Density‐dependent behavior underpins white‐tailed deer (Odocoileus virginianus) theory and management application in North America, but strength or frequency of the phenomenon has varied across the geographic range of the species. The modifying effect of stochastic environments and poor‐quality habitats on density‐dependent behavior has been recognized for ungulate populations around the world, including white‐tailed deer populations in South Texas, USA. Despite the importance of understanding mechanisms influencing density dependence, researchers have concentrated on demographic and morphological implications of deer density. Researchers have not focused on linking vegetation dynamics, nutrition, and deer dynamics. We conducted a series of designed experiments during 2004–2012 to determine how strongly white‐tailed deer density, vegetation composition, and deer nutrition (natural and supplemented) are linked in a semi‐arid environment where the coefficient of variation of annual precipitation exceeds 30%. We replicated our study on 2 sites with thornshrub vegetation in Dimmit County, Texas. During late 2003, we constructed 6 81‐ha enclosures surrounded by 2.4‐m‐tall woven wire fence on each study site. The experimental design included 2 nutrition treatments and 3 deer densities in a factorial array, with study sites as blocks. Abundance targets for low, medium, and high deer densities in enclosures were 10 deer (equivalent to 13 deer/km²), 25 deer (31 deer/km²), and 40 deer (50 deer/km²), respectively. Each study site had 2 enclosures with each deer density. We provided deer in 1 enclosure at each density with a high‐quality pelleted supplement ad libitum, which we termed enhanced nutrition; deer in the other enclosure at each density had access to natural nutrition from the vegetation. We conducted camera surveys of deer in each enclosure twice per year and added or removed deer as needed to approximate the target densities. We maintained >50% of deer ear‐tagged for individual recognition. We maintained adult sex ratios of 1:1–1:1.5 (males:females) and a mix of young and older deer in enclosures. We used reconstruction, validated by comparison to known number of adult males, to make annual estimates of density for each enclosure in analysis of treatment effects. We explored the effect of deer density on diet composition, diet quality, and intake rate of tractable female deer released into low‐ and high‐density enclosures with natural nutrition on both study sites (4 total enclosures) between June 2009 and May 2011, 5 years after we established density treatments in enclosures. We used the bite count technique and followed 2–3 tractable deer/enclosure during foraging bouts across 4 seasons. Proportion of shrubs, forbs, mast, cacti, and subshrubs in deer diets did not differ (P > 0.57) between deer density treatments. Percent grass in deer diets was higher (P = 0.05) at high deer density but composed only 1.3 ± 0.3% (SE) of the diet. Digestible protein and metabolizable energy of diets were similar (P > 0.45) between deer density treatments. Likewise, bite rate, bite size, and dry matter intake did not vary (P > 0.45) with deer density. Unlike deer density, drought had dramatic (P ≤ 0.10) effects on foraging of tractable deer. During drought conditions, the proportion of shrubs and flowers increased in deer diets, whereas forbs declined. Digestible protein was 31%, 53%, and 54% greater (P = 0.06) during non‐drought than drought during autumn, winter, and spring, respectively. We studied the effects of enhanced nutrition on the composition and quality of tractable female deer diets between April 2007 and February 2009, 3 years after we established density treatments in enclosures. We also estimated the proportion of supplemental feed in deer diets. We used the 2 low‐density enclosures on each study site, 1 with enhanced nutrition and 1 with natural nutrition (4 total enclosures). We again used the bite count technique and 2–3 tractable deer living in each enclosure. We estimated proportion of pelleted feed in diets of tractable deer and non‐tractable deer using ratios of stable isotopes of carbon. Averaged across seasons and nutrition treatments, shrubs composed a majority of the vegetation portion of deer diets (44%), followed by mast (26%) and forbs (15%). Enhanced nutrition influenced the proportion of mast, cacti, and flowers in the diet, but the nature and magnitude of the effect varied by season and year. The trend was for deer in natural‐nutrition enclosures to eat more mast. We did not detect a statistical difference (P = 0.15) in the proportion of shrubs in diets between natural and enhanced nutrition, but deer with enhanced nutrition consumed 7–24% more shrubs in 5 of 8 seasons. Deer in enhanced‐nutrition enclosures had greater (P = 0.03) digestible protein in their overall diet than deer in natural‐nutrition enclosures. The effect of enhanced nutrition on metabolizable energy in overall diets varied by season and was greater (P < 0.04) for enhanced‐nutrition deer during summer and autumn 2007 and winter 2008. In the enhanced‐nutrition treatment, supplemental feed averaged 47–80% of the diet of tractable deer. Of non‐tractable deer in all density treatments with enhanced nutrition, 97% (n = 128 deer) ate supplemental feed. For non‐tractable deer averaged across density treatments, study sites, and years, percent supplemental feed in deer diets exceeded 70% for all sex and age groups. We determined if increasing deer density and enhanced nutrition resulted in a decline in preferred forbs and shrubs and an increase in plants less preferred by deer. We sampled all 12 enclosures via 20, 50‐m permanent transects in each enclosure. Percent canopy cover of preferred forbs was similar (P = 0.13) among deer densities averaged across nutrition treatments and sampling years (low density: = 8%, SE range 6–10; medium density: 5%, 4–6; high density: 4%, 3–5; SE ranges are presented because SEs associated with backtransformed means are asymetrical). Averaged across deer densities, preferred forb canopy cover was similar between nutrition treatments in 2004; but by 2012 averaged 20 ± 17–23% in enhanced‐nutrition enclosures compared to 10 ± 8–13% in natural‐nutrition enclosures (P = 0.107). Percent canopy cover of other forbs, preferred shrubs, other shrubs, and grasses, as well as Shannon's index, evenness, and species richness were similar (P > 0.10) among deer densities, averaged across nutrition treatments and sampling years. We analyzed fawn:adult female ratios, growth rates of fawns and yearlings, and survival from 6 to 14 months of age and for adults >14 months of age. We assessed adult body mass and population growth rates (lambda apparent, λ_APP) to determine density and nutrition effects on deer populations in the research enclosures during 2004–2012. Fawn:adult female ratios declined (P = 0.04) from low‐medium density to high density in natural‐nutrition enclosures but were not affected (P = 0.48) by density in enhanced nutrition enclosures although, compared to natural nutrition, enhanced nutrition increased fawn:adult female ratios by 0.15 ± 0.12 fawns:adult female at low‐medium density and 0.44 ± 0.17 fawns:adult female at high density. Growth rate of fawns was not affected by deer density under natural or enhanced nutrition (P > 0.17) but increased 0.03 ± 0.01 kg/day in enhanced‐nutrition enclosures compared to natural nutrition (P < 0.01). Growth rate of yearlings was unaffected (P > 0.71) by deer density, but growth rate increased for males in some years at some density levels in enhanced‐nutrition enclosures. Adult body mass declined in response to increasing deer density in natural‐nutrition enclosures for both adult males (P < 0.01) and females (P = 0.10). Enhanced nutrition increased male body mass, but female mass did not increase compared to natural nutrition. Survival of adult males was unaffected by deer density in natural‐ (P = 0.59) or enhanced‐ (P = 0.94) nutrition enclosures. Survival of adult females was greatest in medium‐density enclosures with natural nutrition but similar at low and high density (P = 0.04). Enhanced nutrition increased survival of females (P < 0.01) and marginally for males (P = 0.11). Survival of fawns 6–14 months old was unaffected (P > 0.35) by density in either natural‐ or enhanced‐nutrition treatments but was greater (P = 0.04) under enhanced nutrition. Population growth rate declined (P = 0.06) with increasing density in natural‐nutrition enclosures but not (P = 0.55) in enhanced nutrition. Enhanced nutrition increased λ_APP by 0.32. Under natural nutrition, we found only minor effects of deer density treatments on deer diet composition, nutritional intake, and plant communities. However, we found density‐dependent effects on fawn:adult female ratios, adult body mass, and population growth rate. In a follow‐up study, deer home ranges in our research enclosures declined with increasing deer density. We hypothesized that habitat quality varied among home ranges and contributed to density‐dependent responses. Variable precipitation had a greater influence on deer diets, vegetation composition, and population parameters than did deer density. Also, resistance to herbivory and low forage quality of the thornshrub vegetation of our study sites likely constrained density‐dependent behavior by deer. We posit that it is unlikely that, at our high‐density (50 deer/km²) and perhaps even medium‐density (31 deer/km²) levels, negative density dependence would occur without several wet years in close association. In the past century, this phenomenon has only happened once (1970s). Thus, density dependence would likely be difficult to detect in most years under natural nutrition in this region. Foraging by deer with enhanced nutrition did not result in a reduction in preferred plants in the vegetation community and had a protective effect on preferred forbs because ≤53% of deer diets consisted of vegetation. However, enhanced nutrition improved fitness of individual deer and deer populations, clearly demonstrating that nutrition is limiting for deer populations under natural conditions in western South Texas. © 2019 The Authors. Wildlife Monographs published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

中文翻译：

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在随机环境中链接白尾鹿的密度，营养和植被

依赖密度的行为是白尾鹿（Odocoileus virginianus）的基础）理论和管理在北美的应用，但是这种现象的强度或发生频率在物种的地理范围内有所不同。随机环境和劣质生境对密度依赖性行为的改变作用已被世界上有蹄类种群（包括美国南德克萨斯州的白尾鹿种群）认识到。尽管了解影响密度依赖性的机制很重要，但研究人员仍专注于人口密度和形态对鹿密度的影响。研究人员还没有集中精力将植被动态，营养和鹿动态联系在一起。我们在2004-2012年进行了一系列设计实验，以确定白尾鹿密度，植被组成，在半干旱的环境中，年降水量的变异系数超过30％，而鹿的营养（天然的和补充的）则与之联系在一起。我们在得克萨斯州迪米特县的2个有刺灌木植被的地点重复了我们的研究。在2003年下半年，我们在每个研究站点上建造了6个81公顷的围墙，周围环绕着2.4米高的编织铁丝网。实验设计包括2种营养处理和3种鹿密度的阶乘阵列，以研究地点为块。围栏中低，中和高鹿密度的丰度目标是10鹿（相当于13鹿/公里）每个研究地点的4层高编织金属丝网围栏。实验设计包括2种营养处理和3种鹿密度的阶乘阵列，以研究地点为块。围栏中低，中和高鹿密度的丰度目标是10鹿（相当于13鹿/公里）每个研究地点的4层高编织金属丝网围栏。实验设计包括2种营养处理和3种鹿密度的阶乘阵列，以研究地点为块。围栏中低，中和高鹿密度的丰度目标是10鹿（相当于13鹿/公里）²），25鹿（31鹿/ km ²）和40鹿（50鹿/ km ²）。每个研究地点都有2个围栏，每个围栏都具有鹿的密度。我们在每个密度的1个围栏中随意提供高质量的颗粒状补品鹿，我们称之为增强营养；处于不同密度的其他围栏中的鹿都可以从植被中获取自然营养。我们每年对每个围栏中的鹿进行两次相机调查，并根据需要添加或删除鹿以近似目标密度。我们保留了超过50％的鹿耳标签以供个人识别。我们将成年雌性比例保持在1：1–1：1.5（雄性：雌性），并在围栏中混合了幼年和年长的鹿。我们使用重建技术（通过与已知数量的成年男性进行比较来验证），对治疗效果的分析中每个围栏的密度进行年度估算。我们探索了鹿密度对日粮组成，日粮质量的影响，2009年6月至2011年5月之间，即我们在隔离圈中进行密度处理的5年之后，在两个研究地点（具有4个隔离圈）向具有自然营养的低密度和高密度圈养的易处理母鹿的摄取率进行了研究。我们使用了叮咬计数技术，并在4个季节的觅食回合中追踪了2-3个可处理的鹿/圈地。鹿日粮中灌木，前叉，肥大，仙人掌和半灌木的比例没有差异（P  > 0.57）。 在高鹿密度下，鹿日粮中的草百分比较高（P = 0.05），但只占日粮的1.3±0.3％（SE）。日粮 之间的可消化蛋白质和代谢能相似（P > 0.45）。同样，叮咬率，叮咬大小和干物质摄入量也不随 鹿的密度而变化（P > 0.45）。不像鹿密度，干旱有显着（P 上的易处理的鹿觅食≤0.10）的影响。在干旱条件下，鹿日粮中灌木和花朵的比例增加，而草则减少。可消化蛋白质分别增加31％，53％和54％（P = 0.06）分别是秋季，冬季和春季非干旱时期的干旱。我们在2007年4月至2009年2月（即我们在鸡舍内建立密度处理后的3年）之间研究了增强营养对易处理雌性鹿日粮组成和质量的影响。我们还估计了鹿饲料中补充饲料的比例。我们在每个研究地点使用了2个低密度围栏，其中1个围栏营养增强，1个围栏自然营养（总共4个围栏）。我们再次使用了咬数技术和每个围栏中生活的2-3只可驯鹿。我们使用碳的稳定同位素比率估算了可加工鹿和不可加工鹿日粮中颗粒饲料的比例。根据季节和营养处理的平均值，灌木占鹿饮食中植被的大部分（44％），其次是桅杆（26％）和前叉（15％）。营养的增强影响了饮食中肥大，仙人掌和花朵的比例，但影响的性质和程度因季节和年份而异。趋势是自然营养围栏中的鹿要吃更多的肥大肥肉。我们没有发现统计差异（ 在自然营养和增强营养之间的日粮中灌木的比例为P = 0.15），但营养增强的鹿在8个季节中的5个季节中消耗了7-24％的灌木。强化营养围栏 中的鹿比天然营养围栏中的鹿具有更高的（P = 0.03）可消化蛋白质。营养增加对总体饮食中代谢能的影响因季节而异， 在2007年夏季和秋季以及2008年冬季，营养增强的鹿对营养的影响更大（P <0.04）。在营养增强的处理中，补充饲料的平均含量为47-80％的鹿的饮食。在所有密度较高的营养强化处理中，顽固性鹿中有97％（n = 128头鹿）吃了补充饲料。对于在密度处理，研究地点和年份中平均的难吃鹿，在所有性别和年龄组中，鹿饮食中补充饲料的百分比均超过70％。我们确定了鹿密度的增加和营养的增加是否导致偏爱的小灌木丛和灌木的减少以及不那么受鹿偏爱的植物的增加。我们通过每个机柜中的20、50-m永久样条对所有12个机柜进行了采样。 在营养处理和采样年平均鹿密度中，优选的小树冠覆盖率相似（P = 0.13）（低密度：= 8％，SE范围为6-10；中密度：5％，4-6；高密度：4％，3-5；之所以提供SE范围，是因为与反向转换后的均值相关联的SE是不对称的。从鹿的密度平均来看，2004年营养处理之间首选的树冠覆盖率相似。但是到2012年，营养强化型箱的平均利用率为20±17–23％，而自然营养型箱的平均值为10±8–13％（P  = 0.107）。其他灌木，首选灌木，其他灌木和草的冠层覆盖率以及Shannon指数，均匀度和物种丰富度相似（P > 0.10）的鹿密度，在营养治疗和采样年间平均。我们分析了小鹿：成年雌性的比率，小鹿和一岁的增长率以及6至14个月大的成年和大于14个月成年的成活率。我们评估了成年体重和人口增长率（表观λ，_λAPP），以确定密度和营养对2004-2012年研究围栏内鹿种群的影响。 在自然营养条件下，小鹿：成年雌性比例从中低密度降低到高密度（P = 0.04），但没有受到影响（P = 0.48），尽管与天然营养相比，增强营养使小鹿：成年雌性比增加了0.15±0.12小鹿：成年雌性在低中密度，而0.44±0.17小鹿：成年雌性比在高密度中增加了。在自然或强化营养下，小鹿的生长速度不受鹿密度的影响（P  > 0.17），但与天然营养相比，强化营养围栏中小鹿的生长速度增加了0.03±0.01 kg /天（P  <0.01）。 鹿的密度对一岁鸡的生长率没有影响（P > 0.71），但是在强化营养围栏中，某些密度的雄性鸡的生长率在某些年份有所提高。成年雄性由于自然营养围栏中鹿密度的增加，成年体重下降（P  <0.01）和女性（P  = 0.10）。营养增强会增加男性体重，但与自然营养相比女性体重不会增加。在自然（P  = 0.59）或增强型（P  = 0.94）营养围栏中，成年雄性的存活不受鹿密度的影响。成年雌性的存活率在具有自然营养的中等密度围栏中最大，但在低密度和高密度条件下相似（P  = 0.04）。营养增强会提高女性的生存率（P  <0.01），而男性的生存率则略有提高（P  = 0.11）。 在自然营养或强化营养处理中，密度在6至14个月大的小鹿的存活率均未受到影响（P > 0.35），但存活率更高（P  = 0.04）。 随着自然营养围栏密度的增加，人口增长率下降（P = 0.06），而营养 增强则没有（P = 0.55）。营养增强增加_λAPP0.32。在自然营养下，我们发现鹿密度处理对鹿的饮食组成，营养摄入和植物群落只有很小的影响。但是，我们发现密度对小鹿：成年雌性比例，成年体重和人口增长率的依赖关系。在一项后续研究中，随着鹿密度的增加，我们研究围栏内的养鹿场范围有所减少。我们假设栖息地质量因家庭范围而异，并且对依赖密度的反应做出了贡献。与鹿的密度相比，可变的降水量对鹿的饮食，植被组成和种群参数的影响更大。此外，我们研究地点的刺灌木植被对草食动物的抵抗力和低草料质量可能限制了鹿的密度依赖性行为。我们认为，以我们的高密度（50鹿/公里）²）甚至中等密度（31 Deer / km ²）水平，如果没有几个湿润年份的紧密联系，就会出现负密度依赖性。在过去的一个世纪中，这种现象只发生过一次（1970年代）。因此，在该地区的自然营养条件下，大多数年份可能很难检测到密度依赖性。营养增强的鹿觅食并不会减少植被群落中的首选植物，并且对首选的草有保护作用，因为≤53％的鹿日粮由植物组成。然而，营养的增强改善了个体鹿和鹿种群的适应性，这清楚地证明了营养在南德克萨斯州西部自然条件下对鹿种群的限制。©2019作者。野生动物专着 由Wiley Periodicals，Inc.代表“野生动物协会”出版。