The Power of Strategic Mission Investing

A growing number of foundations are offering low-interest loans, buying into green business ventures, and investing in other asset classes to advance their missions. Yet most mission investing remains haphazard and inconsequential. To bring about real change, foundations need to take a fundamentally different approach, making strategic mission investments that complement their grantmaking. Authors Mark Kramer and Sarah Cooch talk about strategic mission investing in the Fall 2007 issue of Stanford Social Innovation Review

Aggregating Impact: A Funder's Guide to Mission Investment Intermediaries

This report provides a guide to mission investment intermediaries, organizations that collect capital from multiple sources and reinvest it in people and enterprises, whether nonprofit or for-profit, that deliver both social impact and financial returns. A growing number of foundations and other funders are beginning to use such intermediaries versus making mission investments directly. This is due to a number of advantages that intermediaries can provide, such as ease of investment, reduced risk, lower transaction costs, specialized expertise, performance reporting, and an expanded deal flow. Yet research disclosed that many funders are unaware of the wide range of mission investment intermediaries that are available and of the advantages they can offer. The authors provide an overview of mission investment intermediaries and how foundations use them, the benefits and challenges of investing in intermediaries, and an analysis of available intermediaries that address economic development, housing and the environment

Compounding Impact: Mission Investing by U.S. Foundations

This recently published report provides the first comprehensive analysis of mission investing by U.S. foundations. The study, funded by The David and Lucile Packard Foundation, analyzes the mission investment activity of 92 U.S. foundations, which have made a combined total of $2.3 billion of mission investments. Mission investing is a more specific type of social investing, and represents the use of financial investments as tools to achieve a foundation's mission. Through interviews with foundations and extensive data collection, FSG assembled a rich picture of current and historical mission investment activity stretching back almost 40 years. The study found that the number of foundations engaged in mission investing has doubled in recent years, and the amount of funds committed annually has tripled. Although most mission investments are still low-interest loans, foundations are increasingly using equity and other investments that generate market-rate returns. Surprisingly, most of the growth has been driven by smaller foundations with assets under$200 million

Investing for Impact - Managing and Measuring Proactive Social Investments

This 2006 study, commissioned by the Shell Foundation, and prepared by FSG, sees strong growth and opportunity in the nascent field of proactive social investment (PSI). In a typical PSI, a socially-responsible corporation or a charitable foundation uses its capital to invest in new enterprises that can play a critical role in alleviating a societal problem. Although still a very small share of investments, the report estimates that PSIs total nearly US$15 billion, and are attracting increasing interest among foundations and corporations. The study, based on in-depth interviews with 36 pioneers in social investment from the US and Europe, validates the belief that PSIs can simultaneously deliver measurable social benefits and attractive rates of return

Population dynamics

Increases or decreases in the size of populations over space and time are, arguably, the motivation for much of pure and applied ecological research. The fundamental model for the dynamics of any population is straightforward: the net change over time in the abundance of some population is the simple difference between the number of additions (individuals entering the population) minus the number of subtractions (individuals leaving the population). Of course, the precise nature of the pattern and process of these additions and subtractions is often complex, and population biology is often replete with fairly dense mathematical representations of both processes. While there is no doubt that analysis of such abstract descriptions of populations has been of considerable value in advancing our, there has often existed a palpable discomfort when the ‘beautiful math’ is faced with the often ‘ugly realities’ of empirical data. In some cases, this attempted merger is abandoned altogether, because of the paucity of ‘good empirical data’ with which the theoretician can modify and evaluate more conceptually–based models. In some cases, the lack of ‘data’ is more accurately represented as a lack of robust estimates of one or more parameters. It is in this arena that methods developed to analyze multiple encounter data from individually marked organisms has seen perhaps the greatest advances. These methods have rapidly evolved to facilitate not only estimation of one or more vital rates, critical to population modeling and analysis, but also to allow for direct estimation of both the dynamics of populations (e.g., Pradel, 1996), and factors influencing those dynamics (e.g., Nichols et al., 2000). The interconnections between the various vital rates, their estimation, and incorporation into models, was the general subject of our plenary presentation by Hal Caswell (Caswell & Fujiwara, 2004). Caswell notes that although interest has traditionally focused on estimation of survival rate (arguably, use of data from marked individuals has been used for estimation of survival more than any other parameter, save perhaps abundance), it is only one of many transitions in the life cycle. Others discussed include transitions between age or size classes, breeding states, and physical locations. The demographic consequences of these transitions can be captured by matrix population models, and such models provide a natural link connecting multi–stage mark–recapture methods and population dynamics. The utility of the matrix approach for both prospective, and retrospective, analysis of variation in the dynamics of populations is well–known; such comparisons of results of prospective and retrospective analysis is fundamental to considerations of conservation management (sensu Caswell, 2000). What is intriguing is the degree to which these methods can be combined, or contrasted, with more direct estimation of one or more measures of the trajectory of a population (e.g., Sandercock & Beissinger, 2002). The five additional papers presented in the population dynamics session clearly reflected these considerations. In particular, the three papers submitted for this volume indicate the various ways in which complex empirical data can be analyzed, and often combined with more classical modeling approaches, to provide more robust insights to the dynamics of the study population. The paper by Francis & Saurola (2004) is an example of rigorous analysis and modeling applied to a large, carefully collected dataset from a long–term study of the biology of the Tawny Owl. Using a combination of live encounters and dead recoveries, the authors were able to separate the relative contributions of various processes (emigration, mortality) on variation in survival rates. These analyses were combined with periodic matrix models to explore comparisons of direct estimation of changes in population size (based on both census and mark–recapture analysis) with model estimates. The utility of combining sources of information into analysis of populations was the explicit subject of the other two papers. Gauthier & Lebreton (2004) draw on a long–term study of an Arctic–breeding Goose population, where both extensive mark–recapture, ring recovery, and census data are available. The primary goal is to use these various sources of information to to evaluate the effect of increased harvests on dynamics of the population. A number of methods are compared; most notably they describe an approach based on the Kalman filter which allows for different sources of information to be used in the same model, that is demographic data (i.e. transition matrix) and census data (i.e. annual survey). They note that one advantage of this approach is that it attempts to minimize both uncertainties associated with the survey and demographic parameters based on the variance of each estimate. The final paper, by Brooks, King and Morgan (Brooks et al., 2004) extends the notion of the combining information in a common model further. They present a Bayesian analysis of joint ring–recovery and census data using a state–space model allowing for the fact that not all members of the population are directly observable. They then impose a Leslie–matrix–based model on the true population counts describing the natural birth–death and age transition processes. Using a Markov Chain Monte Carlo (MCMC) approach (which eliminates the need for some of the standard assumption often invoked in use of a Kalman filter), Brooks and colleagues describe methods to combine information, including potentially relevant covariates that might explain some of the variation, within a larger framework that allows for discrimination (selection) amongst alternative models. We submit that all of the papers presented in this session indicate clearly significant interest in approaches for combining data and modeling approaches. The Bayesian framework appears a natural framework for this effort, since it is able to not only provide a rigorous way to evaluate and integrate multiple sources of information, but provides an explicit mechanism to accommodate various sources of uncertainty about the system. With the advent of numerical approaches to addressing some of the traditionally ‘tricky’ parts of Bayesian inference (e.g., MCMC), and relatively user–friendly software, we suspect that there will be a marked increase in the application of Bayesian inference to the analysis of population dynamics. We believe that the papers presented in this, and other sessions, are harbingers of this trend

The effects of stem-girdling on ectomycorrhizal fungi growth and nitrogen cycling.

General EcologyEctomycorrhizal (ECM) fungi have a symbiotic relationship with tree roots; the fungi make various nutrients in the soil, specifically nitrogen, accessible to trees in exchange for the carbohydrates produced by the tree via photosynthesis (Smith and Read 2008). This relationship makes hyphal growth of ECM fungi a relevant substrate for studying nitrogen cycling in forest ecosystems. Under the Forest Accelerated Succession ExperimenT (FASET), tree girdling was used to replicate disturbance and early forest succession. Labeled nitrogen was used to examine nutrient flux in hyphae varied by experimental plots. Although no significant relationship was found between stem-girdling and nitrogen levels in ECM fungi, nor stem-girdling and hyphae biomass, more data was added to the FASET study.http://deepblue.lib.umich.edu/bitstream/2027.42/89431/1/VanDyke_Cooch_Gold_Weiler_2011.pd

Do foraging methods in winter affect morphology during growth in juvenile snow geese?

Physical exertion during growth can affect ultimate size and density of skeletal structures. Such changes from different exercise regimes may explain morphological differences between groups, such as those exhibited by lesser snow geese (Chen caerulescens caerulescens; hereafter snow geese) foraging in southwest Louisiana. In rice-prairie habitats (hereafter rice-prairies), snow geese bite off or graze aboveground vegetation, whereas they dig or grub for subterranean plant parts in adjacent coastal marshes. Grubbing involves considerably more muscular exertion than does grazing. Thus, we hypothesized that rates of bone formation and growth would be lower for juveniles wintering in rice-prairies than those in coastal marshes, resulting in smaller bill and skull features at adulthood. First, we tested this exertion hypothesis by measuring bills, skulls, and associated musculature from arrival to departure (November-February) in both habitats in southwest Louisiana, using both banded birds and collected specimens. Second, we used the morphological data to test an alternative hypothesis, which states that smaller bill dimensions in rice-prairies evolved because of hybridization with Ross's geese (C.rossii). Under the exertion hypothesis, we predicted that bill and skull bones of juveniles would grow at different rates between habitats. However, we found that bill and skull bones of juveniles grew similarly between habitats, thus failing to support the exertion hypothesis. Morphometrics were more likely to differ by sex or change with sampling date than to differ by habitat. We predicted that significant, consistent skewness toward smaller birds could indicate hybridization with Ross's geese, but no skewness was observed in our morphological data, which fails to support the hybridization hypothesis. Further research is needed to clarify whether snow geese wintering in Louisiana represent a single polymorphic population that segregates into individually preferred habitats, which we believe at present to be more likely as an explanation than two ecologically and spatially distinct morphotypes.Canadian Wildlife Service, Louisiana Department of Wildlife and Fisheries (LDWF), Delta Waterfowl Foundation, Rockefeller Scholarship Program, USGS-Louisiana Cooperative Fish and Wildlife Research Unit, Graduate School; Agricultural Center, School of Renewable Natural Resources at Louisiana State UniversityPeer Reviewe

Exploring Barriers to Exercise among Adolescents at the Burlington Boys and Girls Club

Introduction: The Boys and Girls Club of Burlington (BGCB) is a non-profit that holds after-school activities for adolescents, including music, art, technology, and sports. The BGCB has struggled to encourage physical activity (PA) among many participants. We designed our study to identify deterrents to PA, as well as possible ways to improve participation.https://scholarworks.uvm.edu/comphp_gallery/1066/thumbnail.jp

Standardising terminology and notation for the analysis of demographic processes in marked populations

The development of statistical methods for the analysis of demographic processes in marked animal populations has brought with it the challenges of communication between the disciplines of statistics, ecology, evolutionary biology and computer science. In order to aid communication and comprehension, we sought to root out a number of cases of ambiguity, redundancy and inaccuracy in notation and terminology that have developed in the literature. We invited all working in this field to submit topics for resolution and to express their own views. In the ensuing discussion forum it was then possible to establish a series of general principles which were, almost without exception, unanimously accepted. Here we set out the background to the areas of confusion, how these were debated and the conclusions which were reached in each case. We hope that the resulting guidelines will be widely adopted as standard terminology in publications and in software for the analysis of demographic processes in marked animal populationspostprin