Evaluating knowledge integration and co-production in a 2-year collaborative learning process with smallholder dairy farmer groups

Although knowledge integration and co-production are integral to transdisciplinary approaches to foster sustainable change in social–ecological systems, this type of research is usually not evaluated based on assessments of the learning process. While participants are meant to be central in such approaches, too often, their perspectives are not central to the evaluation. Moreover, there is limited empirical information about how new knowledge is transformed into action. We respond to these knowledge gaps by analyzing (A) farmers’ perspectives on the collaborative learning process and (B) how farmers’ new knowledge can serve as the basis for changed actions. Theoretically, we are guided by second-order cybernetics and have integrated the Control Loop Model with Learning Loops to extend Kirkpatrick (Evaluating training programs: the four levels, 2nd edn. Berrett-Koehler Publisher, San Francisco, 1998) four-level evaluation scheme. We apply this to evaluate a 2-year collaborative learning process with two smallholder dairy farmer groups in Nakuru County, Kenya that aimed to co-develop local sustainable pathways to reduce milk losses. Results showed that farmers learned by (1) implementing corrective actions based on known cause–effect relations (single-loop learning); (2) discovering new cause–effect relations and testing their effect (double-loop learning); and (3) further questioning and changing their aims (triple-loop learning). Highlighting the importance of knowledge integration and co-production, this collaboration between farmers, researchers, and field assistants improved the farmers’ ability to respond, adapt, and intentionally transform their farming system in relation with complex sustainability challenges. Results demonstrate that the potential of our evaluation scheme to better reflect learning and empowerment experienced by actors involved in transdisciplinary research for sustainability.     

Anishnaabe Aki: an indigenous perspective on the global threat of invasive species

Conservation discourses tend to portray invasive species as biological entities temporally connected to colonial timelines, using terms such as “alien”, “colonizing”, “colonial”, and “native”. This focus on a colonial timeline emerges from scientific publications within conservation biology and invasion ecology and is enacted through invasive species management by state and NGO actors. Colonialism is influential for indigenous nations in myriad ways, but in what ways do indigenous understandings of invasive species engage with colonialism? We conducted ethnographic research with indigenous Anishnaabe communities to learn about the ways Anishnaabe people conceptualize invasive species as a phenomenon in the world and were gifted with three primary insights. First, Anishnaabe regard plants, like all beings, as persons that assemble into nations more so than “species”. The arrival of new plant nations is viewed by some Anishnaabe as a natural form of migration. The second insight highlights the importance of actively discovering the purpose of new species, sometimes with the assistance of animal teachers. Lastly, while Anishnaabe describe invasive species as phenomenologically entangled with colonialism, the multiple ways Anishnaabe people think about invasive species provide alternatives to native–non-native binaries that dominate much of the scientific discourse.     

Human–nature connectedness as a ‘treatment’ for pro-environmental behavior: making the case for spatial considerations

The degree to which an individual feels connected to the natural world can be a positive predictor of pro-environmental behavior (PEB). This has led to calls to ‘reconnect to nature’ as a ‘treatment’ for PEB. What is not clear is the relationship between where one feels connected to nature and where one acts pro-environmentally. We propose that integrating spatial scale into the conceptualization of these constructs will provide insights into how different degrees of connectedness influence pro-environmental behavior. We discuss trends towards a spatial understanding of human–nature connectedness (HNC) and introduce three archetypes that highlight scalar relationships between scale of connectedness and scale of pro-environmental behavior: (1) equal interactions, (2) embedded interactions, and (3) extended interactions. We discuss potential policy and practice implications of taking a spatially explicit approach to HNC–PEB research, and propose a research agenda for investigating these scalar relationships that can inform nature as a ‘treatment’ intervention.     

Factors Affecting Predator-Prey Distribution in a Protected Area,Tehran, Iran (a Case with Wolves and Wild Sheep)

We tried to model habitat suitability of two prey and predator species including wild sheep (Ovis orientalis) and wolf (Canis lupus) in Varjin protected area located in northern east of Tehran using a presence only method, maximum entropy (MaxEnt). Totally 11 environmental variables were measured in the species presence points which can be classified in three groups including topographical, vegetation and distal variables. Resulted maps indicated that habitat variables such as slope (ranging from 35 to 40 percent) and elevation (lower than 1700 meters above sea level) are both institute those factors which mostly affect studied prey and predator habitat use. Our results regarding prey and predator geographical range of used habitat indicated that wolves cover most area than wild sheep which show more dispersed habitat resources for the prey species. ENMTools test revealed that wolf’s niche breadth is more than twice as much as wild sheep’s. Wild sheep in Varjin protected area has a relatively narrow geographical extent and shows a tendency to marginal habitats while wolves cover obviously more areas which denotes its high mobility and low dependency to specific habitats.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Quantifying the squeezing or stretching of fisheries as they adapt to displacement by marine reserves

The designation of no‐take marine reserves involves social and economic concerns due to the resulting displacement of fishing effort, when fishing rights are removed from those who traditionally fished within an area. Displacement can influence the functioning of the fishery and success of the reserve, yet levels of displacement are seldom quantified after reserve implementation and very rarely before that. We devised a simple analytical framework based on set theory to facilitate reserve placement. Implementation of the framework requires maps of fishing grounds, fishing effort, or catch per unit effort for at least 2 years. The framework quantifies the level of conflict that a reserve designation might cause in the fishing sector due to displacement and the opportunities to offset the conflict through fisher spatial mobility (i.e., ability of fishers to fish elsewhere). We also considered how the outputs of the framework can be used to identify targeted management interventions for each fishery. We applied the method in Honduras, where the largest marine protected area in Central America is being placed, for which spatial data on fishing effort were available for 6 fisheries over 3 years. The proposed closure had a greater negative impact on the shrimp and lobster scuba fisheries, which concentrated respectively 28% and 18% of their effort inside the reserve. These fisheries could not accommodate the displacement within existing fishing grounds. Both would be forced to stretch into new fishing grounds, which are available but are of unknown quality. These stakeholders will likely require compensation to offset costly exploratory fishing or to travel to fishing grounds farther away from port.     

Characterizing the Width of Amphibian Movements During Postbreeding Migration

Habitat linkages can help maintain connectivity of animal populations in developed landscapes. However, the lack of empirical data on the width of lateral movements (i.e., the zigzagging of individuals as they move from one point to point another) makes determining the width of such linkages challenging. We used radiotracking data from wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in a managed forest in Maine (U.S.A.) to characterize movement patterns of populations and thus inform planning for the width of wildlife corridors. For each individual, we calculated the polar coordinates of all locations, estimated the vector sum of the polar coordinates, and measured the distance from each location to the vector sum. By fitting a Gaussian distribution over a histogram of these distances, we created a population‐level probability density function and estimated the 50th and 95th percentiles to determine the width of lateral movement as individuals progressed from the pond to upland habitat. For spotted salamanders 50% of lateral movements were ≤13 m wide and 95% of movements were ≤39 m wide. For wood frogs, 50% of lateral movements were ≤17 m wide and 95% of movements were ≤ 51 m wide. For both species, those individuals that traveled the farthest from the pond also displayed the greatest lateral movement. Our results serve as a foundation for spatially explicit conservation planning for pond‐breeding amphibians in areas undergoing development. Our technique can also be applied to movement data from other taxa to aid in designing habitat linkages. Caracterización de la Amplitud de Movimiento de Anfibios durante la Migración Pos‐Reproducción     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción