https://www.cs.princeton.edu/~schapire/papers/ecolmod.pdf

Maximum entropy modeling of species geographic distributions

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

/pdf/experimental-design-and-data-analysis-for-biologists-8ybva8d53x.pdf

Experimental Design and Data Analysis for Biologists

Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

/pdf/novel-methods-improve-prediction-of-species-distributions-3cmioqeu6v.pdf

Novel methods improve prediction of species' distributions from occurrence data

Dengue is a systemic viral infection transmitted between humans by Aedes mosquitoes. For some patients, dengue is a life-threatening illness. There are currently no licensed vaccines or specific therapeutics, and substantial vector control efforts have not stopped its rapid emergence and global spread. The contemporary worldwide distribution of the risk of dengue virus infection and its public health burden are poorly known. Here we undertake an exhaustive assembly of known records of dengue occurrence worldwide, and use a formal modelling framework to map the global distribution of dengue risk. We then pair the resulting risk map with detailed longitudinal information from dengue cohort studies and population surfaces to infer the public health burden of dengue in 2010. We predict dengue to be ubiquitous throughout the tropics, with local spatial variations in risk influenced strongly by rainfall, temperature and the degree of urbanization. Using cartographic approaches, we estimate there to be 390 million (95% credible interval 284-528) dengue infections per year, of which 96 million (67-136) manifest apparently (any level of disease severity). This infection total is more than three times the dengue burden estimate of the World Health Organization. Stratification of our estimates by country allows comparison with national dengue reporting, after taking into account the probability of an apparent infection being formally reported. The most notable differences are discussed. These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue. We anticipate that they will provide a starting point for a wider discussion about the global impact of this disease and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.

/pdf/the-global-distribution-and-burden-of-dengue-4d1crnic4u.pdf

The global distribution and burden of dengue

https://www.wsl.ch/staff/niklaus.zimmermann/papers/ecomod135_147.pdf

Predictive habitat distribution models in ecology

Generalized additive models (GAMs) are a non- parametric extension of generalized linear models (GLMs). They are introduced here as an exploratory tool in the analysis of species distributions with respect to climate. An important result is that the long-debated question of whether a response curve, in one dimension, is actually symmetric and bell- shaped or not, can be tested using GAMs. GAMs and GLMs are discussed and are illustrated by three examples using binary data. A grey-scale plot of one of the fits is constructed to indicate which areas on a map seem climatically suitable for that species. This is useful for species introductions. Further applications are mentioned.

Generalized additive models in plant ecology

Microclimate and vegetation edge effects in a fragmented podocarp-broadleaf forest in New Zealand

▪ Abstract Conservation in New Zealand is failing to halt an ongoing decline in biodiversity. Classical problems of ecosystem loss and fragmentation have largely been countered in some regions by reservation of 30% of total land area. Unsustainable harvesting of native biodiversity has stopped; indeed harvesting of terrestrial species is rare. In contrast, marine reserves do not cover even 1% of the managed area, and harvest of native species, some of it unsustainable, are a major industry. Introduced pests, especially mammals, are the overwhelming conservation problem. Legislation, management, and considerable public opinion is based on preservationist ideals that demand the sanctity of native land biodiversity. Considerable success in threatened species management, island eradications, and mainland control of pests is increasing opportunities for restoration. New legislation is increasingly built on concepts of sustainability and offers the opportunity for integrating conservation, use, and development....

Conservation Issues in New Zealand

Modelling techniques based on Laplacian smoothing splines were used to derive climate trend surfaces for each of four parameters: monthly mean rainfall, minimum temperature, maximum temperature and solar radiation. The use of analytical procedures, based on the program BIOCLIM, are described; these allow the estimation of climate parameters at individual locations from the trend surfaces. These techniques were used to analyse the geographic distribution of kauri with respect to contemporary climate. For each location where kauri has been recorded, an estimate was made of various climate parameters, which by summation allowed the derivation of a ‘climate profile’. This profile may be considered a multivariate definition of the climatic regime within which the species now grows. To analyse the role of climate in determining the geographic distribution of kauri, each location in a North Island database was tested against the profile, to assess whether it could support kauri growth. There was a close...

https://www.tandfonline.com/doi/pdf/10.1080/03036758.1991.10416106

The derivation of climate surfaces for New Zealand, and their application to the bioclimatic analysis of the distribution of kauri (Agathis australis)

. A quantitative study of relationships between forest pattern and environment in the central North Island, New Zealand, is based on forest composition data from ca. 2000 existing plots distributed throughout the forests of the region. Estimates of mean annual temperature, rainfall, and solar radiation are derived for each plot from mathematical surfaces fitted to climate station data. Estimates of the depth of the last major rhyolitic eruption, (Taupo Pumice, ca. 130 AD) are derived from isopach maps. A classification procedure is used to identify broad compositional groups. Generalised linear models are used to examine relationships between major species and climatic and other physical factors. Significant relationships are identified between the distributions of both plot groups and species, and climate, vulcanism, topography and drainage. Among these factors, temperature and/or solar radiation are indicated as major determinants of the regional forest pattern, with rainfall, topography, and drainage acting at a secondary level. The role of the Taupo Pumice eruption is more difficult to interpret, and its effects seem to have been greatly influenced by topography. Deep extensive deposits of tephra on flat-to-rolling sites close to the eruption centre have probably favoured the current dominance of these sites by more rapidly dispersing conifers. In contrast, on adjacent steep sites where forest destruction was likely to be less severe, slow-dispersing Nothofagus species are largely dominant. Further work is needed to understand the factors favouring conifer dominance of the central basins and the degree to which Nothofagus species might expand their range in the future.

Neil Mitchell

Papers

Generalized additive models in plant ecology

Microclimate and vegetation edge effects in a fragmented podocarp-broadleaf forest in New Zealand

Conservation Issues in New Zealand

The derivation of climate surfaces for New Zealand, and their application to the bioclimatic analysis of the distribution of kauri (Agathis australis)

Forest pattern, climate and vulcanism in central North Island, New Zealand