Financial overview and grant giving statistics of Case Western Reserve University

Financial overview and grant giving statistics of Association for Continuing Education Case Western Reserve'uni

Understanding complex responses of multiple character suites (e.g., behaviour, life history, morphology) to multifarious environments is a challenging task. Here we use a multivariate approach (partial least squares structural equation modelling) to disentangle drivers (i.e., predation, resource availability, and population demographics) of phenotypic divergence among populations of Bahamas mosquitofish (Gambusia hubbsi) inhabiting blue holes. We further employ a two-block partial least squares analysis in a novel approach to uncovering integrated and independent aspects of divergence in correlated character suites. Results suggest that phenotypic divergence mainly resulted from differences in predation regimes, with population demography and resource availability also influencing particular aspects of divergence. We uncovered statistically significant covariation of life histories and morphologies, and revealed that phenotypic divergence between predation regimes involved both integrated and independent responses. For instance, female life histories diverged mostly independently of morphology, although some morphological shifts (abdominal distension) resulted from changes in fecundity. In contrast, males showed strong morphological divergence independent of life history, but much of their life-history shifts reflected joint morphological changes (lean weight and body shape). Our study illustrates the utility of gathering disparate data types from multiple populations/species to understand the causes and nature of phenotypic divergence in the wild.

Environmental variation drives ecological and phenotypic change. How predictable is differentiation in response to environmental change? Answering this question requires the development and testing of multifarious a priori predictions in natural systems. We employ this approach using Gobiomorus dormitor populations that have colonized inland blue holes differing in the availability of fish prey. We evaluated predictions of differences in demographics, habitat use, diet, locomotor and trophic morphology, and feeding kinematics and performance between G. dormitor populations inhabiting blue holes with and without fish prey. Populations of G. dormitor independently diverged between prey regimes, with broad agreement between observed differences and a priori predictions. For example, in populations lacking fish prey, we observed male-biased sex ratios, a greater use of shallow-water habitat, and larger population diet breadths as a result of greater individual diet specialization. Furthermore, we found predictable differences in body shape, mouth morphology, suction generation capacity, strike kinematics, and feeding performance on different prey types, consistent with the adaptation of G. dormitor to piscivory when coexisting with fish prey and to feeding on small invertebrates in their absence. The results of the present study suggest great potential in our ability to predict population responses to changing environments, which is an increasingly important capability in a human-dominated, ever-changing world.

Tree demographic, tree biomass and shrub count data for two Ausplots adjacent to Credo Flux tower (Salmon Gum, SG100E and Gimlet, Gim100W). Floristic survey data and 1000 points of cover. Tree demographics was measured using a tape at 130cm for diameter and 2 different laser height finders. These gave consistently different measures and both are presented. Plot biomass was calculated from allometric regression published by Jonson and Freudenberger (2011). All shrubs with mature heights of over 0.5m were measured in ten, 10m wide by 100m transects to ensure all shrubs in the one hectare plots were counted. Floristic survey was undertaken and 1000 point intercepts recorded along 10 lines (5 north-south, 5 east-west with one point per meter) for SG100W according to Ausplots methodology (Foulkes et al., 2011)

Statistical table of case numbers by region, age group, and gender since 2003 (disease name: West Nile fever, date type: date of diagnosis, case type: confirmed case, source of infection: domestic, imported from overseas).

In this archive we share the data and R code used for the construction of population models for seven bird species (Common Starling, Black-tailed Godwit, Marsh Harrier, Eurasian Spoonbill, White Stork, Common Tern and White-tailed Eagle) for our assessment of the effects of wind farms (Schippers et al. 2020). In most cases we parameterized our population models based on species-specific survival and reproduction rates from scientific articles and reports, but in the case of the Western Marsh Harrier we analyzed previously unpublished nest success and capture-mark-resighting data. Below we first describe per species which data we used for model parameterization, and then describe per data file what each variable represents.

We selected populations of seven species based on the availability of data, considerable likelihood to collide with wind turbines and contrasting ages of first reproduction. For species for which long time series of demographic data were available with population trends clearly changing over time, we separately assessed periods with contrasting population trends, as detailed in the species descriptions below. Mean survival and reproduction rates, standard deviations and additional information like the age of first reproduction can be found in the accompanying paper by Schippers et al. (2020).

Common Starling

On the fast-slow continuum of reproductive capacity, the common starling is the fastest of the seven species we selected: it starts reproducing at an age of one year. We used the mean survival and reproductive rates for the whole Dutch breeding population (Versluijs et al. 2016), distinguishing three separate periods: 1960-1978, 1978-1990 and 1990-2012. In the first period (1960-1978) the population grew at 10% per year. This was followed by a period where the population was relatively stable (1978-1990). During the last period (1990-2012) the population declined strongly.

Black tailed Godwit

Kentie et al. (2017) studied two Dutch populations of the Black-tailed Godwit in southwestern Fryslân (Skriezekrite and Kuststrook) over four to five annual transitions (Kentie et al. 2017). Godwits started reproducing at age two, but only had 0.5-0.6 fledglings per breeding pair per year. The adults are rather long-lived with an 86% annual survival rate. We construct separate matrix models for the two populations.

Marsh Harrier

Mean vital rates of the Dutch breeding population of Marsh Harriers were estimated for 1997-2015 using respectively ring recoveries available at the Dutch Centre for Avian Migration and Demography NIOO-KNAW and reproduction data from the Dutch Raptor Working Group. Annual survival of Marsh Harriers was analyzed using live re-sightings and dead recoveries of 12,059 birds ringed as nestling between 1991 and 2016 and 74 birds ringed as ‘adult’ in the same period (due to low sample sizes, birds ringed in their first and second calendar year were lumped with older birds in the ‘adult’ category; see ‘marshHarrierSurvival.csv’ below). Nest success was estimated using data of 1914 nests, which were followed from the beginning to the end of the nest cycle, in the Netherlands between 1997 and 2015 (see ‘marshHarrierReproduction.csv’ below; we thank Rob G. Bijlsma for making the data available).

Spoonbill

For each year in the 1994-2008 period, age-specific (first-year, second-year, third-year, older) annual survival rates were derived for the Dutch Spoonbill population from van der Jeugd et al. (2014). Participation in the breeding population was 0% in the first three years and went up from 63% at age four to 95% at age 6 and older.

White Stork

Schaub et al. (2004) analyzed demographic data on White Storks in Switzerland from 1977 till 2000. Here we extracted annual survival and reproduction rates from the COMADRE Animal Matrix Database (version 2.0.1; Salguero-Gómez et al., 2016). Storks start reproducing at age 3, with breeding participation increasing with age from 48% to 100%.

Common Tern

For the Common Tern we used mean vital rate estimates published by van der Jeugd et al. (2014) for the Dutch Waddenzee population, including the Northern part of the IJsselmeer, between 2000 and 2010 (van der Jeugd et al. 2014). The total Waddenzee and IJsselmeer population is estimated at 7,630 pairs (average population 2010-2014), constituting approximately 40% of the Dutch breeding population of about 20,000 pairs (Sovon 2016).

White-tailed Eagle

Krüger et al. (2010) published demographic data on White-tailed Eagles in Schleswig-Holstein, Germany, over the period 1947 till 2008. Following these authors, and based on the two matrices in COMADRE v.2.0.1 (Salguero-Gómez et al., 2016), we used separate matrix models for the early period (stable population dynamics) and from 1975 onwards (population growth). These eagles start reproducing at age five.

Here we describe the archived files:

matrices.R

This annotated R file details how the vital rate estimates are used to construct age-structured, post-breeding-census, one-year-timestep population matrix models. In these so-called post-breeding census models the birds in the first class were 0 years old (Caswell 2001).

commonstarling19602012.csv

Mean survival and reproductive rates for the whole Dutch breeding population of Common Starlings for the time period 1960-2012.

year = start year

juvSurv = first-year survival of fledgelings

adultSurv = annual survival of older birds

fec = number of fledgelings per pair (which have a 1:1 sex ratio)

blacktailedgodwit20112016.csv

Mean survival and reproduction rates of the Black-tailed Godwit in southwestern Fryslân (populations Skriezekrite and Kuststrook) over four to five annual transitions in the period 2011-2016.

pop = population

startYear = start year

adultSurv = annual survival of older birds

chickSurv = first-year survival of chicks

nestSuc = probability that a nest is successful

marshharrier19972015.csv

Mean vital rates of the Dutch breeding population of Western Marsh Harriers for 1997-2015.

year = start year

r = number of fledgelings per pair

s1 = first-year survival of fledgelings

s2 = annual survival of older birds

marshharrierreproduction.csv

Western Marsh Harrier nest record data of in the Netherlands.

year = year

clutchSize = number of eggs

young = number of chicks (if known)

fledgelings = number of fledgelings

marshharriersurvival.csv

Ringing and resighting data (using EURING coding) on Western Marsh Harriers in the Netherlands.

ringID = ring identifier

date = observation date

metalRingInformation

1 = Metal ring added (where no metal ring was present), position (on tarsus or above) unknown or unrecorded.

2 = Metal ring added (where no metal ring was present), definitely on tarsus.

3 = Metal ring added (where no metal ring was present), definitely above tarsus.

4 = Metal ring is already present.

condition

0 = Condition completely unknown.

1 = Dead but no information on how recently the bird had died (or been killed).

2 = Freshly dead – within about a week.

3 = Not freshly dead – information available that it had been dead for more than about a week.

4 = Found sick, wounded, unhealthy etc. and known to have been released (including ring or other mark identified on a bird in poor condition without the bird having being caught).

5 = Found sick, wounded, unhealthy etc. and not released or not known if released.

6 = Alive and probably healthy but taken into captivity.

7 = Alive and probably healthy and certainly released (including ring or other mark identified on a healthy bird without the bird having being caught).

8 = Alive and probably healthy and released by a ringer (including ring or other mark identified on the bird by a ringer without the bird having being caught).

ageReported

0 = Age unknown, i.e. not recorded.

1 = Pullus: nestling or chick, unable to fly freely, still able to be caught by hand.

2 = Full-grown: able to fly freely but age otherwise unknown.

3 = First-year: full-grown bird hatched in the breeding season of this calendar year.

4 = Afer first-year: full-grown bird hatched before this calendar year; year of hatching otherwise unknown.

5 = 2nd year: a bird hatched last calendar year and now in its second calendar year.

6 = Afer 2nd year: full-grown bird hatched before last calendar year; year of hatching otherwise unknown.

7 = 3rd year: a bird hatched two calendar years before, and now in its third calendar year.

8 = Afer 3rd year: a full-grown bird hatched more than three calendar years ago (including present year as one); year if bird otherwise unknown.

9 = 4th year: a bird hatched three calendar years before, and now in its fourth calendar year.

A = Afer 4th year: a bird older than category 9 – age otherwise unknown.

sexReported

U = Unknown

M = Male

F = Female

eurasianspoonbill19942008.csv

For each year in the 1994-2008 period, age-specific (first-year, second-year, third-year, older) annual survival rates are given for the Dutch Spoonbill population.

year = start year

fled = number of fledgelings per breeding pair

s1 = first-year survival rate

s2 = second-year survival rate

s3 = third-year survival rate

s4 = older birds' annual survival rate

whitestork19772000.csv

Demographic data on White Storks in Switzerland from 1977 till 2000.

year = start year

fled = number of fledgelings per pair

sj = first-year survival of fledgelings

sa = annual survival of older birds

Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well-suited to the IPM approach. Herein, we present the first stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (Ambystoma californiense; CTS). This Bayesian model reveals that CTS population dynamics show the greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicates that long-term viability is possible with surprisingly high (20–50%) terrestrial mortality, but simultaneously identified likely minimum terrestrial buffer requirements of 600–1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically-similar species. Methods Please see the associated manuscript for full methodological details.

In 2022, there were an estimated 1.85 million cases of malaria in the Western Pacific region. The number of estimated malaria cases in the Western Pacific region in the last decade peaked in 2014, reaching over two million cases.

This statistic shows the rate of registrations of newly diagnosed cases of skin melanoma per 100,000 population in England in 2020, by region and gender. In this year, the rate of newly diagnosed cases of skin cancer among women was highest in the West Midlands region of England at 28.3 cases per 100,000 population, whereas the highest rate among men was in North West at 31.7 per 100,000 population