDPN-only+ cells were detected. Nuclei positive for PROX1 were never detected in the choroid, and vessel-like structures immunoreactive for LYVE-1, PDPN, or CCL21 (other than blood vessels) were never observed. Immunoreactivity of VEGFR3 was absent in the majority of choroidal blood vessels, but present in choriocapillaris, while other structures positive for VEGFR3 were not detected. Nonvascular smooth muscle cells were lacking VEGFR3-immunoreactivity. Messenger RNA analysis detected all lymphatic markers investigated and confirmed immunohistochemical results. CONCLUSIONS. By combining several lymphatic markers, single cells expressed these markers, but classical lymphatic vessels were not detected in the human choroid. Therefore, the healthy adult human choroid must be considered alymphatic, at least with the markers applied here.