Simulating Species Richness Using Agents with Evolving Niches, with an Example of Galápagos Plants

I sought to evolve plant species richness patterns on 22 Galápagos Islands, Ecuador, as an exploration of the utility of evolutionary computation and an agent-based approach in biogeography research. The simulation was spatially explicit, where agents were plant monocultures defined by three niche dimensions, lava (yes or no), elevation, and slope. Niches were represented as standard normal curves subjected to selection pressure, where neighboring plants bred if their niches overlapped sufficiently, and were considered the same species, otherwise they were different species. Plants that bred produced seeds with mutated niches. Seeds dispersed locally and longer distances, and established if the habitat was appropriate given the seed's niche. From a single species colonizing a random location, hundreds of species evolved to fill the islands. Evolved plant species richness agreed very well with observed plant species richness. I review potential uses of an agent-based representation of evolving niches in biogeography research

Adjustment and Sensitivity Analyses of a Beta Global Rangeland Model

G-Range is a global model that simulates generalized changes in rangelands through time, created with support from the International Livestock Research Institute. Spatial data and a set of parameters that control plant growth and other ecological attributes in landscape units combine with computer code to represent ecological process such as soil nutrient and water dynamics, vegetation growth, fire, and wild and domestic animal offtake. The model is spatial, with areas of the world divided into square cells

La evolución de la legislación sobre menores de edad delincuentes en la dictadura militar brasileña

La dictadura brasileña (1964-1985) desarrolló diversos mecanismos para el cuidado de la infancia y adolescencia marginal, como era denominada por el discurso oficial. Dentro de ese grupo de «menores» sinónimo de niños pobres- este artículo se propone aproximarse a los conocidos como menores delincuentes, y analizar cómo la normativa, el tratamiento y la ideología proyectados sobre esos muchachos y muchachas evolucionaron a lo largo de los años dictatoriales, como parte de las estrategias de consolidación y supervivencia del Régimen autoritario.-1. Introducción. -2. Los inicios del Derecho de Menores en Brasil. -3. Dictadura militar, Fundación de Bienestar del Menor y marginalidad social. -4. La normativa menorista y el progresivo endurecimiento del sistema dictatorial. -5. La década de 1970 y el aumento de la violencia contra los niños y niñas marginales. -6.El Código de Menores de 1979. El paradigma de la situación irregular. -7. De la Dictadura a la Democracia: ¿cambios en la consideración de la infancia delincuente? 8. Conclusiones. -Bibliografía

Climate Change Impacts on Livestock

This Working Paper summarizes projected climate change impacts on livestock across Africa, using a combination of literature review and some new results on the projected impacts of climate change on the rangelands of Africa. Findings show that there are many options that can help livestock keepers adapt, but there appear to be no options that are widely applicable which do not have constraints to their adoption. An enabling technical and policy environment will thus be needed to ensure livestock keepers can adapt to climate change and enhance their livelihoods and food security

Impact of climate change on African agriculture: focus on pests and diseases

According to the IPCC’s Fifth Assessment Report, changes in the climate over the last 30 years have already reduced global agricultural production by 1 – 5 % per decade relative to a baseline without climate change. In addition, recent studies indicate that even a 2 degrees increase in global temperature will affect agricultural productivity, particularly in the tropics, and this impact will rise with increases in temperature. In this context, this Info Note presents recent evidence on the implications for crops, livestock, and fisheries production, and their associated pests and diseases in Africa

Drivers of site fidelity in ungulates

1. While the tendency to return to previously visited locations—termed ‘site fidelity’—is common in animals, the cause of this behaviour is not well understood. One hypothesis is that site fidelity is shaped by an animal's environment, such that animals living in landscapes with predictable resources have stronger site fidelity. Site fidelity may also be conditional on the success of animals’ recent visits to that location, and it may become stronger with age as the animal accumulates experience in their landscape. Finally, differences between species, such as the way memory shapes site attractiveness, may interact with environmental drivers to modulate the strength of site fidelity. 2. We compared inter‐year site fidelity in 669 individuals across eight ungulate species fitted with GPS collars and occupying a range of environmental conditions in North America and Africa. We used a distance‐based index of site fidelity and tested hypothesized drivers of site fidelity using linear mixed effects models, while accounting for variation in annual range size. 3. Mule deer Odocoileus hemionus and moose Alces alces exhibited relatively strong site fidelity, while wildebeest Connochaetes taurinus and barren‐ground caribou Rangifer tarandus granti had relatively weak fidelity. Site fidelity was strongest in predictable landscapes where vegetative greening occurred at regular intervals over time (i.e. high temporal contingency). Species differed in their response to spatial heterogeneity in greenness (i.e. spatial constancy). Site fidelity varied seasonally in some species, but remained constant over time in others. Elk employed a ‘win‐stay, lose‐switch’ strategy, in which successful resource tracking in the springtime resulted in strong site fidelity the following spring. Site fidelity did not vary with age in any species tested. 4. Our results provide support for the environmental hypothesis, particularly that regularity in vegetative phenology shapes the strength of site fidelity at the inter‐annual scale. Large unexplained differences in site fidelity suggest that other factors, possibly species‐specific differences in attraction to known sites, contribute to variation in the expression of this behaviour. 5. Understanding drivers of variation in site fidelity across groups of organisms living in different environments provides important behavioural context for predicting how animals will respond to environmental change

Validation of ACE-FTS version 3.5 NOy species profiles using correlative satellite measurements

The ACE-FTS (Atmospheric Chemistry Experiment – Fourier Transform Spectrometer) instrument on the Canadian SCISAT satellite, which has been in operation for over 12 years, has the capability of deriving stratospheric profiles of many of the NO$_{γ}$ (N+ NO+ NO$_{2}$+ NO$_{3}$+ 2×N$_{2}$O$_{5}$+HNO$_{3}$+HNO$_{4}$+ClONO$_{2}$+BrONO$_{2}$) species. Version 2.2 of ACE-FTS NO, NO$_{2}$, HNO$_{3}$, N$_{2}$O$_{5}$, and ClONO$_{2}$ has previously been validated, and this study compares the most recent version (v3.5) of these five ACE-FTS products to spatially and temporally coincident measurements from other satellite instruments – GOMOS, HALOE, MAESTRO, MIPAS, MLS, OSIRIS, POAM III, SAGE III, SCIAMACHY, SMILES, and SMR. For each ACE-FTS measurement, a photochemical box model was used to simulate the diurnal variations of the NO$_{γ}$ species and the ACE-FTS measurements were scaled to the local times of the coincident measurements. The comparisons for all five species show good agreement with correlative satellite measurements. For NO in the altitude range of 25–50 km, ACE-FTS typically agrees with correlative data to within -10 %. Instrumentaveraged mean relative differences are approximately 10% at 30–40 km for NO$_{2}$, within ±7% at 8–30 km for HNO$_{3}$, better than -7% at 21–34 km for local morning N$_{2}$O$_{5}$, and better than -8% at 21–34 km for ClONO$_{2}$. Where possible, the variations in the mean differences due to changes in the comparison local time and latitude are also discussed