Cayo Santiago is the oldest continuously operating free-ranging rhesus monkey colony in the world. Population control of this colony has historically been carried out by periodic live capture and removal of animals. However, the effect of such a strategy on the size, growth rate, age structure, and sex ratio of the population has not been analyzed. This study reviews past removal data and uses a population projection model to simulate the effects of different removal schemes based on Cayo Santiago demographic data from 2000–2012. The model incorporates negative density-dependence in female fertility, as well as male and female survival rates, to determine the population-level effects of selective removal by age and sex. Modeling revealed that removal of sexually immature individuals has negligible effects on the population dynamics explaining why with an initial population of 1309 in 2000 and annual removals of immature monkeys a mean annual population growth rate of 12% and a final population size of ~1,435 individuals by 2012 (~0.009 animal/m2) was observed. With no removals, the population is expected to exhibit dampened oscillations until reaching equilibrium at ~1,690 individuals (~0.0111 animal/m2) in 2100. In contrast, removal of adult females (≥4 yrs) would significantly reduce the population size, but would also promote an increase in population growth rate due to density feedback. A maximum annual production of 275 births is expected when 550 adult females are present in the population. Sensitivity analyses showed that removing females, in contrast to controlling their fertility through invasive treatments would contribute the most to changes in population growth rate. Given the density compensation on fertility, stabilizing the population would require removing ~80% of the current population of adult females. This study highlights the importance of addressing the population-level density effects, as well as sensitivity analyses, to optimize management strategies.

Reproductive synchrony and the consequent clustering of births are hypothesized to be regulated by seasonal changes in rainfall and food availability. Such climate-related seasonality is, however, questionable in tropical populations occupying temporally invariant habitats year round. Using the long-term data of the Cayo Santiago rhesus macaques from 1973 to 2013, this study distinguishes synchrony (a greater than chance clustering of births) from seasonality (a cluster of births during a period of the year when abiotic conditions are favorable) and shows that females are highly synchronized (>72% of births in a 3-month period) but the effects of environmental zeitgebers on reproduction are overridden by biological factors. Specifically, biotic and abiotic factors including (i) loss of immature offspring; (ii) population density; (iii) age at delivery; (iv) rainfall; and (v) changes in colony management were modeled in relation to the annual onset of births and the median birth date. Females experiencing loss of immature offspring had an interbirth interval of <365 days in average and the proportion of these females increased up to 48% due to changes in colony management overtime, although reproductive synchrony increased with increasing population density. A secular trend in both the onset of births and the median date of birth is documented and the model predicts that the median birth date will advance across all calendar-based seasons by 2050. The secular trend in reproduction appears to be triggered by changes in the age at delivery of females, the absence of physiological constraints from maternal investment due to offspring loss, shorter interbirth interval, and a higher degree of coordination due to increasing population density. This study challenges the reproductive phenology previously described for rhesus macaques highlighting the importance of long-term studies in addressing the ultimate causes of reproductive synchrony.

Global change poses numerous challenges to developing nations and small-island developing states (SIDSs). Among these are the effects of climate change on honeybees' provisioning services including honey production. Here we ask two questions. First, what is the relationship between honey yield and climate in a tropical environment? Second, how does yield vary spatially under current climate and future scenarios of climate change? Focusing on the island of Puerto Rico, we developed an ensemble of bioclimatic models that were used in a geographical information system to identify suitable areas for honey production under current and future scenarios of climate change. A comparison between contemporary (1998-2005) and historical honey yield data revealed a reduction in average yield, including variability, over time, with current yields averaging 5.3 L/colony. Three bioclimatic variables were retained by at least three models: temperature seasonality and mean temperature of the wettest quarter were negatively correlated with honey yields whereas precipitation of the wettest month was positively correlated. The four models varied in terms of their predictions but showed that both honey yields and areas suitable for honey production will decrease under scenarios of climate change. These results illustrate the possible impacts of climate change on honey and ultimately honeybees.

Tetanus was a major cause of mortality in the free-ranging population of rhesus monkeys on Cayo Santiago prior to 1985 when the entire colony was given its first dose of tetanus toxoid. The immediate reduction in mortality that followed tetanus toxoid inoculation (TTI) has been documented, but the long-term demographic effects of eliminating tetanus infections have not. This study uses the Cayo Santiago demographic database to construct comparative life tables 12 years before, and 12 years after, TTI. Life tables and matrix projection models are used to test for differences in: (i) survival among all individuals as well as among social groups, (ii) long-term fitness of the population, (iii) age distribution, (iv) reproductive value, and (v) life expectancy. A retrospective life table response experiment (LTRE) was performed to determine which life cycle transition contributed most to observed changes in long-term fitness of the population post-TTI. Elimination of clinical tetanus infections through mass inoculation improved the health and well-being of the monkeys. It also profoundly affected the population by increasing survivorship and long-term fitness, decreasing the differences in survival rates among social groups, shifting the population’s age distribution towards older individuals, and increasing reproductive value and life expectancy. These findings are significant because they demonstrate the long-term effects of eradicating a major cause of mortality at a single point in time on survival, reproduction, and overall demography of a naturalistic population of primates.

Predicting the invasive potential of introduced species remains an ongoing challenge due to the multiple interacting regional and global processes that facilitate the introduction and proliferation of alien species. This may be particularly true in regions where native species are increasingly reported as expanding and impacting ecosystems in ways indistinguishable from alien ones. Current approaches to assess the invasive potential of plants may be limited by the choice of traits used and the exclusion of native species. To overcome these limitations, we develop a novel approach that focuses on all species—native and alien—within a functional group of plants to predict their proliferation status. Our approach relied on the development of an extensive database of extrinsic and intrinsic traits for Puerto Rican vines with the goal of generating a predictive model of vine proliferation status. We test three hypotheses linking origin, extrinsic and intrinsic traits, and proliferation status. We found that the origin of proliferating vines was associated with only one out of seven traits, namely plant use. We also found that proliferation status was associated with all but two traits, namely life span and climbing mechanism. Finally, a classification tree analysis identified five variables as good predictors of proliferation status and used them to split the species into six groups characterized by a unique suite of traits, three of them included proliferating species. The development of tools to identify potential proliferating species is critical for management and conservation purposes. Tools that can minimize biases and make predictions based on trait data easily obtainable are particularly needed in regions with a high taxonomic and functional diversity, and with limited ecological knowledge of individual species. In addition, these tools should be capable of incorporating native species since an increasing number of native species are behaving like invasive aliens.