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

-Microhabitat selection of the Kentucky Warbler (Oporornis formosus), a forestinterior Neotropical migrant, was examined using a geographical information system. The distribution of territorial male Kentucky Warblers was mapped within a 460-ha study area in northwestern Virginia from 1979 through 1992. Each annual distribution of territories was compared, using logistic regression, to a random distribution of territories with respect to habitat features codified within a vector-based geographical information system. Kentucky Warblers selected forested areas with cove hardwoods and avoided oak/hickory overstory. The warblers also were found more often in areas that contained streams and in areas with low white-tailed deer (Odocoileus virginianus) densities. Since 1979 there have been significant shifts in Kentucky Warbler use of habitat at this site, resulting in fewer territories within oak/hickory and edge habitats. Received 22 November 1993, accepted 31 August 1994. KENTUCKY WARBLERS (Oporornis formosus) are insectivorous, ground-nesting birds that breed within the interior forests of the northeastern United States and winter from southern Mexico to South America. This species is one of many wood-warblers that has shown an apparent decline over the last two decades (Robbins et al. 1989) and, therefore, is of particular interest to land managers and conservationists. In studies using multivariate analysis to describe forest bird communities, Kentucky Warblers were found to be associated with large, mature forests that possess a dense understory (Lynch and Whigham 1984, Robbins et al. 1989). As with most wood-warbler species, however, little is known of specific microhabitat requirements beyond the valuable, but anecdotal, reports from early naturalists (Chapman 1907, DeGaris 1936, Bent 1953) and annual surveys that detected population declines (Robbins et al. 1989). Declines within some unmanaged forests have been postulated to be due to an increased density of white-tailed deer (Odocoileus virginianus; Boone and Dowell 1986, Robbins 1991) through reduced density of understory shrubs. Geographical information systems (GIS) have been used successfully to model habitat requirements of Sage Grouse (Centrocercus urophasianus; Homer et al. 1993) and Wild Turkey (Meleagris gallopavo; Donovan et al. 1987). These models, however, identified landscape-scale features that were associated with flocks or populations of birds and, thus, may be inappropriate for analysis of habitat use by individual birds within a forest block. Given that Kentucky Warblers inhabit mature, deciduous forests, it may be possible to determine how they are distributed within this landscape-scale habitat using a GIS. Since 1979 extensive surveys for Kentucky Warblers have been conducted at the National Zoological Park's Conservation and Research Center (CRC). This site is a small (1,200-ha), protected area in the Blue Ridge Mountains of Virginia, 5 km south-southeast of Front Royal, Virginia. These annual surveys can be compared to vegetation and habitat attribute maps recently produced for the study area with a GIS. We examine: whether landscape level features and habitat measures derived from aerial photographs, when organized within a GIS, are suitable for quantifying habitat requirements of small forest birds; whether shifts in habitat use are detectable; and what factors might precipitate habitat shifts.

Long-term trends in habitat selection by Kentucky Warblers

We report the study of parental care of Wood Thrush (Hylocichla mustelina) fledglings from nest-leaving to independence. From 1993 to 1995, we captured, radio-tagged, and monitored the movements and behavior of 23 fledglings and their parents from 12 broods at the U.S. Marine Corps Base, Quantico, Virginia. For pairs that subsequently renested (n = 5), the family group of male, female, and fledglings, remained within 62 (±5 SE) m of the first nest after fledging. During the period of post-fledging parental care, mean maximum distance between parents was 70 (±14) m. Females attended the young 13 (±1.3) days before initiating the incubation of a second clutch. Males continued attending the fledglings for 6 (±0.7) more days until the young achieved independence and dispersed (28–36 days post-hatching). In final clutches (n = 7), brood care was divided between the parents, and the position of the fledglings relative to the nest depended on the parents' choice of molting site (in the nesting area or e...

Parental care of fledgling wood thrushes

Predators affect prey directly by removing animals from the population and indirectly by modifying prey behavior. Humans have extirpated apex predators from many ecosystems, and the extent to which smaller predators, or humans themselves, can ecologically replace apex predators remains uncertain. White-tailed deer Odocoileus virginianus in the Eastern United States were released from their two most important predators a century ago following the extirpation of cougars Puma concolor and wolves Canis lupus. We studied the extent to which perceived predation risk from humans and a newly arrived mesopredator, the coyote, Canis latrans affects deer behavior, predicting that deer will be most vigilant in areas hunted by humans which also have the highest levels of coyote activity. We quantified deer vigilance rates in 33 natural areas of which 15 allowed hunting, across six states by evaluating the head posture of 3470 deer photographed at unbaited camera traps. We documented wide variation in coyote activity (0–2.5 detections/day) and human activity (0–306 detections/day), but contrary to our predictions, did not find strong positive relationships between deer vigilance and either of these predators. Deer vigilance was lower in areas with high levels of human recreation, suggesting that deer become habituated to the presence of humans. Vigilance increased across the fall season in both hunted and non-hunted populations, which suggests that increased vigilance may be associated more with mating behavior or environmental factors other than hunting. Our results show that variation in coyote and human activity does not significantly impact the vigilance behavior of white-tailed deer year-round, suggesting that deer rely on other risk-avoidance behaviors or neither are functioning as apex predators in the region.

Deer on the lookout: how hunting, hiking and coyotes affect white-tailed deer vigilance

Distribution and abundance of oaks in North America.

Occupancy models are popular for estimating the probability a site is occupied by a species of interest when detection is imperfect. Occupancy models have been extended to account for interacting species and spatial dependence but cannot presently allow both factors to act simultaneously. We propose a two-species occupancy model that accommodates both interspecific and spatial dependence. We use a point-referenced multivariate hierarchical spatial model to account for both spatial and interspecific dependence. We model spatial random effects with predictive process models and use probit regression to improve efficiency of posterior sampling. We model occupancy probabilities of red fox (Vulpes vulpes) and coyote (Canis latrans) with camera trap data collected from six mid-Atlantic states in the eastern United States. We fit four models comprising a fully factorial combination of spatial and interspecific dependence to two-thirds of camera trapping sites and validated models with the remaining data. Red fox and coyotes each exhibited spatial dependence at distances > 0.8 and 0.4 km, respectively, and exhibited geographic variation in interspecific dependence. Consequently, predictions from the model assuming simultaneous spatial and interspecific dependence best matched test data observations. This application highlights the utility of simultaneously accounting for spatial and interspecific dependence.

https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1890/15-1193.1

William J. McShea

Papers

Long-term trends in habitat selection by Kentucky Warblers

Parental care of fledgling wood thrushes

Deer on the lookout: how hunting, hiking and coyotes affect white-tailed deer vigilance

Distribution and abundance of oaks in North America.

A two-species occupancy model accommodating simultaneous spatial and interspecific dependence.