Modelling temperature-driven changes in species associations across freshwater communities.

Due to global climate change-induced shifts in species distributions, estimating changes in community composition through the use of Species Distribution Models has become a key management tool. Being able to determine how species associations change along environmental gradients is likely to be pivotal in exploring the magnitude of future changes in species' distributions. This is particularly important in connectivity-limited ecosystems, such as freshwater ecosystems, where increased human translocation is creating species associations over previously unseen environmental gradients. Here, we use a large-scale presence-absence dataset of freshwater fish from lakes across the Fennoscandian region in a Joint Species Distribution Model, to measure the effect of temperature on species associations. We identified a trend of negative associations between species tolerant of cold waters and those tolerant of warmer waters, as well as positive associations between several more warm-tolerant species, with these associations often shifting depending on local temperatures. Our results confirm that freshwater ecosystems can expect to see a large-scale shift towards communities dominated by more warm-tolerant species. While there remains much work to be done to predict exactly where and when local extinctions may take place, the model implemented provides a starting-point for the exploration of climate-driven community trends. This approach is especially informative in regards to determining which species associations are most central in shaping future community composition, and which areas are most vulnerable to local extinctions.

Analyzing dynamic species abundance distributions using generalized linear mixed models.

Understanding the mechanisms of ecological community dynamics and how they could be affected by environmental changes is important. Population dynamic models have well known ecological parameters that describe key characteristics of species such as the effect of environmental noise and demographic variance on the dynamics, the long-term growth rate, and strength of density regulation. These parameters are also central for detecting and understanding changes in communities of species; however, incorporating such vital parameters into models of community dynamics is challenging. In this paper, we demonstrate how generalized linear mixed models specified as intercept-only models with different random effects can be used to fit dynamic species abundance distributions. Each random effect has an ecologically meaningful interpretation either describing general and species-specific responses to environmental stochasticity in time or space, or variation in growth rate and carrying capacity among species. We use simulations to show that the accuracy of the estimation depends on the strength of density regulation in discrete population dynamics. The estimation of different covariance and population dynamic parameters, with corresponding statistical uncertainties, is demonstrated for case studies of fish and bat communities. We find that species heterogeneity is the main factor of spatial and temporal community similarity for both case studies.

A re-analysis of NH4+ sorption on biochar: Have expectations been too high?

Sorption of nutrients such as NH4+ is often quoted as a critical property of biochar, explaining its value as a soil amendment and a filter material. However, published values for NH4+ sorption to biochar vary by more than 3 orders of magnitude, without consensus as to the source of this variability. This lack of understanding greatly limits our ability to use quantitative sorption measurements towards product design. Here, our objective was to conduct a quantitative analysis of the sources of variability, and infer which biochar traits are more favourable to high sorption capacity. To do so, we conducted a standardized remodelling exercise of published batch sorption studies using Langmuir sorption isotherm. We excluded studies presenting datasets that either could not be reconciled with the standard Langmuir sorption isotherm or generated clear outliers. Our analysis indicates that the magnitude of sorption capacity of unmodified biochar for NH4+ is lower than previously reported, with a median of 4.2 mg NH4+ g-1 and a maximum reported sorption capacity of 22.8 mg NH4+ g-1. Activation resulted in a significant relative improvement in sorption capacity, but absolute improvements remain modest, with a maximum reported sorption of 27.56 mg NH4+ g-1 for an activated biochar. Methodology appeared to substantially impact sorption estimates, especially practices such as pH control of batch sorption solution and ash removal. Our results highlight some significant challenges in the quantification of NH4+ sorption by biochar and our curated data set provides a potentially valuable scale against which future estimates can be assessed.