NetGAM: Using generalized additive models to improve the predictive power of ecological network analyses constructed using time-series data

Ecological network analyses are used to identify potential biotic interactions between microorganisms from species abundance data. These analyses are often carried out using time-series data; however, time-series networks have unique statistical challenges. Time-dependent species abundance data can lead to species co-occurrence patterns that are not a result of direct, biotic associations and may therefore result in inaccurate network predictions. Here, we describe a generalize additive model (GAM)-based data transformation that removes time-series signals from species abundance data prior to running network analyses. Validation of the transformation was carried out by generating mock, time-series datasets, with an underlying covariance structure, running network analyses on these datasets with and without our GAM transformation, and comparing the network outputs to the known covariance structure of the simulated data. The results revealed that seasonal abundance patterns substantially decreased the accuracy of the inferred networks. Additionally, the GAM transformation increased the F1 score of inferred ecological networks on average and improved the ability of network inference methods to capture important features of network structure. This study underscores the importance of considering temporal features when carrying out network analyses and describes a simple, effective tool that can be used to improve results.

DIVERSITY OF MOLLUSCA BIVALVIA ALONG THE BEACHES SAND OF KARANG MAS, MUARA GADING MAS, MARINGGAI REGENCY, EAST OF LAMPUNG

East Lampung Regency has a coastal area of East Lampung with 316 ha. One of the coastal tourist areas owned by East Lampung Regency is Shells Mas Beach. This beach has a fairly long coastline where there are a lot of bivalves, but the inventory of the types of bivalves on the beach.The purpose of the research is to analyze both the species diversities of bivalves and physical also chemical conditions of the waters. The research methodology used purposive sampling method analysis of species abundance data, diversity index, and index dominance. From the result of the bivalve diversities on the coast, bivalve the most common found are is Matra grandis,it is found out that there is no dominating bivalve amongst them due to below normal dominating rate that is 0,08-0,16 to be considered low level (00,00<C≤0,30); middle with diversity index 2,18–2,70 (2<H’≤3); high with index diversity 0,85–0,94 (E>0,6). The highest abundance value at station 1 is 4787.01 ind/m3 and the lowest species abundance value at station 3 is138.75 ind/m3. From the results of the chemical physics measurements, it shows that it still is in the range of sea water quality standards. The Bivalve diversity relationship shows a positive correlation to the parameters of salinity, grain size, and sediment TSS. Meanwhile, it shows negative correlation for parameters DO, pH and temperature.

The Subhabitat Dependence of Biogeographic Pattern

We introduce and test the subhabitat dependence hypothesis (SDH) in biogeography. This hypothesis posits that biogeographic pattern within a region differs when determined with species abundance data from different subhabitat types. It stems from the notion that the main abiotic factors that drive species distribution in different subhabitat types across a biogeographic region often vary differently across space. To test the SDH, we measured the abundance of algae and sessile invertebrates in two different subhabitats (high intertidal zone and mid-intertidal zone) at eight locations along the Atlantic Canadian coast. We conducted multivariate analyses of the species abundance data to compare alongshore biogeographic pattern between both zones. For both subhabitat types, location groupings based on community similarity not always responded to geographic proximity, leading to biogeographic patchiness to some extent. Nonetheless, both biogeographic patterns were statistically unrelated, thus supporting the SDH. This lack of concordance was most evident for southern locations, which clustered together based on high-intertidal data but showed considerable alongshore patchiness based on mid-intertidal data. We also found that the ordination pattern of these eight locations based on sea surface temperature data was significantly related to biogeographic pattern for the mid-intertidal zone but not for the high intertidal zone. This finding supports the rationale behind the SDH due to the longer periods of submergence experienced by the mid-intertidal zone. Overall, we conclude that biogeographic pattern within a region can depend on the surveyed subhabitat type. Thus, biological surveys restricted to specific subhabitats may not properly reveal biogeographic pattern for a biota as a whole or even just for other subhabitats. As many studies generate biogeographic information with data only for specific subhabitats, we recommend testing the SDH in other systems to determine its domain of application.

Evaluation of the estimate bias magnitude of the Rao’s quadratic diversity index

Rao’s quadratic diversity index is one of the most widely applied diversity indices in functional and phylogenetic ecology. The standard way of computing Rao’s quadratic diversity index for an ecological assemblage with a group of species with varying abundances is to sum the functional or phylogenetic distances between a pair of species in the assemblage, weighted by their relative abundances. Here, using both theoretically derived and observed empirical datasets, we show that this standard calculation routine in practical applications will statistically underestimate the true value, and the bias magnitude is derived accordingly. The underestimation will become worse when the studied ecological community contains more species or the pairwise species distance is large. For species abundance data measured using the number of individuals, we suggest calculating the unbiased Rao’s quadratic diversity index.

A ~6000 yr diatom record of mid- to late Holocene fluctuations in the level of Lago Wiñaymarca, Lake Titicaca (Peru/Bolivia)

A multidecadal-scale lake-level reconstruction for Lago Wiñaymarca, the southern basin of Lake Titicaca, has been generated from diatom species abundance data. These data suggest that ~6500 cal yr BP Lago Wiñaymarca was dry, as indicated by a sediment unconformity. At ~4400 cal yr BP, the basin began to fill, as indicated by the dominance of shallow epiphytic species. It remained somewhat saline with extensive wetlands and abundant aquatic plants until ~3800 cal yr BP, when epiphytic species were replaced by planktic saline-indifferent species, suggesting a saline shallow lake. Wiñaymarca remained a relatively shallow lake that fluctuated on a multidecadal scale until ~1250 cal yr BP, when freshwater planktic species increased, suggesting a rise in lake level with a concomitant decrease in salinity. The lake became gradually fresher, dominated by deep, freshwater species from ~850 cal yr BP. By ~80 cal yr BP, saline-tolerant species were rare, and the lake was dominated by freshwater planktic diatoms, resembling the fresh and deep lake of today. These results reveal a more dynamic and chronologically specific record of lake-level fluctuations and associated ecological conditions that provide important new data for paleoclimatologists and archaeologists, to better understand human-environmental dynamics during the mid- to late Holocene.