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

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

The Journal of the Acoustical Society of America

In this review we report new findings concerning interaction between marine debris and wildlife. Deleterious effects and consequences of entanglement, consumption and smothering are highlighted and discussed. The number of species known to have been affected by either entanglement or ingestion of plastic debris has doubled since 1997, from 267 to 557 species among all groups of wildlife. For marine turtles the number of affected species increased from 86 to 100 % (now 7 of 7 species), for marine mammals from 43 to 66 % (now 81 of 123 species) and for seabirds from 44 to 50 % of species (now 203 of 406 species). Strong increases in records were also listed for fish and invertebrates, groups that were previously not considered in detail. In future records of interactions between marine debris and wildlife we recommend to focus on standardized data on frequency of occurrence and quantities of debris ingested. In combination with dedicated impact studies in the wild or experiments, this will allow more detailed assessments of the deleterious effects of marine debris on individuals and populations.

/pdf/deleterious-effects-of-litter-on-marine-life-20031a25xa.pdf

Deleterious Effects of Litter on Marine Life

Global increases in environmental noise levels – arising from expansion of human populations, transportation networks, and resource extraction – have catalysed a recent surge of research into the effects of noise on wildlife. Synthesising a coherent understanding of the biological consequences of noise from this literature is challenging. Taxonomic groups vary in auditory capabilities. A wide range of noise sources and exposure levels occur, and many kinds of biological responses have been observed, ranging from individual behaviours to changes in ecological communities. Also, noise is one of several environmental effects generated by human activities, so researchers must contend with potentially confounding explanations for biological responses. Nonetheless, it is clear that noise presents diverse threats to species and ecosystems and salient patterns are emerging to help inform future natural resource-management decisions. We conducted a systematic and standardised review of the scientific literature published from 1990 to 2013 on the effects of anthropogenic noise on wildlife, including both terrestrial and aquatic studies. Research to date has concentrated predominantly on European and North American species that rely on vocal communication, with approximately two-thirds of the data set focussing on songbirds and marine mammals. The majority of studies documented effects from noise, including altered vocal behaviour to mitigate masking, reduced abundance in noisy habitats, changes in vigilance and foraging behaviour, and impacts on individual fitness and the structure of ecological communities. This literature survey shows that terrestrial wildlife responses begin at noise levels of approximately 40 dBA, and 20% of papers documented impacts below 50 dBA. Our analysis highlights the utility of existing scientific information concerning the effects of anthropogenic noise on wildlife for predicting potential outcomes of noise exposure and implementing meaningful mitigation measures. Future research directions that would support more comprehensive predictions regarding the magnitude and severity of noise impacts include: broadening taxonomic and geographical scope, exploring interacting stressors, conducting larger-scale studies, testing mitigation approaches, standardising reporting of acoustic metrics, and assessing the biological response to noise-source removal or mitigation. The broad volume of existing information concerning the effects of anthropogenic noise on wildlife offers a valuable resource to assist scientists, industry, and natural-resource managers in predicting potential outcomes of noise exposure.

https://www.wildliferesearch.co.uk/Wildlife_Research/Publications_files/A%20synthesis%20of%20two%20decades%20of%20research%20documenting%20the%20effects%20of%20noise%20on%20wildlife%20Shannon.pdf

A synthesis of two decades of research documenting the effects of noise on wildlife

Faced with the problem of mapping accurately the Tawny owl's territories, we used spectrographic analyses of the recorded territorial calls to distinguish the different individual males. From November 1986 to August 1988 we collected about 2000 hootings from different Tawny owls. The visual analysis of the spectrograms revealed a high degree of inter-individual variation and a certain amount of intra-individual variation in the song, so that we have submitted a sample of 140 calls of 17 identified individuals to univariate and multivariate analyses, in order to reach objective conclusions. Seven temporal parameters of the song were selected and measured. The coefficient of variation for each parameter and the test of homogeneity of variances between two series of calls of the same owl showed a stability over time of the selected parameters. On the other hand, the ANOVA test indicated that all the parameters of song varied significantly within the population and discriminant analysis provided a correct cla...

Individual recognition of male Tawny owls (Strix aluco) using spectrograms of their territorial calls

Background 
Mass strandings of sperm whales (Physeter macrocephalus) remain peculiar and rather unexplained events, which rarely occur in the Mediterranean Sea. Solar cycles and related changes in the geomagnetic field, variations in water temperature and weather conditions, coast geographical features and human activities have been proposed as possible causes. In December 2009, a pod of seven male sperm whales stranded along the Adriatic coast of Southern Italy. This is the sixth instance from 1555 in this basin.


Methodology/Principal Findings 
Complete necropsies were performed on three whales whose bodies were in good condition, carrying out on sampled tissues histopathology, virology, bacteriology, parasitology, and screening of veins looking for gas emboli. Furthermore, samples for age determination, genetic studies, gastric content evaluation, stable isotopes and toxicology were taken from all the seven specimens.

The animals were part of the same group and determined by genetic and photo-identification to be part of the Mediterranean population. Causes of death did not include biological agents, or the “gas and fat embolic syndrome”, associated with direct sonar exposure. Environmental pollutant tissue concentrations were relatively high, in particular organochlorinated xenobiotics. Gastric content and morphologic tissue examinations showed a prolonged starvation, which likely caused, at its turn, the mobilization of lipophilic contaminants from the adipose tissue. Chemical compounds subsequently entered the blood circulation and may have impaired immune and nervous functions.


Conclusions/Significance 
A multi-factorial cause underlying this sperm whales' mass stranding is proposed herein based upon the results of postmortem investigations as well as of the detailed analyses of the geographical and historical background. The seven sperm whales took the same “wrong way” into the Adriatic Sea, a potentially dangerous trap for Mediterranean sperm whales. Seismic surveys should be also regarded as potential co-factors, even if no evidence of direct impact has been detected.

/pdf/sometimes-sperm-whales-physeter-macrocephalus-cannot-find-36ol70n15r.pdf

Sometimes Sperm Whales (Physeter macrocephalus) Cannot Find Their Way Back to the High Seas: A Multidisciplinary Study on a Mass Stranding

Bioacoustics approaches in biodiversity inventories

Males of two freshwater Italian gobies, the common goby, Padogobius martensii and the panzarolo goby, Knipowitschia punctatissima, emit trains of low-frequency pulses, i.e. ‘drumming’ sounds, in the presence of a ripe female in the nest. In P, martensii the drumming sound is usually followed by a tonal sound (complex sound). Examination of the pulse structure suggests that these sounds are produced by muscles acting on the swimbladder. Both species exhibited high emission rates of spawning sounds, especially before the beginning of oviposition. Moreover, spawning sound production ceased only after the female abandoned the nest, which always occurred at the end of oviposition. This is the first study reporting the production among fishes of distinct sounds during protracted spawning. Unlike sounds produced just before mating by fishes with planktonic or demersal zygotes, the spawning sound production of these gobies does not function to coordinate mating events in the nest. The presence of a two-part vocalization by male P. martensii even suggests a functional dichotomy of spawning sounds in this species.

Spawning vocalizations in male freshwater gobiids (Pisces, Gobiidae)

In this paper the breeding sound production among gobiids is reviewed. Results of recent comparative studies on both pre‐spawning (courtship) and spawning sound production in the three italian freshwater gobiids are reported. A significant production of sounds associated to mating was discovered in two of these species. Furthermore, the quantification of acoustic behaviour across the spawning period (i.e., from the beginning of oviposition until the departure of the female from the male's nest) revealed a pattern of spawning sound production similar in the two species.

Gianni Pavan

Papers

Individual recognition of male Tawny owls (Strix aluco) using spectrograms of their territorial calls

Sometimes Sperm Whales (Physeter macrocephalus) Cannot Find Their Way Back to the High Seas: A Multidisciplinary Study on a Mass Stranding

Bioacoustics approaches in biodiversity inventories

Spawning vocalizations in male freshwater gobiids (Pisces, Gobiidae)

Sound production during courtship and spawning among freshwater gobiids (pisces, gobiidae)