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Effective conservation requires understanding species’ abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities because variation in species’ dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates of communities of species is often prohibitively time intensive and expensive. We developed a multispecies dynamicN‐occupancy model to estimate unbiased, community‐wide relative abundance and demographic rates. In this model, detection–nondetection data (e.g., repeated presence–absence surveys) are used to estimate species‐ and community‐level parameters and the effects of environmental factors. To validate our model, we conducted a simulation study to determine how and when such an approach can be valuable and found that our multispecies model outperformed comparable single‐species models in estimating abundance and demographic rates in many cases. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest‐dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species’ local population. The antelope community was fairly stable (although 17% of populations [species–park combinations] declined over the study period). Variation in apparent survival was linked more closely to differences among national parks than to individual species’ life histories. The multispecies dynamicN‐occupancy model requires only detection–nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for examining the reasons behind recent biodiversity loss.

 

The ability to interface microfluidic devices with native complex biological architectures, such as whole organs, has the potential to shift the paradigm for the study and analysis of biological tissue. Here, we show 3D printing can be used to fabricate bio-inspired conformal microfluidic devices that directly interface with the surface of whole organs. Structured-light scanning techniques enabled the 3D topographical matching of microfluidic device geometry to porcine kidney anatomy. Our studies show molecular species are spontaneously transferred from the organ cortex to the conformal microfluidic device in the presence of fluid flow through the organ-conforming microchannel. Large animal studies using porcine kidneys ( n = 32 organs) revealed the profile of molecular species in the organ-conforming microfluidic stream was dependent on the organ preservation conditions. Enzyme-linked immunosorbent assay (ELISA) studies revealed conformal microfluidic devices isolate clinically relevant metabolic and pathophysiological biomarkers from whole organs, including heat shock protein 70 (HSP-70) and kidney injury molecule-1 (KIM-1), which were detected in the microfluidic device as high as 409 and 12 pg mL −1 , respectively. Overall, these results show conformal microfluidic devices enable a novel minimally invasive ‘microfluidic biopsy’ technique for isolation and profiling of biomarkers from whole organs within a clinically relevant interval. This achievement could shift the paradigm for whole organ preservation and assessment, thereby helping to relieve the organ shortage crisis through increased availability and quality of donor organs. Ultimately, this work provides a major advance in microfluidics through the design and manufacturing of organ-conforming microfluidic devices and a novel technique for microfluidic-based analysis of whole organs.