Cannot see the diversity for all the species: Evaluating inclusion criteria for local species lists when using abundant citizen science data

Abundant citizen science data on species occurrences are becoming increasingly available and enable identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands, we investigated the sensitivity of α‐ and β‐diversity estimates to the use raw versus detection‐corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested seven inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence‐only observation data are abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based α‐ and β‐diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: The large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.     

Length-weight relationship of fish species captured around an artificial offshore reef (northern Rio de Janeiro,Brazil)

The present work provides length-weight relationships (LWRs) for fish species captured around artificial offshore reef deployed 5 km from Guaxindiba Port, northern Rio de Janeiro, Brazil. The fish were captured during two sampling periods each year between 1996 and 2017 using bottom gill nets (25 m_length × 3 m_depth; 30 mm mesh). The fish were kept on ice and the biometric data, including total length (cm) and total wet weight (g) were determined in the laboratory. A total of 16 species belonging to 10 families were analyzed with Sciaenidae being the species richest family (5 spp) in the samples. The new value of LWRs for Sphyraena guachancho and new maximum sizes recorded for seven species highlight the scarcity of information on biological aspects of South America coastal fishes. These LWRs should assist fisheries scientist and managers to complement their further studies of population parameters to improve management decisions.     

Large vertical movements by a goosefish,Lophius americanus,suggests the potential of data storage tags for behavioral studies of benthic fishes

The extensive periodic vertical movements of up to 14 h and 209 m observed in this study for an individual goosefish, Lophius americanus, challenges previous assumptions about the benthic and highly sedentary behavior of the species as well as of other lophiids. Researchers should consider conducting similar data storage tagging studies with other benthic fishes to test assumptions of sedentary behavior.     

Comparative analysis of bone remodelling models with respect to computerised tomography-based finite element models of bone

Subject-specific finite element models are an extensively used tool for the numerical analysis of the biomechanical behaviour of human bones. However, bone modelling is not an easy task due to the complex behaviour of bone tissue, involving non-homogeneous and anisotropic mechanical properties. Moreover, bone is a living tissue and therefore its microstructure and mechanical properties evolve with time in a known process called bone remodelling. This phenomenon has been widely studied, many being the numerical models that have been formulated to predict density distribution and its evolution in several bones. The aim of the present study is to assess the capability of a bone remodelling model to predict the bone density distribution of different types of human bone (femur, tibia and mandible) comparing the obtained results with the bone density estimated by means of computerised tomography. Good accuracy was observed for the bone remodelling predictions including the thickness of the cortical layer.     

Development of tree-ring maximum latewood density chronologies for the western Tien Shan Mountains,China: Influence of detrending method and climate response

Three tree-ring maximum latewood density chronologies were developed from high elevation Picea schrenkiana sites in the western Tien Shan Mountains using different detrending methods. The new chronologies extend back to the early 16th and late 17th centuries, and contain significant late spring and summer temperature signals, respectively. An assessment of varying detrending methods and band-pass filtering the chronologies revealed only slightly differing low frequency trends retained in the maximum latewood densities. The distance between sampling sites and the varying seasonality of limiting climatic factors are identified as key drivers affecting the correlation among the maximum latewood density records in the study region. The new chronologies represent reliable proxies of high elevation late spring and summer temperature variability in an area underrepresented by such data, and are ready-to-use for network analyses addressing longer-term climate variations in eastern central Asia.     

Efficient rescue of threatened biodiversity data using reBiND workflows

Abstract

Biodiversity data generated in the context of research projects often lack a strategy for long-term preservation and availability, and are therefore at risk of becoming outdated and finally lost. The reBiND project aims to develop an efficient and well-documented workflow for rescuing such data sets. The workflow consists of phases for data transformation into contemporary standards, data validation, storage in a native XML database, and data publishing in international biodiversity networks. It has been developed and tested using the example of collection and observational data but is flexible enough to be transferred to other data types and domains.