Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Predicting the distribution of endangered species from habitat data is frequently perceived to be a useful technique. Models that predict the presence or absence of a species are normally judged by the number of prediction errors. These may be of two types: false positives and false negatives. Many of the prediction errors can be traced to ecological processes such as unsaturated habitat and species interactions. Consequently, if prediction errors are not placed in an ecological context the results of the model may be misleading. The simplest, and most widely used, measure of prediction accuracy is the number of correctly classified cases. There are other measures of prediction success that may be more appropriate. Strategies for assessing the causes and costs of these errors are discussed. A range of techniques for measuring error in presence/absence models, including some that are seldom used by ecologists (e.g. ROC plots and cost matrices), are described. A new approach to estimating prediction error, which is based on the spatial characteristics of the errors, is proposed. Thirteen recommendations are made to enable the objective selection of an error assessment technique for ecological presence/absence models.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0376892997000088

A review of methods for the assessment of prediction errors in conservation presence/absence models

Aim: Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application across a range of biogeographical analyses. Some of the most promising applications relate to species for which occurrence records are scarce, due to cryptic habits, locally restricted distributions or low sampling effort. However, the minimum sample sizes required to yield useful predictions remain difficult to determine. Here we developed and tested a novel jackknife validation approach to assess the ability to predict species occurrence when fewer than 25 occurrence records are available. Location: Madagascar. Methods: Models were developed and evaluated for 13 species of secretive leaf-tailed geckos (Uroplatus spp.) that are endemic to Madagascar, for which available sample sizes range from 4 to 23 occurrence localities (at 1 km2 grid resolution). Predictions were based on 20 environmental data layers and were generated using two modelling approaches: a method based on the principle of maximum entropy (Maxent) and a genetic algorithm (GARP). Results: We found high success rates and statistical significance in jackknife tests with sample sizes as low as five when the Maxent model was applied. Results for GARP at very low sample sizes (less than c. 10) were less good. When sample sizes were experimentally reduced for those species with the most records, variability among predictions using different combinations of localities demonstrated that models were greatly influenced by exactly which observations were included. Main conclusions: We emphasize that models developed using this approach with small sample sizes should be interpreted as identifying regions that have similar environmental conditions to where the species is known to occur, and not as predicting actual limits to the range of a species. The jackknife validation approach proposed here enables assessment of the predictive ability of models built using very small sample sizes, although use of this test with larger sample sizes may lead to overoptimistic estimates of predictive power. Our analyses demonstrate that geographical predictions developed from small numbers of occurrence records may be of great value, for example in targeting field surveys to accelerate the discovery of unknown populations and species. © 2007 The Authors.

Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar

Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

/pdf/fast-tree-computing-large-minimum-evolution-trees-with-4grq0gwfpy.pdf

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Rates and reactions of biogeochemical processes vary in space and time to produce both hot spots and hot moments of elemental cycling. We define biogeochemical hot spots as patches that show disproportionately high reaction rates relative to the surrounding matrix, whereas hot moments are defined as short periods of time that exhibit disproportionately high reaction rates relative to longer intervening time periods. As has been appreciated by ecologists for decades, hot spot and hot moment activity is often enhanced at terrestrial-aquatic interfaces. Using examples from the carbon (C) and nitrogen (N) cycles, we show that hot spots occur where hydrological flowpaths converge with substrates or other flowpaths containing complementary or missing reactants. Hot moments occur when episodic hydrological flowpaths reactivate and/or mobilize accumulated reactants. By focusing on the delivery of specific missing reactants via hydrologic flowpaths, we can forge a better mechanistic understanding of the factors that create hot spots and hot moments. Such a mechanistic understanding is necessary so that biogeochemical hot spots can be identified at broader spatiotemporal scales and factored into quantitative models. We specifically recommend that resource managers incorporate both natural and artificially created biogeochemical hot spots into their plans for water quality management. Finally, we emphasize the needs for further research to assess the potential importance of hot spot and hot moment phenomena in the cycling of different bioactive elements, improve our ability to predict their occurrence, assess their importance in landscape biogeochemistry, and evaluate their utility as tools for resource management.

/pdf/biogeochemical-hot-spots-and-hot-moments-at-the-interface-of-1vpqinkleu.pdf

Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems

Vertical habitat segregation as a mechanism for coexistence in sympatric rodents

Goals and guidelines for managing oak ecosystems for wildlife.

Eld’s deer is an endangered species confined to dry forests of Southeast Asia. With the largest populations occurring in Myanmar, the Smithsonian Institution engaged the government and local organizations in conservation efforts. Nationwide, there has been a decline in both dry forest and deer distribution since the 1980s, despite the deer having national and international protected status. The deer persist in two national protected areas, Chatthin and Shwesettaw Wildlife Sanctuaries. From 1995 to 2005, the Smithsonian intensively upgraded facilities, staff capacity, and local education at Chatthin Wildlife Sanctuary and documented a marked rise in deer numbers. Following a 2005 pullout by the Smithsonian and a steep decline in international funds, deer populations at this reserve declined rapidly to below 1995 levels. This period coincided with a near complete loss of suitable habitat outside the reserve, repeated changes of reserve leadership, and emphasis on sustainable livelihoods for the surrounding communities rather than enforcement. At Shwesettaw Wildlife Sanctuary, chronically low deer densities and lack of funding were dramatically reversed with the influx of military personnel around a new military base established inside the reserve. The military presence resulted in extensive forest clearing and was protested heavily by the Smithsonian and other international organizations as detrimental to the deer. However, the immediate response in Shwesettaw Wildlife Sanctuary has been an increase in deer numbers. Whether examining the “soft diplomacy” of public engagement and increased staff capacity or the “hard enforcement” by the military, both demonstrated that the species can respond rapidly to management actions; but the sustainability of these population responses without further government agency investment is uncertain.

The Challenges of Protecting an Endangered Species in the Developing World: A Case History of Eld’s Deer Conservation in Myanmar

This document outlines procedures for surveying large terrestrial mammals at sites of CTFS-ForestGEO 3, a global network of large Forest Dynamics Plots (FDPs) in which all trees >1 cm diameter are mapped, tagged, identified and monitored. Large terrestrial mammals – here defined as mediumto large-sized mammals, with a body mass >1 kg that spend at least some portion of their daily cycle on ground – are a key component of tropical forest communities. For CTFS-ForestGEO, large mammals are of special interest because they influence the vital rates of plants in multiple ways, such as through pollination, seed dispersal, seed predation and herbivory, through redistribution of nutrients and physical alteration of the abiotic conditions, and by controlling abundances of natural enemies (Power et al. 1996; Dobson et al. 2006). Large mammals can thus have a strong influence role in the composition and structure of vegetation.

William J. McShea

Papers

Vertical habitat segregation as a mechanism for coexistence in sympatric rodents

Goals and guidelines for managing oak ecosystems for wildlife.

The Challenges of Protecting an Endangered Species in the Developing World: A Case History of Eld’s Deer Conservation in Myanmar

Protocol for camera-trap surveys of mammals at CTFS-ForestGEO sites

'In my experience...' Conflict of interests: a public hunt at the National Zoo's Conservation and Research Center.