Changing patterns of eastern Mediterranean shellfish exploitation in the Late Glacial and Early Holocene: Oxygen isotope evidence from gastropod in Epipaleolithic to Neolithic human occupation layers at the Haua Fteah cave, Libya

The seasonal pattern of shellfish foraging at the archaeological site of Haua Fteah in the Gebel Akhdar, Libya was investigated from the Epipaleolithic to the Neolithic via oxygen isotope (d18O) analyses of the topshell Phorcus (Osilinus) turbinatus. To validate this species as faithful year-round palaeoenvironmental recorder, the intra-annual variability of d18O in modern shells and sea water was analysed and compared with measured sea surface temperature (SST). The shells were found to be good candidates for seasonal shellfish forging studies as they preserve nearly the complete annual SST cycle in their shell d18O with minimal slowing or stoppage of growth. During the terminal Pleistocene Early Epipaleolithic (locally known as the Oranian, with modeled dates of 17.2-12.5 ka at 2sigma probability, Douka et al., 2014), analysis of archaeological specimens indicates that shellfish were foraged year-round. This complements other evidence from the archaeological record that shows that the cave was more intensively occupied in this period than before or afterwards. This finding is significant as the period of the Oranian was the coldest and driest phase of the last glacial cycle in the Gebel Akhdar, adding weight to the theory that the Gebel Akhdar may have served as a refugium for humans in North Africa during times of global climatic extremes. Mollusc exploitation in the Latest Pleistocene and Early Holocene, during the Late Epipaleolithic (locally known as the Capsian, c. 12.7 to 9 ka) and the Neolithic (c. 8.5 to 5.4 ka), occurred predominantly during winter. Other evidence from these archaeological phases shows that hunting activities occurred during the warmer months. Therefore, the timing of Holocene shellfish exploitation in the Gebel Akhdar may have been influenced by the seasonal availability of other resources at these times and possibly shellfish were used as a dietary supplement when other foods were less abundant

The contribution of other effective area-based conservation measures (OECMs) to protecting global biodiversity

Abstract Nations recently agreed to set aside 30% of the planet by 2030 as conservation areas (the “30 × 30” goal) necessitating major expansions, not just of traditional protected areas like national parks, but also of ‘other effective area-based conservation measures’ (OECMs) – areas that provide de facto benefits to biodiversity despite conservation not being the primary management objective. But evidence for whether OECMs achieve positive biodiversity outcomes remains critically needed. Here we quantify how OECMs contribute to biodiversity conservation in the three high-biodiversity countries in which they have been extensively trialed. OECM performance varies across countries; those in South Africa align better with areas that a priori strategic planning identified as important for species conservation and key ecosystem services than those in Colombia and the Philippines. OECMs tend not to cover areas supporting regional connectivity in any of the countries. OECMs have potential to assist conservation, but policy, planning, and coordination at national and international levels would help ensure that new OECMs are strategically established and effectively managed to enhance outcomes for biodiversity conservation and ecosystem service provisioning

The contribution of other effective areabased conservation measures (OECMs) to protecting global biodiversity

Nations recently agreed to set aside 30% of the planet by 2030 as conservation areas (the “30 × 30” goal) necessitating major expansions, not just of traditional protected areas like national parks, but also of ‘other effective areabased conservation measures’ (OECMs) – areas that provide de facto benefits to biodiversity despite conservation not being the primary management objective. But evidence for whether OECMs achieve positive biodiversity outcomes remains critically needed. Here we quantify how OECMs contribute to biodiversity conservation in the three high-biodiversity countries in which they have been extensively trialed. OECM performance varies across countries; those in South Africa align better with areas that a priori strategic planning identified as important for species conservation and key ecosystem services than those in Colombia and the Philippines. OECMs tend not to cover areas supporting regional connectivity in any of the countries. OECMs have potential to assist conservation, but policy, planning, and coordination at national and international levels would help ensure that new OECMs are strategically established and effectively managed to enhance outcomes for biodiversity conservation and ecosystem service provisioning

Landscape-scale benefits of protected areas for tropical biodiversity

The United Nations recently agreed to major expansions of global protected areas (PAs) to slow biodiversity declines. However, although reserves often reduce habitat loss, their efficacy at preserving animal diversity and their influence on biodiversity in surrounding unprotected areas remain unclear. Unregulated hunting can empty PAs of large animals6, illegal tree felling can degrade habitat quality, and parks can simply displace disturbances such as logging and hunting to unprotected areas of the landscape (a phenomenon called leakage). Alternatively, well-functioning PAs could enhance animal diversity within reserves as well as in nearby unprotected sites (an effect called spillover). Here we test whether PAs across mega-diverse Southeast Asia contribute to vertebrate conservation inside and outside their boundaries. Reserves increased all facets of bird diversity. Large reserves were also associated with substantially enhanced mammal diversity in the adjacent unprotected landscape. Rather than PAs generating leakage that deteriorated ecological conditions elsewhere, our results are consistent with PAs inducing spillover that benefits biodiversity in surrounding areas. These findings support the United Nations goal of achieving 30% PA coverage by 2030 by demonstrating that PAs are associated with higher vertebrate diversity both inside their boundaries and in the broader landscape

Landscape-scale benefits of protected areas for tropical biodiversity

The United Nations recently agreed to major expansions of global protected areas (PAs) to slow biodiversity declines1. However, although reserves often reduce habitat loss, their efficacy at preserving animal diversity and their influence on biodiversity in surrounding unprotected areas remain unclear2,3,4,5. Unregulated hunting can empty PAs of large animals6, illegal tree felling can degrade habitat quality7, and parks can simply displace disturbances such as logging and hunting to unprotected areas of the landscape8 (a phenomenon called leakage). Alternatively, well-functioning PAs could enhance animal diversity within reserves as well as in nearby unprotected sites9 (an effect called spillover). Here we test whether PAs across mega-diverse Southeast Asia contribute to vertebrate conservation inside and outside their boundaries. Reserves increased all facets of bird diversity. Large reserves were also associated with substantially enhanced mammal diversity in the adjacent unprotected landscape. Rather than PAs generating leakage that deteriorated ecological conditions elsewhere, our results are consistent with PAs inducing spillover that benefits biodiversity in surrounding areas. These findings support the United Nations goal of achieving 30% PA coverage by 2030 by demonstrating that PAs are associated with higher vertebrate diversity both inside their boundaries and in the broader landscape

Reply to: Causal claims, causal assumptions and protected area impact

In the accompanying Comment, Geldmann et al.1 incorrectly claim that protected area (PA) efficacy cannot be established without biodiversity data that predates establishment of the PA. Spatial correlates of diversity are known as a result of centuries of ecological research; our analyses controlled for these factors in a variety of ways in order to isolate the impacts of protection per se on bird and mammal biodiversity. The proposition of Geldmann et al. that our results are biased because PAs were established in areas with high natural biodiversity ignores these analytical controls, is naive to the realities of on-the-ground conservation, and has been disproved by recent research. Although we look forward to future work that improves on our predictions, our study provides robust estimates of the biodiversity impacts of PAs across hyperdiverse Southeast Asia2—information that is critically needed to support large-scale conservation objectives

The utility of dynamic forest structure from GEDI lidar fusion in tropical mammal species distribution models.

Remote sensing is an important tool for monitoring species habitat spatially and temporally. Species distribution models (SDM) often rely on remotely-sensed geospatial datasets to predict probability of occurrence and infer habitat preferences. Lidar measurements from the Global Ecosystem Dynamics Investigation (GEDI) are shedding light on three dimensional forest structure in regions of the world where this aspect of species habitat has previously been poorly quantified. Here we combine a large camera trap dataset of mammal species in Borneo and Sumatra with a diverse set of geospatial data to predict the probability of occurrence of 47 species. Multi-temporal GEDI predictors were created through fusion with Landsat time series, extending back to the year 2001. The availability of these GEDI-based forest structure predictors and other temporally-resolved predictor variables enabled temporal matching of species occurrences and hindcast predictions of species probability of occurrence at years 2001 and 2021. Our GEDI-Landsat fusion approach worked well for forest structure metrics related to canopy height (relative height of the 95th percentile of returned energy R2 = 0.62 and relative RMSE = 41%) but, not surprisingly, was less accurate for metrics related to interior canopy vegetation structure (e.g., plant area volume density from 0 to 5 m above the ground R2 = 0.05 and relative RMSE = 85%). For the SDM analyses, we tested several combinations of predictor sets and found that when considering a large pool of multiscale predictors, the exact composition, and whether GEDI Fusion predictors were included, didn’t have a large impact on generalized linear modeling (GLM) and Random Forest (RF) model performance. Adding GEDI Fusion predictors to a baseline set only meaningfully improved performance for some species (n = 4 for RF and n = 3 for GLM). However, when GEDI Fusion predictors were used in a smaller predictor set that is more suitable for hindcasting species probability of occurrence, more SDMs showed meaningful performance improvements relative to the baseline model (n = 9 for RF and n = 4 for GLM) and the relative importance of GEDI-based canopy structure predictors increased relative to when they were combined with the baseline predictor set. Moreover, as we examined predictor importance and partial dependence, the utility of GEDI Fusion predictors in hindcast models was evident in regards to ecological interpretability. We produced a catalog of probability of occurrence maps for all 47 mammals species at 90 m spatial resolution for years 2001 and 2021, enabling subsequent ecological interpretation and conservation analyses

CSF1R inhibitor JNJ-40346527 attenuates microglial proliferation and neurodegeneration in P301S mice

Neuroinflammation and microglial activation are significant processes in Alzheimer's disease pathology. Recent genome-wide association studies have highlighted multiple immune-related genes in association with Alzheimer's disease, and experimental data have demonstrated microglial proliferation as a significant component of the neuropathology. In this study, we tested the efficacy of the selective CSF1R inhibitor JNJ-40346527 (JNJ-527) in the P301S mouse tauopathy model. We first demonstrated the anti-proliferative effects of JNJ-527 on microglia in the ME7 prion model, and its impact on the inflammatory profile, and provided potential CNS biomarkers for clinical investigation with the compound, including pharmacokinetic/pharmacodynamics and efficacy assessment by TSPO autoradiography and CSF proteomics. Then, we showed for the first time that blockade of microglial proliferation and modification of microglial phenotype leads to an attenuation of tau-induced neurodegeneration and results in functional improvement in P301S mice. Overall, this work strongly supports the potential for inhibition of CSF1R as a target for the treatment of Alzheimer's disease and other tau-mediated neurodegenerative diseases

The utility of dynamic forest structure from GEDI lidar fusion in tropical mammal species distribution models

Remote sensing is an important tool for monitoring species habitat spatially and temporally. Species distribution models (SDM) often rely on remotely-sensed geospatial datasets to predict probability of occurrence and infer habitat preferences. Lidar measurements from the Global Ecosystem Dynamics Investigation (GEDI) are shedding light on three dimensional forest structure in regions of the world where this aspect of species habitat has previously been poorly quantified. Here we combine a large camera trap dataset of mammal species in Borneo and Sumatra with a diverse set of geospatial data to predict the probability of occurrence of 47 species. Multi-temporal GEDI predictors were created through fusion with Landsat time series, extending back to the year 2001. The availability of these GEDI-based forest structure predictors and other temporally-resolved predictor variables enabled temporal matching of species occurrences and hindcast predictions of species probability of occurrence at years 2001 and 2021. Our GEDI-Landsat fusion approach worked well for forest structure metrics related to canopy height (relative height of the 95th percentile of returned energy R2 = 0.62 and relative RMSE = 41%) but, not surprisingly, was less accurate for metrics related to interior canopy vegetation structure (e.g., plant area volume density from 0 to 5 m above the ground R2 = 0.05 and relative RMSE = 85%). For the SDM analyses, we tested several combinations of predictor sets and found that when considering a large pool of multiscale predictors, the exact composition, and whether GEDI Fusion predictors were included, didn’t have a large impact on generalized linear modeling (GLM) and Random Forest (RF) model performance. Adding GEDI Fusion predictors to a baseline set only meaningfully improved performance for some species (n = 4 for RF and n = 3 for GLM). However, when GEDI Fusion predictors were used in a smaller predictor set that is more suitable for hindcasting species probability of occurrence, more SDMs showed meaningful performance improvements relative to the baseline model (n = 9 for RF and n = 4 for GLM) and the relative importance of GEDI-based canopy structure predictors increased relative to when they were combined with the baseline predictor set. Moreover, as we examined predictor importance and partial dependence, the utility of GEDI Fusion predictors in hindcast models was evident in regards to ecological interpretability. We produced a catalog of probability of occurrence maps for all 47 mammals species at 90 m spatial resolution for years 2001 and 2021, enabling subsequent ecological interpretation and conservation analyses

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction: Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a \u201cHoly Grail\u201d of AD research and intensively sought; however, there are no well-established plasma markers. Methods: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. Results: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APO\u3b54 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). Discussion: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation