Biology subjects

Seddon, A. W. R.

Publications and source records attributed to Seddon, A. W. R..

4 recordsLinked to original sources

bioRxiv2024

: A tool for modelling ecosystem resilience

AimsA number of modelling frameworks exist to aid in the identification and exploration of stable states and the assessment of resilience from ecological datasets. However, because such models are complex to implement there is a substantial barrier for the application in ecological research. Here we develop a flexible model of ecological resilience based on Bayesian approximation of the "stability landscape". We illustrate its usage on a tropical area where variation in tree cover has been previously interpreted as alternative stable states. MethodsThe stability landscape, from which stable states and resilience parameters are computed, is modelled using a mixture of multiple distributions, each representing a regression between the system state variable and the environmental covariates. Our "mixglm" model allows the mean, precision, and probability parameters of these distributions in the landscape to be dependent on multiple external covariates. "Mixglm" is implemented as a function in R package with the same name, internally using Bayesian inference via NIMBLE. We also conducted a power analysis to provide guidance regarding required sample size. ResultsWe illustrate the use of the "mixglm" on a published case of tree cover in South America which reports a stability landscape with three distinct stable states. Using "mixglm", we were able to replicate the identification of these states. Moreover, we quantified uncertainty of our estimates, and computed resilience of South Americas forests. Conclusions"Mixglm" can be readily used for description of stability landscapes and identification of stable states in most spatial datasets of system state variables, and it is accompanied by tools for calculation of resilience metrics. It can also be further expanded using regression framework to account for more complex data structures such as spatio-temporal data.

ecology↗

bioRxiv2022

Long-term ecological responses of a Dipterocarp forest to climate changes and nutrient availability

O_LIUnderstanding the long-term impact of projected climate change on tropical rainforests is critical given their central role in the Earths system. Palaeoecological records can provide a valuable perspective on this problem. Here we examine for the first time the effects of past climatic changes on the dominant forest type of Southeast Asia - Dipterocarp forest. C_LIO_LIWe use a range of proxies extracted from a 1,400-year-old lacustrine sedimentary sequence from north-eastern Philippines to model long-term vegetation responses of Dipterocarp forest, including its dominant tree group Dipterocarps, to changes in precipitation, fire and nutrient availability over time. C_LIO_LIOur results show a positive relationship between Dipterocarps pollen accumulation rates (PARs) and leaf wax hydrogen isotope values, which suggests a negative effect of drier conditions on Dipterocarp tree abundance. Furthermore, we find a positive relationship between Dipterocarp PARs and the proxy for phosphorus availability, which suggests phosphorus controls the productivity of these keystone trees on longer time scales. Other plant taxa show widely varying relationships with the abiotic factors, demonstrating a high diversity of functional responses. C_LIO_LIOur findings provide novel insights into Dipterocarp forest responses to changing climatic conditions in the past, and highlight potential impacts of future climate change on this globally important ecosystem. C_LI

ecology↗

bioRxiv2020

Rate-of-change analysis in palaeoecology revisited: a new approach

AO_SCPLOWBSTRACTC_SCPLOWDynamics in the rate of compositional change (rate-of-change; RoC) of biotic or abiotic assemblages preserved in palaeoecological sequences, are thought to reflect changes due to exogenous drivers such as climate and human forcing as well as endogenous factors linked to local dynamics and biotic interactions. However, changes in sedimentation rates and sampling strategies can result in an uneven distribution of time intervals and are known to affect RoC estimates. Furthermore, there has been relatively little exploration of the implications of these challenges in quantifying RoC in palaeoecology. Here, we introduce R-Ratepol - an easy-to-use R package - that provides a robust numerical technique for detecting and summarising RoC patterns in complex multivariate time-ordered stratigraphical sequences. First, we compare the performance of common methods of estimating RoC and detecting periods of high RoC (peak-point) using simulated pollen-stratigraphical data with known patterns of compositional change and temporal resolution. In addition, we propose a new method of binning with a moving window, which shows a more than 5-fold increase in the correct detection of peak-points compared to the more traditional way of using individual levels. Next, we apply our new methodology to four representative European pollen sequences and show that our approach also performs well in detecting periods of significant compositional change during known onsets of human activity, early land-use transformation, and changes in fire frequency. Expanding the approach using R-Ratepol to open-access paleoecological datasets in global databases, such as Neotoma, will allow future palaeoecological and macroecological studies to quantify major changes in biotic composition or in sets of abiotic variables across broad spatio-temporal scales.

ecology↗

bioRxiv2019

Chemical variations in Quercus pollen as a tool for taxonomic identification: implications for long-term ecological and biogeographic research

vi.AimFossil pollen is an important tool for understanding biogeographic patterns in the past, but the taxonomic resolution of the fossil-pollen record may be limited to genus or even family level. Chemical analysis of pollen grains has the potential to increase the taxonomic resolution of pollen, but present-day chemical variability is poorly understood. This study aims to investigate whether a phylogenetic signal is present in the chemical variations of Quercus L. pollen and to assess the prospects of chemical techniques for identification in biogeographic research. LocationPortugal TaxonSix taxa (five species, one subspecies) of Quercus L., Q. faginea, Q. robur, Q. robur ssp. estremadurensis, Q. coccifera, Q. rotundifolia and Q. suber belonging to three sections: Cerris, Ilex, and Quercus (Denk, Grimm, Manos, Deng, & Hipp, 2017) MethodsWe collected pollen samples from 297 individual Quercus trees across a 4{degrees} ([~]450 km) latitudinal gradient and determined chemical differences using Fourier-transform infrared spectroscopy (FTIR). We used canonical powered partial least-squares regression (CPPLS) and discriminant analysis to describe within- and between-species chemical variability. ResultsWe find clear differences in the FTIR spectra from Quercus pollen at the section level (Cerris: [~]98%; Ilex: [~]100%; Quercus: [~]97%). Successful discrimination is based on spectral signals related to lipids and sporopollenins. However, discrimination of species within individual Quercus sections is more difficult: overall, species recall is [~]76% and species misidentifications within sections lie between 18% and 31% of the test-set. Main ConclusionsOur results demonstrate that subgenus level differentiation of Quercus pollen is possible using FTIR methods, with successful classification at the section level. This indicates that operator-independent FTIR approaches can surpass traditional morphological techniques using the light microscope. Our results have implications both for providing new insights into past colonisation pathways of Quercus, and likewise for forecasting future responses to climate change. However, before FTIR techniques can be applied more broadly across palaeoecology and biogeography, our results also highlight a number of research challenges that still need to be addressed, including developing sporopollenin-specific taxonomic discriminators and determining a more complete understanding of the effects of environmental variation on pollen-chemical signatures in Quercus.

ecology↗