Determining spatial and temporal scales for management: lessons from whaling

Selection of the appropriate management unit is critical to the conservation of animal populations. Defining such units depends upon knowledge of population structure and upon the timescale being considered. Here, we examine the trajectory of eleven subpopulations of five species of baleen whales to investigate temporal and spatial scales in management. These subpopulations were all extirpated by commercial whaling, and no recovery or repopulation has occurred since. In these cases, time elapsed since commercial extinction ranges from four decades to almost four centuries. We propose that these subpopulations did not recover either because cultural memory of the habitat has been lost, because widespread whaling among adjacent stocks eliminated these as sources for repopulation, and/or because segregation following exploitation produced the abandonment of certain areas. Spatial scales associated with the extirpated subpopulations are frequently smaller than those typically employed in management. Overall, the evidence indicates that: (1) the time frame for management should be at most decadal in scope (i.e., <100 yr) and based on both genetic and nongenetic evidence of population substructure, and (2) at least some stocks should be defined on a smaller spatial scale than they currently are.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Holocene lake-level trends in the Rocky Mountains, USA

The availability of water shapes life in the western United States, and much of the water in the region originates in the Rocky Mountains. Few studies, however, have explicitly examined the history of water levels in the Rocky Mountains during the Holocene. Here, we examine the past levels of three lakes near the Continental Divide in Montana and Colorado to reconstruct Holocene moisture trends. Using transects of sediment cores and sub-surface geophysical profiles from each lake, we find that mid-Holocene shorelines in the small lakes (4–110 ha) were as much as ~10 m below the modern lake surfaces. Our results are consistent with existing evidence from other lakes and show that a wide range of settings in the region were much drier than today before 3000–2000 years ago. We also discuss evidence for millennial-scale moisture variation, including an abruptly-initiated and -terminated wet period in Colorado from 4400 to 3700 cal yr BP, and find only limited evidence for low-lake stands during the past millennium. The extent of low-water levels during the mid-Holocene, which were most severe and widespread ca. 7000–4500 cal yr BP, is consistent with the extent of insolation-induced aridity in previously published regional climate model simulations. Like the simulations, the lake data provide no evidence for enhanced zonal flow during the mid-Holocene, which has been invoked to explain enhanced mid-continent aridity at the time. The data, including widespread evidence for large changes on orbital time scales and for more limited changes during the last millennium, confirm the ability of large boundary-condition changes to push western water supplies beyond the range of recent natural variability.

Evidence for Millennial-Scale Climate Change During Marine Isotope Stages 2 and 3 at Little Lake, Western Oregon, U.S.A.

Pollen and geochemical data from Little Lake, western Oregon, suggest several patterns of millennial-scale environmental change during marine isotope stage (MIS) 2 (14,100–27,600 cal yr B.P.) and the latter part of MIS 3 (27,600–42,500 cal yr B.P.). During MIS 3, a series of transitions between warm- and cold-adapted taxa indicate that temperatures oscillated by ca. 2±–4±C every 1000–3000 yr. Highs and lows in summer insolation during MIS 3 are generally associated with the warmest and coldest intervals. Warm periods at Little Lake correlate with warm sea-surface temperatures in the Santa Barbara Basin. Changes in the strength of the subtropical high and the jet stream may account for synchronous changes at the two sites. During MIS 2, shifts between mesic and xeric subalpine forests suggest changes in precipitation every 1000–3000 yr. Increases in Tsuga heterophylla pollen at 25,000 and 22,000 cal yr B.P. imply brief warmings. Minimum summer insolation and maximum global ice-volumes during MIS 2 correspond to cold and dry conditions. Fluctuations in precipitation at Little Lake do not correlate with changes in the Santa Barbara Basin and may be explained by variations in the strength of the glacial anticyclone and the position of the jet stream.

Millennial-Scale Climate Variability during the Last Glacial Period in the Tropical Andes

Millennial-scale climate variation during the Last Glacial period is evident in many locations worldwide, but it is unclear if such variation occurred in the interior of tropical South America, and, if so, how the low-latitude variation was related to its high-latitude counterpart. A high-resolution record, derived from the deep drilling of sediments on the floor of Lake Titicaca in the southern tropical Andes, is presented that shows clear evidence of millennial-scale climate variation between ~60 and 20 ka BP. This variation is manifested by alternations of two interbedded sedimentary units. The two units have distinctive sedimentary, geochemical, and paleobiotic properties that are controlled by the relative abundance of terrigenous or nearshore components versus pelagic components. The sediments of more terrigenous or nearshore nature likely were deposited during regionally wetter climates when river transport of water and sediment was higher, whereas the sediments of more pelagic character were deposited during somewhat drier climates regionally. The majority of the wet periods inferred from the Lake Titicaca sediment record are correlated with the cold events in the Greenland ice cores and North Atlantic sediment cores, indicating that increased intensity of the South American summer monsoon was part of near-global scale climate excursions.

Weekly Problems Scales: Instruments for Sexually Abused Youth and Their Nonoffending Parents in Treatment

This study’s purpose was to determine if efficient measures could be created to assess multiple problematic behaviors identified in youth who were sexually abused and in treatment. Because of the lack of easily administered brief instruments that assess multiple domains of interest in this population, complementary parent and child assessment measures were developed. The Weekly Problems Scale–Child Version (WPSC) and the Weekly Problems Scale–Parent Version (WPS-P) were created to monitor the weekly progress of the child and family in treatment and focus specifically on common areas of difficulties in this population. Exploratory factor analysis was conducted to assist in identifying the number of underlying dimensions in the scales. Results indicate that the WPS-C and WPS-P demonstrate adequate internal consistency, temporal stability, and construct validity. The WPS-C and WPSP display significant promise as research and clinical assessment tools for use with youth who are sexually abused and their nonoffending parents in treatment.