How decisions about fitting species distribution models affect conservation outcomes

Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10-20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.Peer reviewe

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed

Stepwise basis set selection

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146410/1/jcc25363.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146410/2/jcc25363_am.pd

Modelling fish habitat preference with a genetic algorithm-optimized Takagi-Sugeno model based on pairwise comparisons

Species-environment relationships are used for evaluating the current status of target species and the potential impact of natural or anthropogenic changes of their habitat. Recent researches reported that the results are strongly affected by the quality of a data set used. The present study attempted to apply pairwise comparisons to modelling fish habitat preference with Takagi-Sugeno-type fuzzy habitat preference models (FHPMs) optimized by a genetic algorithm (GA). The model was compared with the result obtained from the FHPM optimized based on mean squared error (MSE). Three independent data sets were used for training and testing of these models. The FHPMs based on pairwise comparison produced variable habitat preference curves from 20 different initial conditions in the GA. This could be partially ascribed to the optimization process and the regulations assigned. This case study demonstrates applicability and limitations of pairwise comparison-based optimization in an FHPM. Future research should focus on a more flexible learning process to make a good use of the advantages of pairwise comparisons

Using Ecological Modelling Tools to Inform Policy Makers of Potential Changes in Crop Distribution: An Example with Cacao Crops in Latin America

International audienceSpecies distribution models (SDM) is a powerful simulation tool that has become widely used in the ecological and agronomical sciences. The use of easily available presence data, global downscaled climate layers and software that can run on desktop computer has contributed to their popularity. The most used application is based on maximum entropy models that fit presence data to a series of environmental descriptors. SDM can be used to predict crop distribution under future conditions but the level of uncertainty of those models can be very high. The best use of these models is to be used as generators of hypothesis to be combined with other type of analysis

Implementación de un Sistema de Seguridad y Salud en el Trabajo para mejorar la productividad en la empresa Constructora General Tantas E.I.R.L, Huaral, 2020

La tesis fue elaborada con la finalidad de Implementar un Sistema de Seguridad y Salud en el Trabajo para mejorar la productividad en la Empresa Constructora General Tantas E.I.R. L, quien se encontraba con una deficiencia en el área de producción por la falta de control preventivo y de salud provocando que el recurso humano se vea afectado y en consecuencia la productividad de la empresa. Se desarrolló un marco conceptual mediante su respectiva metodología. Asimismo, se describen aspectos importantes que deben de ser efectuados para lograr una buena gestión dentro de la Organización para prevenir enfermedades, accidentes e incidentes que afecten a la mano de obra, implicando el incumplimiento de sus funciones derivadas a la producción. Bajo las características mencionadas, implementar un Sistema de Seguridad y Salud en el trabajo permitirá identificar los peligros, prevenir riesgos así tomar las medidas necesarias de control para prevenir los accidentes en el lugar de trabajo. Si bien es cierto implantar un sistema radica de cumplir ciertas normas, esto debe de ir más allá de ello, siendo el compromiso de la empresa el bienestar físico, psicológico y social de sus colaboradores ofrecer un ambiente de trabajo adecuado donde los colaboradores se sientan en armonía motivados a cumplir con sus funciones de manera eficaz y eficiente a favor que se cumple el objetivo deseado. Para el caso ya mencionado se tomaron en cuenta 16 semanas antes y después de implementar el sistema, de tal modo se logró comparar el pre y post que posteriormente se puede observar al detalle, se muestran también el estudio de los datos obtenidos en el software SPSS versión 21 teniendo como resultado que la productividad de la Empresa constructora General Tantas E.I.R.L incremento en un 54 % concluyendo de este modo que la aplicación tuvo el logro deseado en la empresa

Rol de óxido nítrico en la hipertrofia arteriolar pulmonar y ventricular cardiaca derecha en pollos a nivel del mar y expuestos a hipoxia de la altura

El síndrome ascítico es una de las principales causas de mortalidad en aves de producción de carne, siendo la hipoxia el factor desencadenante a la que se suma la respuesta del organismo mediante la liberación de diversas sustancias que conducen al cuadro patológico, tales como endotelina 1 (ET-1), óxido nítrico (ON), prostaglandinas y diversas citoquinas inflamatorias. Aún no se conoce el rol del óxido nítrico en la hipertrofia arteriolar pulmonar e hipertrofia cardiaca derecha que se observa en el síndrome ascítico. Por lo tanto, el objetivo del presente estudio fue determinar los valores de nitritos y nitratos, metabolitos estables del ON y su correlación con el grado de hipertrofia arteriolar pulmonar mediante la relación capa muscular/diámetro arteriolar (CM/DA) y con la hipertrofia cardiaca derecha mediante la relación ventrículo derecho/ventrículo total (VD/VT) y relación ventrículo derecho/peso corporal (VD/PC) en aves sometidas a hipoxia ambiental. De un mismo lote de aves machos de la línea Cobb vantres, nacidos a nivel del mar, se estudiaron 135 animales; 15 fueron sacrificados a 1 día de edad, en sus muestras se estudiaron diversas variables cuyos resultados fueron la base comparativa para los que se obtuvieron en los demás animales. Los 120 animales restantes fueron divididos en los grupos: nivel del mar (NM) 60 animales y altura (A) 60 animales. A los 10, 20, 30 y 40 días de edad se tomaron 15 aves (al azar) de cada grupo.Las variables determinadas fueron peso corporal (PC), hematocrito (Ht), nitritos y nitratos, CM/DA, VD/VT y VD/PC.Ascitic syndrome is one of the main causes of mortality in broilers, being the hypoxia the leading factor to which is added the answer of the organism by liberation of diverse sustances that conduce to the pathologic pattern, such us endotheline 1 (ET-1), nitric oxide (NO), prostaglandins and inflammatory chemokines. The rol of NO in the pulmonary arteriolar hypertrophy and right cardiac hypertrophy observed in ascitic syndrome is still unknown. Hence, the aim of this study was to obtain the values of nitrites and nitrates, stable metabolites of NO, and its correlation with the degree of pulmonary arteriole hypertrophy through the muscular wall/arteriolar diameter (CM/DA) ratio, the right ventricular hypertrophy through the right ventricle/total ventricle (RV/TV) ratio and right ventricle/body weight (RV/BW) ratio in chickens rised at environmental hypoxia. A total of 135 male, Cobb vantres chickens and born at sea level were studied; 15 of them were sacrificed at 1 day age and diverse variables were determinate in their samples whose results were used as comparative base line for those of the other animals. The reminder 120 chickens were distributed in the groups: Sea Level (SL) 60 birds and altitude (A) 60 birds. At 10, 20, 30 and 40 days old, 15 chicken were taken randomly to measure body weight (BW), hematocrite (Ht), nitrites and nitrates, MW/AD, RV/VT and RV/BW.Tesi