Responses to potential threats to welfare vary greatly between species. Even closely related animals often differ in their fear of humans and/or novelty; their behavioural responses to pain; and when captive, their overall welfare and the form and frequency of their stereotypies. Such species differences stimulate hypotheses about I) the way that responses to challenge co-vary with other biological traits; 2) the adaptive value of particular responses; and 3) the factors predicting responses to evolutionarily new scenarios, such as captivity. We illustrate how these ideas can be statistically tested with multi-species comparisons, and show how techniques such as the Comparative Analysis of Independent Contrasts can be used to control for any non-independence of data points caused by species’ relatedness. For each of the three types of hypothesis, we then provide several welfare-relevant examples including one that has been fully tested (respectively, the relationships between sociality and anti-predator behaviour in antelopes; predation pressure, foraging niche and neophobia in parrots; and home range size and stereotypy in carnivores). Ultimate explanations such as these, based on species’ ecology and evolutionary history, have great explanatory appeal. Species comparisons can also have great practical value, allowing the test of hypotheses that would be almost impossible to investigate experimentally, and generating principles that allow predictions about the welfare of similar unstudied species. Multi-species data, for example from the many taxa held in zoos, thus hold enormous potential for increasing the fundamental understanding of animal welfare.

Microhabitat characteristics can be used as a proxy to predict the community structure of associated organisms and evaluate their vulnerability to habitat degradation. Microhabitat-specific and ectothermic taxa (like many reptiles) are among the best models to study responses to changing habitats and climate. We examined the niche breadth and guild structure of reptiles from Agasthyamalai Hills in the southern Western Ghats of India based on microhabitat use data. We recorded a total of 47 reptile species from 1,554 observations comprising two major orders and 11 families. Niche breadth analysis revealed that 45% of reptiles are microhabitat specialists, indicating the importance of protecting their habitats with all structural attributes. Cluster analysis grouped reptile species into four major guilds based on microhabitat preferences. The forest floor-dwelling guild was the largest group with 25 species, followed by the semi-arboreal guild with 12 species. The floor-dwelling guild also exhibited both the highest number of microhabitat specialists (n = 11) and globally threatened species (n = 3), highlighting the need for preserving ground cover characteristics such as leaf litter, boulders, and open ground for conserving reptiles in the region. Considering the microhabitat specializations within the community, we recommend a dynamic approach to monitor abundance, diversity, and habitat quality across the Agasthyamalai landscape to better conserve its rich reptile diversity.

Field studies were conducted from 1998 through 2000 to compare weed population shifts in soybean and cotton using a total glyphosate system, preemergence (PRE) herbicides followed by glyphosate, and a conventional herbicide program. In the first year of the soybean study, populations of hemp sesbania were highest for treatments of PRE herbicides followed by either glyphosate or the conventional herbicide program because of better control from the total glyphosate system. Barnyardgrass populations in the first year of the study for the nontreated plots were 0 plants/m2 but increased in the third year to 61 plants/m2. Flumetsulam plus metolachlor followed by glyphosate at the lower rates and the nontreated check were the only treatments in which there was an increase in barnyardgrass over the 3-yr study. Broadleaf signalgrass populations increased in the third year with 0.1 kg ai/ha flumetsulam plus 2.1 kg ai/ha metolachlor followed by 0.84 kg ae/ha glyphosate, primarily because of reduced competition from lower populations of other weeds such as hemp sesbania. Pitted morningglory populations for all treatments decreased in the third year because of good control of this species and the high level of interference from other weed species in the first 2 yr. Johnsongrass populations decreased in the third year with 0.4 kg ai/ha flumetsulam plus 1.1 kg ai/ha metolachlor followed by 0.84 kg/ha glyphosate. Johnsongrass populations decreased with timely glyphosate sequential applications, with 5 plants/m2 in 1998 and 0 plants/m2 in 2000. Yields increased from the first year to the second year, corresponding to reduced weed pressure, and yields varied from 710 to 1,420 kg/ha. Because of weed pressure, soybean yields were not different in any of the treatments, including the nontreated, although treatments changed the species present. In the cotton study, weed populations over the 3 yr decreased, with the most significant reductions from the treatments of fluometuron plus prometryn plus metolachlor followed by either pyrithiobac or glyphosate. Weeds that showed the most significant decline were barnyardgrass and hemp sesbania, whereas johnsongrass increased, with 27 plants/m2 in treatments of 0.6 kg ai/ha fluometuron plus 0.3 kg ai/ha prometryn plus 0.7 kg ai/ha metolachlor followed by 0.84 kg/ha glyphosate. Lint cotton yields varied from 0 to 128 kg/ha. Because of the weed pressure, cotton yields were not different in any of the treatments, although treatments changed the species present. This research has shown that weed species can decrease over time with the continued use of any of these herbicide programs.

Nonnative, invasive plants are becoming increasingly widespread and abundant throughout the southwestern United States, leading to altered fire regimes and negative effects on native plant communities. Models of potential invasion are pertinent tools for informing regional management. However, most modeling studies have relied on occurrence data, which predict the potential for nonnative establishment only and can overestimate potential risk. We compiled locations of presence and high abundance for two problematic, invasive plants across the southwestern United States: red brome (Bromus rubens L.) and African mustard (Brassica tournefortii Gouan). Using an ensemble of five climate projections and two types of distribution model (MaxEnt and Bioclim), we modeled current and future climatic suitability for establishment of both species. We also used point locations of abundant infestations to model current and future climatic suitability for abundance (i.e., impact niche) of both species. Because interpretations of future ensemble models depend on the threshold used to delineate climatically suitable from unsuitable areas, we applied a low threshold (1 model of 10) and a high threshold (6 or more models of 10). Using the more-conservative high threshold, suitability for Bromus rubens presence expands by 12%, but high abundance contracts by 42%, whereas suitability for Brassica tournefortii presence and high abundance contract by 34% and 56%, respectively. Based on the low threshold (worst-case scenario), suitability for Bromus rubens presence and high abundance are projected to expand by 65% and 64%, respectively, whereas suitability for Brassica tournefortii presence and high abundance expand by 29% and 28%, respectively. The difference between results obtained from the high and low thresholds is indicative of the variability in climate models for this region but can serve as indicators of best- and worst-case scenarios.

The objective of this study is to estimate possible impacts of global climate change on the geographical distribution of the African lion Panthera leo in the coming decades. Current lion population occurrence data across Africa and distributions of lions in historical times (6,000–100 years before present) were obtained from the literature and integrated with data on present-day climates to generate ecological niche models. Models based on distributions of African lions were tested for predictive ability based on various subsetting approaches and were projected across Asia, Africa and Europe, to retrodict the distribution of the species for the past 6,000 years. These models were highly accurate, giving confidence in future projections. Future potential distributions were predicted by projecting ecological niche models onto three climate scenarios of future greenhouse gas emissions based on eight climate models for the years 2040–2070. The prediction was of relative range stability into the future: few new areas were identified as becoming suitable for the species but large areas of southern Africa and West Africa are expected to become less suitable. Predictions of effects of climate change on potential distributions of lions may assist conservation efforts by clarifying options for mitigation and response.

For land-breeding marine organisms such as seabirds, knowledge about their habitat use has mainly been gained through studies of breeding individuals that are constrained to return frequently to their breeding grounds. In this study we set out to measure whether: a) habitat selection in the non-breeding period predicts habitat selection in the breeding period, and b) whether breeding individuals concentrated their activity on the closest suitable habitats. Macaroni Eudyptes chrysolophus and gentoo Pygoscelis papua penguins, two marine predators with contrasting foraging strategies, were tracked from the Iles Kerguelen and their habitat selection investigated through Mahalanobis distances factorial analysis. This study presents the first data about gentoo penguins’ juvenile dispersal. For both species, results showed 6.9 times larger maximum ranges and up to 12.2 times greater distances travelled during the non-breeding period. Habitat suitability maps suggested both species made similar environmental selections whatever the period. Macaroni penguins targeted pelagic areas beyond the shelf break while gentoo penguins always remained over the shelf. We consider the ecological significance of larger scale movements made outside the breeding period and suggest that this non-breeding period is of particular interest when attempting to understand an animal's habitat selection.

The occurrence of most species is linked to the distribution of specific combinations of environmental variables that define their occupied niche. As a result, the relationship between environmental variables and species occurrence can be used to model species distribution. However, when collecting data to construct such models, it is preferable to ensure that the survey coverage is representative of all available habitat combinations within the area as a whole to ensure that the model does not under- or over-estimate the actual species distribution. By using multi-variate statistical techniques, a habitat representativeness score (HRS) can be calculated to provide an objective assessment of whether a specific survey coverage will collect (or has collected) data that are representative of all available habitat variable combinations in an area. To demonstrate this approach, HRSs calculated using principal component analysis were used to assess the minimum number of evenly-spaced parallel north–south surveys required to adequately survey two study areas with differing levels of environmental heterogeneity for all available combinations of four habitat variables. For the more environmentally homogeneous study area, the HRS suggests that for this survey design a minimum of five evenly-spaced parallel transects, covering around 5% of the study area, would be required to obtain representative survey coverage for these four variables. However, for the more heterogeneous study area, at least eight evenly-spaced parallel transects, covering around 9% of the study area, would be required. Therefore, for a given survey design, more survey effort is required to obtain a representative survey coverage when the survey area is more variable. In both cases, conducting fewer surveys than these minimum values would produce an unrepresentative data set and this could potentially lead to the production of species distribution models that do not accurately reflect the true species distribution.